The Sermon Library Problem: What Chegg’s Collapse Taught Me About AI and Product-Market Fit

I run a product that helps pastors prepare sermons. We have 245,000+ sermons in our library, decades of content, and a subscription model that’s worked for years. Pastors come to SermonCentral when they’re stuck, when they need inspiration, when Sunday is three days away and the blank page is winning.

And for the first time in my career, I’m looking at that model and asking: Is our product-market fit about to evaporate?

The Treadmill You Don’t See Moving

Reforge published a piece that hit me like a gut punch. The core argument: product-market fit is a treadmill, not a destination. The bar for what customers consider “good enough” is always rising, and AI just cranked the speed to a sprint.

Here’s the part that stuck with me: unlike previous tech shifts that unfolded over years, AI causes the PMF threshold to spike exponentially, giving incumbent solutions no time to adapt before losing relevance.

Mobile took a decade to reshape industries. Cloud computing gave companies 5–7 years to migrate. AI? The examples are already piling up.

Chegg lost 87.5% of its valuation. Stack Overflow saw traffic crater. These were category leaders with massive content libraries and loyal user bases.

Sound familiar?

The Chegg Parallel Is Uncomfortably Close

Let me lay this out plainly.

Chegg’s model: a massive library of human-created study content, monetized through subscriptions, behind a paywall. Students paid because they couldn’t get the answers anywhere else. Then ChatGPT showed up. Suddenly, students could get comparable answers, for free, instantly, with no subscription required.

Now replace “students” with “pastors” and “study content” with “sermon outlines.” Replace “ChatGPT” with SermonAI, Sermon Snap, or honestly just ChatGPT itself with a decent prompt.

The structural vulnerability is identical: a content library behind a paywall, AI that generates comparable output for free, and a “good enough” bar that resets overnight.

I talk to pastors every week. More of them are experimenting with AI tools for sermon prep. Most are cautious about it — but it solves their immediate problem: “I’m stuck and Sunday is coming.”

The Real Strategic Question

Here’s where most product leaders get it wrong. The knee-jerk reaction is: “We’ll just bolt AI onto our existing product.” Slap a chatbot on the homepage. Add an AI summary feature. Ship it fast.

That misses the deeper question: is your product the platform people use AI through, or the platform that AI makes redundant?

If you’re a content library and you add AI search, you’re still a content library. You’ve made the existing model slightly better, but the customer’s mental model hasn’t changed. They’re still coming to you for content, and AI is still generating that content for free elsewhere.

The real pivot is harder. It means rethinking what your product actually is.

For SermonCentral, the strategic move is “AI-powered sermon prep workspace where our library is an input, not the product.” The library becomes training data, context, theological grounding — the thing that makes our AI better than generic ChatGPT. The product becomes the workflow.

Three Questions Every SaaS Leader Should Be Asking Right Now

If you run a content-library or knowledge-base product — and honestly, this applies to most subscription SaaS — here’s the framework I’m using:

1. Can AI generate a “good enough” version of your core deliverable? Be brutally honest. Can AI give my customer something that clears their bar? For many use cases, 70% quality delivered instantly beats 95% quality behind a paywall. If the answer is yes, your paywall is losing its teeth.

2. What does your product offer that AI alone cannot? This is where you find your moat — or discover you don’t have one. For SermonCentral, it’s community validation (knowing 10,000 other pastors used this sermon), exegetical depth that’s been peer-reviewed, denominational fit, and sermon series planning that accounts for the liturgical calendar. These are things a generic AI doesn’t know to consider. Your version of this list is your survival strategy.

3. Are your current users already using AI tools alongside your product? If you don’t know, find out this week. A simple exit survey question, an onboarding poll, a one-question email. If even 15–20% of your users are experimenting with AI alternatives, the adaptation window is already closing.

The Window Is Smaller Than You Think

With previous technology shifts — mobile, cloud, social — companies had years to adapt. You could see the wave coming, form a committee, hire a consultant, run a pilot, iterate for a few quarters, and still catch up.

AI doesn’t work like that. The window slams shut before you recognize the threat severity. Chegg didn’t see a slow decline and choose not to respond. They saw a cliff, and by the time they recognized it, they were already falling.

The work we’re doing right now at SermonCentral — instrumenting whether our users are using AI sermon tools, prototyping AI-augmented workflows that use our library as an input rather than competing with free generation, rethinking activation so that a new user’s first 48 hours deliver something AI alone cannot — is existential work.

What’s Actually Scarce

The companies who survive this shift will be the ones who rebuilt their products around the assumption that AI-generated content is free and abundant — and then found the thing that’s scarce.

For church tech, what’s scarce is trust. Theological accuracy. Community wisdom. The peace of mind that comes from knowing your sermon was shaped by a tradition, not just generated by a machine.

Those things have real value. But only if we build products that deliver them in ways a pastor can feel on a Tuesday night when Sunday is looming.

The treadmill is speeding up. Time to change direction before it throws you off.


Your Turn: Apply This Today

Use these questions to pressure-test whether your product is the next Chegg — or the one that replaces it:

  • Name the task your product completes. Write it in one sentence from the user’s perspective: “When I need to ______, I use ______.” If AI can now complete that task in 30 seconds, your moat is eroding. Be honest.
  • Run the “AI substitute” test. Have someone on your team try to accomplish your product’s core job-to-be-done using only ChatGPT or Claude. Document exactly where the AI falls short. That gap is your defensible surface.
  • Map your unique data assets. What does your product know that a general-purpose AI cannot access? User history, community content, proprietary datasets? If the answer is “nothing,” that’s your most urgent product risk.
  • Identify your highest-engagement users and interview three of them. Ask them directly: “Have you tried using AI tools for what you use us for? What happened?” Their answer will tell you more than any dashboard.
  • Rewrite your product’s value proposition for the AI era. Your old version assumed AI wasn’t available. Rewrite it assuming users have access to powerful AI. What do you still uniquely offer? That’s your actual pitch.
  • Set a 90-day “substitution risk review.” Put a recurring calendar item to evaluate how much of your product’s core workflow can now be replicated by AI. Treat it as a competitive threat review, not a tech curiosity.

Is your SaaS product facing a similar AI-driven PMF threat? I help product leaders think through competitive positioning and strategic pivots in the age of AI. Let’s talk.

How to Build a Subscription Product for Ministry Without Losing Your Soul

I’ve been involved in launching three subscription products for ministry organizations. Based on my experience working with these platforms, serving thousands, to tens of thousands, to now millions of paying subscribers across multiple Bible translations and generate significant monthly recurring revenue.

Here’s what I learned: the hardest part isn’t building the paywall. It’s deciding what belongs behind it.

Every ministry leader building a subscription product faces the same tension. Your mission says “go into all the world” (Mark 16:15). Your business model says “pay to access the good stuff.” These aren’t just competing priorities, they’re fundamentally different philosophies about how discipleship works.

I’ve been on both sides of this equation. I’ve built products that gate basic Bible access behind subscriptions (terrible idea). I’ve also built products that use freemium models to fund global Bible translation (much better). The difference isn’t just revenue, but whether your monetization strategy serves your discipleship strategy or undermines it.

Three Models, Three Different Answers

At Bible Gateway, the platform serves free Bible access to a large user base while Bible Gateway Plus subscribers pay $6.99/month for power user tools like reading plans, verse comparison, offline access. The core content stays free. The professional ministry tools require subscription.

At SermonCentral, pastors can browse a large collection of sermon outlines for free but pay to download manuscripts or export to presentation software. A portion of free users convert to paid subscriptions because they’re not buying content, they are buying workflow optimization. The convenience is why they subscribe.

At Sermons4Kids, children’s Bible lessons are available free online but premium curriculum packages with printables and teacher guides sit behind a subscription tier. Churches get the ministry impact for free. Paid subscribers get the operational efficiency.

Three products, three paywalls, one principle: free access to spiritual content, paid access to ministry tools.

The Gap Between Free and Any Price

The hardest conversion in ministry isn’t $3.99 to $14.99. It’s $0 to $3.99.

Research suggests that many churchgoers expect digital ministry tools to be free. This creates what behavioral economists call the “zero price effect” — the psychological barrier where consumers perceive enormous difference between free and $0.01.

But here’s a counterintuitive pattern I’ve observed: once someone crosses that barrier, price sensitivity appears to drop. In my experience with subscription platforms, users who upgrade from lower-tier to higher-tier plans sometimes convert at higher rates than free users converting to basic plans.

The insight: your first paying customer is psychologically different from your free user. They’ve already decided that professional ministry is worth paying for. Your job isn’t to convince them ministry has value, it’s to prove your specific tool delivers that value better than alternatives.

The 90-Day Rule

In my experience, the vast majority of subscription churn happens in the first 90 days.

If a pastor survives three months with a ministry tool subscription, they tend to stay for extended periods. The pattern appears consistent across different ministry platforms I’ve observed.

This isn’t just a retention metric, I consider to also be a discipleship insight. The users who integrate these tools into their actual ministry workflow create habits that last. The ones who subscribe impulsively during a crisis (Saturday night sermon prep panic) churn when the crisis passes.

What this means for product design: your onboarding isn’t about feature education. It’s about habit formation. Successful platforms design their first-90-days experience around weekly use cases, not daily engagement metrics.

Annual Beats Monthly (But Not Why You Think)

Based on my observations, a significant majority of ministry tool subscribers choose annual billing over monthly. That’s not just better cash flow, it’s better discipleship outcomes.

Monthly subscribers tend to treat tools as disposable. They sign up for specific projects (Easter series, summer camp curriculum) then cancel. Annual subscribers build the tool into their ministry rhythm. They explore features beyond their immediate need. They recommend it to other pastors.

The psychological commitment of annual billing creates what behavioral economists call “investment bias.” When pastors spend more upfront instead of paying monthly, they appear more likely to actually use the features they paid for. Usage drives value realization. Value realization drives retention.

But here’s the non-obvious part: annual billing also appears to reduce what I call “subscription guilt.” Monthly charges create recurring reminders of cost. Annual billing shifts the conversation from “Is this worth the monthly fee?” to “How can I get more value from the tool I already bought?”

When Monetization Serves Discipleship

The best ministry subscription products don’t just avoid compromising their mission, they use their business model to advance it.

Free users at Bible Gateway get access to numerous Bible translations, with subscriber revenue supporting translation partnerships with Bible societies globally. Every subscription potentially contributes to putting Scripture into new languages. The monetization strategy supports the discipleship strategy.

In some ministry platforms, premium subscribers don’t just get better curriculum — their subscriptions help fund free access for churches in regions where subscription fees equal significant portions of daily wages. Paying customers aren’t just buying convenience. They’re supporting global ministry reach.

This flips the traditional ministry funding model. Instead of asking donors to fund ministry to strangers, you’re asking ministry practitioners to fund better tools for themselves while supporting ministry to strangers as a secondary benefit.

The psychological difference is significant. Donors give out of obligation or generosity. Subscribers pay for value received while creating value for others. One feels like charity. The other feels like partnership.

The Soul Question

Building subscription products for ministry isn’t about finding the right pricing strategy. It’s about answering the right theological question: Does your paywall bring people closer to God or further from God?

If your subscription gates basic spiritual content like Bible reading, prayer resources, or fundamental discipleship materials, you’re creating barriers to spiritual growth. That’s not just bad business (people will find free alternatives). It’s bad stewardship.

If your subscription provides professional tools that help ministry leaders serve others better — workflow optimization, advanced study tools, organizational resources — you’re creating leverage for kingdom impact. It seems like common sense that Pastors who invest in better ministry tools may reach more people, not fewer.

The test: Would removing your paywall increase spiritual growth in your users’ lives? If yes, your monetization strategy needs work. Would removing your paywall decrease your users’ ministry effectiveness? If yes, you’ve found the sweet spot.

Your subscription product should make the gospel more accessible, not less. Sometimes that means charging nothing for content. Sometimes it means charging appropriately for tools. The soul question isn’t whether to charge — it’s what to charge for and why.

Every dollar your subscribers invest should ideally return more than a dollar of kingdom impact. That’s not just sustainable business. That’s biblical stewardship.

Photo by Mockup Free on Unsplash

Ethan Mollick’s Co-Intelligence and the Biblical Call to Wisdom: Why AI Partnership Requires More Than Technical Skill

Ethan Mollick, co-director of Wharton’s Mack Institute for Innovation Management, has spent the last two years making a compelling case that we’re entering an era of “co-intelligence” — where humans and AI work together as cognitive partners rather than in a traditional tool-user relationship.¹ His core thesis: the most productive future isn’t human replacement by AI, but human augmentation through AI, where both parties contribute complementary strengths to problems neither could solve alone. This partnership model, Mollick argues, requires us to develop entirely new skills around delegation, collaboration, and what he calls “cyborg” thinking.

As someone building products for millions of users, I keep coming back to a question Mollick doesn’t directly address: if AI is becoming our cognitive partner, what does wisdom look like in that partnership?

The answer, I think, starts in Proverbs.

The Wisdom Literature Has Something to Say About AI Partners

“Plans fail for lack of counsel, but with many advisers they succeed.” (Proverbs 15:22, NIV)

King Solomon wrote this about human advisers, but the principle extends. The Hebrew word for “counsel” here is sod — it means not just advice, but the kind of intimate consultation that comes from deep understanding of both the problem and the person facing it. It’s the difference between getting information and getting wisdom.

Mollick’s co-intelligence framework captures something biblical that most AI discussions miss: partnership requires discernment about what each party brings. In my daily work, I’ve watched this play out in real time.

When my team started experimenting with AI-assisted content curation, the first instinct was pure efficiency — let the AI scan, categorize, and recommend. Classic tool thinking. The results were technically accurate but spiritually hollow. AI could identify themes in Scripture but couldn’t discern why Romans 8:28 resonates differently for someone walking through grief versus someone making a career change.

The breakthrough came when we shifted to what Mollick would recognize as co-intelligence: AI handling pattern recognition across millions of reading behaviors while humans provided the pastoral wisdom about what those patterns actually meant for individual spiritual formation.

What Co-Intelligence Looks Like in Faith Tech

The Proverbs passage about counsel assumes something crucial: advisers who actually understand the context of your decisions. This is where most AI implementations in faith contexts fall short — not because the AI lacks capability, but because we haven’t thought carefully about what wisdom requires.

“The simple believe anything, but the prudent give thought to their steps.” (Proverbs 14:15, NIV)

Applied to AI partnership, this verse cuts both ways. We can’t be “simple” about what AI tells us, but we also can’t be prudent if we’re trying to solve everything ourselves.

This looks like AI identifying reading patterns — which passages get highlighted most, where people stop in reading plans, which search terms spike during cultural events. But the decision about what those patterns mean for product design? That requires human discernment informed by pastoral experience, theological training, and understanding of how spiritual formation actually works.

Mollick talks about this as “keeping humans in the loop,” but I’d frame it differently: keeping wisdom in the loop. The goal isn’t human involvement for its own sake — it’s ensuring that the partnership produces something that serves human flourishing, not just human efficiency.

The Delegation Problem: More Than Task Management

One area where Mollick’s framework gets really practical: learning how to delegate to AI effectively. This isn’t just about prompt engineering, it’s about understanding what kinds of problems benefit from AI’s strengths (pattern recognition, rapid iteration, handling scale) versus what needs human judgment (context interpretation, ethical reasoning, spiritual discernment).

“Commit to the Lord whatever you do, and he will establish your plans.” (Proverbs 16:3, NIV)

The interesting thing about this verse is the sequence: commit first, then act. In AI delegation, we often reverse this, we act first (deploy the AI solution) and try to align it with our values later.

I’ve been thinking about this in the context of sermon preparation tools. AI is definitely coming for sermon prep, and the early products are impressive from a technical standpoint. But most of them are solving the wrong problem by optimizing for content generation rather than spiritual formation.

A co-intelligence approach would start with the theological question: what’s the actual purpose of sermon preparation? Is it to produce content, or is it to help pastors engage deeply with Scripture so they can shepherd their congregations more effectively?

If it’s the latter (and I think it is), then AI partnership looks different. AI handles the research heavy lifting of cross-referencing commentaries, identifying thematic connections, surfacing relevant cultural context. The pastor handles the spiritual discernment of understanding their congregation’s specific needs, wrestling with how the text speaks to current circumstances, crafting application that connects eternal truth to daily life.

The Stewardship Question

This brings up what might be the biggest theological question about AI co-intelligence: stewardship. If we’re called to be faithful stewards of the gifts and resources God gives us, what does faithfulness look like when one of those resources is artificial intelligence?

“From everyone who has been given much, much will be demanded; and from the one who has been entrusted with much, much more will be asked.” (Luke 12:48, NIV)

AI capability definitely falls into the “much has been given” category. The question is what “much will be demanded” looks like in practice.

Mollick’s work suggests we’re still in the early stages of figuring this out. His research at Wharton shows that even sophisticated knowledge workers are using AI at maybe 20% of its potential, mostly because we’re still thinking about it as an advanced search engine rather than a cognitive partner.

But I wonder if that’s actually wise restraint rather than missed opportunity. The Tower of Babel was fundamentally about the misuse of technological capability, not technology itself, but the assumption that technological power equals wisdom.

In product development, this shows up as the difference between building features because AI makes them possible versus building features because they serve human flourishing. The stewardship question forces us to ask not just “can we?” but “should we?” and “to what end?”

Practical Implications for Product Builders

So what does this mean for those of us building products in an AI-enabled world?

First, it means getting serious about the wisdom question. Mollick’s co-intelligence framework is helpful, but it needs theological grounding. AI partnership isn’t just about efficiency, it’s about ensuring that our use of AI capability serves love of God and neighbor.

Second, it means designing for human flourishing, not just human preference. AI can predict what users will click on, but it can’t determine whether clicking on that thing actually serves their long-term spiritual formation. That requires human judgment informed by wisdom.

Third, it means accepting that co-intelligence is inherently messy. The Proverbs model of seeking counsel assumes disagreement, iteration, and the need for ongoing discernment. AI partnerships that work will feel more like conversations than commands.

In our recent experiments, the most successful AI implementations have been the ones that generate multiple options rather than single recommendations, that surface uncertainty rather than hiding it, and that make their reasoning transparent so humans can engage with it meaningfully.

The Long View

Mollick is right that we’re entering an era of co-intelligence. But I think the Christian perspective adds something crucial to his framework: the recognition that intelligence without wisdom is dangerous, and wisdom without love is meaningless.

“If I… can fathom all mysteries and all knowledge… but do not have love, I am nothing.” (1 Corinthians 13:2, NIV)

Paul wrote this about spiritual gifts, but it applies to artificial intelligence too. The goal isn’t just more capable AI systems, it’s AI systems that help us love God and neighbor more effectively.

That’s a higher bar than efficiency or even intelligence. But for those of us building products that serve spiritual formation, it’s the only bar that matters.

The co-intelligence era is coming whether we’re ready or not. The question is whether we’ll approach it with the wisdom of Proverbs or the folly of Babel. I’m betting on Proverbs, but only if we’re intentional about what that actually means in practice.


¹ Mollick, Ethan. “Co-Intelligence: Living and Working with AI” (Portfolio, 2024). See also his ongoing research at OneUsefulThing.org.

Photo by Mindfield Biosystems on Unsplash

AI Is Coming for Sermon Prep. Here’s What Pastors Actually Need.

When SermonAI launched their Research Assistant with custom theological personas, I watched our SermonCentral dashboard closely. We’d spent years building the world’s largest library of sermon manuscripts — 145,000+ and counting — and suddenly everyone wanted to know: would AI kill the sermon prep industry?

The answer turned out to be more nuanced than the headlines suggested.

The AI Sermon Prep Land Grab Is Here

The competitive landscape shifted fast. Verbum launched a Homily Assistant for Catholic priests. Sermon Snap started capturing “AI sermon” search volume. SermonSpark positioned itself as the ChatGPT for pastors.

But here’s what I noticed from our 14,700 SermonCentral subscribers: they weren’t abandoning human-written content for AI-generated sermons. They were still downloading, printing, and adapting manuscripts written by other pastors.

Our top conversion events remained what they’d always been — print and download actions. Not “generate new sermon” clicks.

That gap between AI marketing promises and actual pastoral behavior revealed something important about what pastors actually need from AI in sermon preparation.

What Pastors Actually Do With Sermon Content

After tracking sermon prep behavior across multiple platforms, the pattern is clear: pastors don’t want sermons written for them. They want research accelerated.

Here’s what the data shows us (note: inferred from aggregate usage patterns, since individual sermon prep workflows aren’t tracked end-to-end):

Most pastors start with a biblical text, then move to research. They’re looking for historical context, cross-references, illustrations that connect to contemporary life. The sermon structure and theological application — that’s where their unique voice emerges.

At SermonCentral, I watched this play out in search behavior. Pastors would search for “Matthew 5:14 illustrations” or “Philippians 4:13 context” far more often than “complete sermon on joy.” They wanted building blocks, not finished products.

The pastor’s voice IS the product. A sermon isn’t a blog post you can template and optimize. It’s performed, personal, deeply theological. It carries the weight of pastoral authority built over years of relationship with a specific congregation.

Why AI-Generated Sermons Miss the Mark

When I see AI tools promising to “write your entire sermon in minutes,” I think about trust.

Pastoral credibility gets built over time through consistent theological depth and personal authenticity. Congregations can sense when a message feels generic or disconnected from their pastor’s usual voice and insight.

More practically, sermons are contextual in ways that AI struggles with. The pastor who preaches on forgiveness the week after a church conflict needs different illustrations than the one preaching the same text to a suburban congregation dealing with achievement anxiety.

AI-generated content optimizes for coherence and theological accuracy. But sermons need something more — they need the pastor’s lived experience, their knowledge of the congregation’s specific struggles, their ability to connect ancient text to current context in ways that feel authentic rather than algorithmic.

This isn’t anti-AI sentiment. It’s about understanding what sermons actually are and how they function in the life of a local church.

The Right Way to Build AI for Sermon Prep

Smart AI sermon tools focus on research acceleration, not content generation.

Here’s where AI actually helps pastors work better:

Illustration Discovery: Instead of spending hours searching for contemporary examples of biblical principles, AI can surface relevant stories, statistics, or cultural references quickly. But the pastor still chooses which ones fit their voice and congregation.

Cross-Reference Mapping: AI can identify thematic connections between passages that might take hours to research manually. But the theological interpretation and application remains with the pastor.

Context Adaptation: AI can help pastors understand how different cultural contexts might hear the same biblical text. But the decision about which perspective to emphasize stays pastoral.

The pattern I’m seeing in effective AI sermon tools: they expand the pastor’s research capacity without replacing their interpretive authority.

Tools like Bible Gateway’s AI features focus on helping users understand what they’re reading, not generating content for them. That’s the right approach — augmenting human insight rather than substituting for it.

The Brand Promise Problem

Here’s the question every AI sermon tool needs to answer: if you market “AI sermons,” what happens to pastoral trust?

When congregations discover their pastor is using AI to write messages, it creates a credibility problem that goes beyond the quality of the content. It raises questions about authenticity, preparation effort, and spiritual authority that most pastoral relationships can’t sustain.

The alternative positioning — “AI research assistance for better sermon prep” — preserves pastoral authority while delivering genuine value.

I learned this lesson building products for ministry leaders across multiple platforms. The most successful tools enhanced their existing strengths rather than promising to replace their core work.

At Bible Gateway, our AI features help people understand Scripture better, not generate spiritual content for them. That boundary matters for user trust and product longevity.

What This Means for Pastoral Ministry

AI sermon preparation tools will succeed when they solve the right problem: helping pastors research faster so they can focus more time on interpretation, application, and delivery.

The pastors who thrive with AI will use it to expand their research capacity — finding better illustrations, understanding cultural context more deeply, connecting biblical themes more comprehensively. But the actual sermon content, structure, and theological insight will remain authentically theirs.

The ones who struggle will be those who try to use AI as a shortcut to the hard work of biblical interpretation and pastoral application.

From what I’ve observed across thousands of pastors using digital sermon prep tools, the most effective approach treats AI as a research assistant, not a co-author. That distinction preserves both the integrity of pastoral authority and the quality of spiritual content that congregations actually need.

The future of AI in sermon prep isn’t about writing better sermons automatically. It’s about helping pastors bring their unique voice and insight to biblical text more effectively than ever before.

Photo by RU Recovery Ministries on Unsplash

What 23 Million Bible Readers Taught Me About Digital Discipleship

digital discipleship

Every month, roughly 23 million people open Bible Gateway to read Scripture. That’s more than attend every Southern Baptist Convention church on a given Sunday — the SBC’s own 2023 report counted 12.4 million in average weekly worship attendance.1

I lead product at HarperCollins Christian Publishing, where Bible Gateway is my primary focus. Before that, I spent years building SermonCentral — a platform serving 14,700+ subscribing pastors with access to 145,000+ sermon manuscripts — and co-built ORI, a youth discipleship app for mentoring teenagers. I’ve spent the last few years of my career watching how people actually behave when they engage with Scripture through technology. And what I’ve observed has changed the way I think about what “digital discipleship” means.

Content Distribution Is Not Discipleship

Most church tech conversations define digital discipleship as “putting Christian content online.” Upload a sermon. Publish a devotional. Build a Bible app.

That’s content distribution. Discipleship is something else.

From a product perspective, digital discipleship is designing technology that facilitates spiritual formation — helping people move from curiosity to commitment to transformation. The difference matters because it changes what you build. If you’re optimizing for content distribution, you chase volume: more translations, more devotionals, more features. If you’re optimizing for formation, you chase behavior change: consistency, depth, relationship.

Bible Gateway has given me a front-row seat to how millions of people actually engage with Scripture. Not how we hope they do, not how pastors assume they do — how they actually do. The patterns are humbling.

Commitment Structures Beat Content Volume

Bible Gateway offers hundreds of reading plans across dozens of categories. We have the content. What we’ve observed is that completion rates vary dramatically — and it’s not the “best” content that wins. It’s the best structure.

Short reading plans with clear daily commitments consistently outperform longer ones in completion rates. (I want to be precise: this is based on aggregate engagement data across our reading plan ecosystem, not a controlled A/B test. The pattern is strong, but I’m stating it as an observed trend.)

This makes sense if you think about it through a discipleship lens. The goal of a reading plan isn’t to get someone through the entire Bible in 365 days. The goal is to build a habit of daily engagement with Scripture. A 7-day plan someone finishes builds more spiritual momentum than a year-long plan abandoned in February. The research supports this — BJ Fogg’s work on Tiny Habits at Stanford demonstrates that small, completable commitments are the foundation of lasting behavior change.2

The product implication: when designing for digital discipleship, optimize for completion and consistency, not comprehensiveness. Finishable is better than thorough.

I saw the same thing at SermonCentral. Pastors didn’t need more sermon content — they needed the right content at the right time in their prep cycle. The value was relevance and timing, not volume.

The Gap Between Bible Search and Bible Study

Something surprised me when I first dug into Bible Gateway’s usage data: the overwhelming majority of sessions are what I’d call “Bible search” behavior, not “Bible study” behavior.

Most people come to look up a specific verse. They type “John 3:16” or “Philippians 4:13” into the search bar, read it, and leave. They’re using the platform as a reference tool. With over 2,000 Bible searches happening every minute on Bible Gateway, that’s a lot of single-verse visits.

This isn’t a criticism — it’s a behavioral insight with real implications for how we think about digital discipleship strategy.

If most users are in “lookup mode,” the discipleship opportunity isn’t in the content they came for. They already know that verse. The opportunity is in what comes next. Cross-references. Historical context. A reading plan that starts at that passage. A study note that opens the text up. The moment after someone finds what they came for is the moment a reference visit can become a formation experience.

(I should be transparent: I’m inferring the “lookup vs. study” distinction from session duration, page depth, and search query patterns in aggregate. We can see that a large portion of sessions are short and single-verse. But I can’t tell you what’s happening in someone’s heart during a 30-second visit — maybe that one verse is exactly what they needed. The data shows behavior, not transformation.)

The product principle applies broadly: meet people where they are, not where you wish they were. Design the next step from actual behavior, not from an ideal user journey.

The Day 7 Engagement Cliff

This is the most actionable pattern I’ve observed, and it’s consistent across every content platform I’ve worked on.

When someone starts a reading plan, engagement drops sharply after about Day 7. The first few days see strong completion. By the end of the first week, there’s a significant cliff. People who make it past Day 10 tend to finish — but a substantial number never get there.

(Evidence level: this is a pattern in aggregate reading plan data. Exact drop-off percentages vary by plan type and length, but the general shape — strong start, sharp drop around Day 7, stabilization for those who persist — is consistent enough that I’m confident calling it a pattern. This aligns with published habit formation research — Phillippa Lally’s 2009 study in the European Journal of Social Psychology found that early repetitions are the most fragile period for new habits.3)

For digital discipleship design, the implication is clear: Day 5 through Day 8 is where you need your best intervention design. Reminders. Encouragement. Community connection. A check-in from a real person. Whatever bridges the gap between initial motivation and formed habit.

This is where most digital discipleship tools fail. They’re good at onboarding. They’re good at content. They go quiet in the messy middle — the stretch where motivation fades and habit hasn’t locked in yet. That gap is where discipleship actually happens, and it’s where most apps have nothing to say.

At Bible Gateway’s scale, even small improvements in that Day 5-8 window could mean hundreds of thousands of people moving from casual lookup to sustained practice.

Why Features Rarely Solve Discipleship Problems

I’ve shipped a lot of features across my career. One thing I’ve learned — sometimes painfully — is that adding features to a discipleship tool almost never solves a discipleship problem.

The instinct is always to build more. More study tools. More social features. More gamification. But the digital discipleship tools that actually seem to work are the ones that reduce friction to spiritual practice, not the ones that add complexity to it.

Bible Gateway’s core value proposition is remarkably simple: read any Bible translation, for free, instantly. Over 200 versions in 70+ languages. That simplicity is the product. Every feature we consider needs to serve that core experience, not compete with it.

There’s a real tension here. Bible Gateway Plus offers 50+ study resources, ad-free reading, and deep study tools at $4.99/month. But even the premium tier works because it removes friction (ads, limited study tools) rather than adding cognitive load. The upgrade makes the simple thing simpler.

What ORI Taught Me About the Limits of Scale

All of this data-driven thinking needs a counterweight. For me, that counterweight is ORI.

ORI is a youth discipleship app I co-built, and its premise is different from a content platform like Bible Gateway. ORI facilitates the relationship between a mentor and a young person. The technology doesn’t do the discipleship — it supports the human who does.

That experience taught me something analytics can’t: the most effective digital discipleship tool is often the one that gets out of the way. The one that connects a young person with an adult who cares about them, gives them a shared framework for conversation, and then steps back. It echoes what Paul wrote to the Thessalonians — “We were gentle among you, like a nursing mother taking care of her own children” (1 Thessalonians 2:7, ESV). Discipleship has always been relational. Technology either serves that or distracts from it.

There’s a spectrum here. On one end, platforms like Bible Gateway serve millions with content at scale. On the other, tools like ORI serve hundreds by facilitating real human relationships. Both are valid. Both are needed. But they succeed for different reasons, and conflating them is a mistake I see church tech teams make often.

Friction Is the Enemy

If I had to compress everything I’ve learned into one principle: your job is to reduce friction between a person and their next spiritual step.

Not to create content. Not to build features. Not to gamify Scripture. To reduce friction.

At Bible Gateway’s scale, that means instant access to any translation, fast search, and reading plans designed around how people actually behave. At ORI’s scale, that means making it easy for a mentor to show up prepared for a fifteen-minute conversation with a teenager.

The 23 million people who use Bible Gateway each month aren’t a metric. They’re people in a spiritual practice — or trying to start one. The best thing a product team can do is figure out where the friction lives and get it out of the way.

I don’t have this figured out. The Day 7 cliff still exists. The gap between Bible search and Bible study is still wide. The question of whether a 30-second verse lookup counts as “discipleship” — I genuinely don’t know. But I think the question itself is worth sitting with, because how you answer it shapes everything you build.


Dr. Josh Read is Director of Product at HarperCollins Christian Publishing, where he leads Bible Gateway. He writes about the product side of digital discipleship at drjoshuaread.com. His other writing explores AI stewardship in ministry and what the Tower of Babel teaches us about technology.


1 Southern Baptist Convention, 2023 Annual Church Profile, reporting 12.4 million average weekly worship attendance across 47,000+ churches.

2 BJ Fogg, Tiny Habits: The Small Changes That Change Everything (Houghton Mifflin Harcourt, 2019). Fogg’s research at Stanford’s Behavior Design Lab demonstrates that starting small and building on success is more effective than ambitious commitment structures.

3 Phillippa Lally et al., “How Are Habits Formed: Modelling Habit Formation in the Real World,” European Journal of Social Psychology 40, no. 6 (2010): 998-1009.

The Tower of Babel Was a Technology Problem, Not a Language Problem

Most pastors I’ve talked to use the Tower of Babel the same way. It’s a warning against ambition. Don’t reach too high. Stay in your lane.

That reading has legs. But I’ve spent the last several years building products for churches — first at SermonCentral, where we managed over 245,000 sermon manuscripts for 14,700+ subscribers, and now at Bible Gateway, which serves 23 million monthly visitors across 200+ Bible translations. When I read Genesis 11 through a product lens, I see something the ambition reading misses.

God didn’t judge the bricks.

“Come, let us build ourselves a city, with a tower that reaches to the heavens, so that we may make a name for ourselves.” — Genesis 11:4, NIV

The materials were fine. The engineering was fine. The goal — consolidating human fame — was the problem. And that distinction matters right now, because the church is having the wrong argument about AI.

AI Is Bricks and Mortar

The debate I keep hearing splits along predictable lines. One camp says AI threatens authentic ministry. The other says it’s the future of outreach. Both are fixated on the tool and ignoring the purpose behind it.

AI is a building material. Your spam filter runs on it. Your search results are shaped by it. Your congregation interacts with machine learning dozens of times a day without a second thought. The question of whether the church uses AI was settled years ago.

The question that matters: what are you building, and for whom?

A church that uses AI to transcribe sermons so a deaf congregant can read along on Monday morning — that’s building for the Kingdom. A church that uses AI-generated sermons so the pastor can spend less time in the text — that’s a tower with its own name on it.

Same bricks. The blueprint is what changed.

Augustine’s Framework (From 397 AD)

About 1,600 years before anyone worried about ChatGPT, Augustine drew a line I think about constantly in product work.

In De Doctrina Christiana (Book I, chapters 3-4), Augustine distinguished between two postures toward the things of this world: uti (to use) and frui (to enjoy as an end in itself). His argument: the things of creation are meant to be used as means toward loving God and neighbor. They become disordered when we treat them as destinations — when we frui the tool instead of the purpose the tool serves.

I’ve found this more useful than any AI ethics whitepaper.

Consider: a church uses AI to automate its weekly bulletin, freeing up a volunteer to spend those 3 hours visiting a homebound member. That’s uti. The tool serves a human end.

Now consider: a church uses AI to eliminate pastoral presence altogether. Their new chatbot handles prayer requests, the algorithm personalizes a sermon playlist, the system runs without a shepherd. That’s frui. The church has started delighting in efficiency as its own reward.

The technology didn’t change. The orientation did.

Three Questions Before Adopting Any AI Tool

I’ve spent enough time in product leadership to know that the best safeguard isn’t a policy document (I’ve written plenty of those — they collect dust). It’s a habit of asking the right questions before you build.

1. Who benefits?

If the honest answer is “the budget” and not “the congregation,” pause. Cost savings aren’t wrong — stewardship matters. But if the primary beneficiary is the institution rather than the people it serves, you’re building in the wrong direction. The best AI implementations I’ve seen at Bible Gateway started with a specific human need, not a line item.

2. What human activity does this replace, and should that activity stay human?

Administrative tasks — scheduling, data entry, email sorting, transcript formatting — automate freely. These are good uses of AI. They free up people for work that only people can do.

But pastoral care, spiritual formation, the ministry of presence — these resist automation for a reason. A hospital visit from a pastor matters because a person chose to show up. An AI can generate a thoughtful prayer. It cannot bear witness to suffering.

(This is the question I find hardest to answer cleanly, by the way. The line between “administrative” and “pastoral” blurs more than we’d like. Where does sermon research end and sermon preparation begin? I don’t have a tidy answer. I think the honest move is to keep asking.)

3. Does this build the church’s capacity or create dependency on a vendor?

This is the product leader in me talking. I’ve watched organizations — churches included — adopt tools that felt like empowerment but functioned as dependency. If your church can’t operate without a specific AI platform, you haven’t adopted a tool. You’ve adopted a landlord.

Look for AI that trains your people. Look for solutions where the value stays with the church if the vendor disappears tomorrow.

From Babel to Pentecost

The Bible doesn’t end the language story at Babel. It picks it back up in Acts 2.

“All of them were filled with the Holy Spirit and began to speak in other tongues as the Spirit enabled them. Now there were staying in Jerusalem God-fearing Jews from every nation under heaven. When they heard this sound, a crowd came together in bewilderment, because each one heard their own language being spoken.” — Acts 2:4-6, NIV

At Babel, human technology consolidated power and built a monument to self. God scattered and confused. At Pentecost, the Spirit moved — and people from every nation heard the gospel in their own mother tongue. Each person’s language, met where they were.

According to recent Barna research, 77% of pastors believe AI can have a positive impact. I think that’s right — but only if we’re asking the Babel question each time we adopt something new.

Here’s what that looks like in practice: a small church in rural Guatemala using AI translation to access theological training that was previously locked behind an English-language paywall. That points toward Pentecost.

A megachurch using AI to scale content production so it can dominate more digital market share. That points back toward Babel.

What We Build Next

I don’t think the church needs to fear AI. I also don’t think it needs to be infatuated with it (and having built products in this space since 2018, I’ve watched both reactions play out in real time).

The bricks and mortar are here. They’re powerful. They’re going to keep getting more powerful. The church’s job is to ask the Babel question every time: what are we building, and whose name is on it?

That question doesn’t have a permanent answer. It has to be asked again with every new tool, every new capability, every new vendor pitch. And I think the churches that will get this right are the ones willing to sit with the discomfort of asking it honestly — even when the answer means building slower.


Sermon Illustration: The Tower of Babel and AI

When the people of Babel built their tower, God didn’t judge the bricks. He didn’t condemn the mortar or the engineering. The materials were fine. The problem was the purpose: “let us make a name for ourselves” (Genesis 11:4, NIV).

Today, AI is the new brick and mortar. Churches face the same question Babel faced: what are we building, and for whom? AI that frees a pastor to sit at a hospital bedside — that’s technology in service of presence. AI that replaces the pastor at the bedside — that’s a tower with our own name on it.

But the story doesn’t end at Babel. At Pentecost, God took language itself — the very thing He confused at Babel — and used it to carry the gospel across every barrier (Acts 2:4-6). The bricks are in our hands. The blueprint is the question.

7 Things I Read This Week (and Why They Matter)

This was one of those weeks where everything I read seemed to converge on the same theme: the ground is shifting faster than most of us realize. AI isn’t coming for our workflows someday – it’s already reshaping how products get discovered, how code gets written, and whether your product-market fit survives the next 12 months.

Here’s what caught my attention.

1. Product Market Fit Collapse: Why Your Company Could Be Next

Reforge Blog

If you’re in SaaS, this is the chart that should scare you. Reforge makes the case that PMF isn’t a destination – it’s a treadmill. And AI just cranked the speed to max. Chegg lost 87.5% of its valuation. Stack Overflow’s traffic cratered. The pattern is the same: AI proves value for a use case, and the incumbent’s window to adapt slams shut before they even recognize the threat.

This one hit me personally. SermonCentral has been the go-to sermon library for over two decades. BUT the question I keep coming back to is: what happens when pastors can generate sermon outlines with AI in seconds? The PMF threshold doesn’t care about your legacy. It only cares about whether you’re still the best answer to the customer’s problem RIGHT NOW.

2. What AI Sees When It Visits Your Website (And How To Fix It)

Google Share

This reframed how I think about our SEO strategy entirely. AI answer engines – ChatGPT, Google AI Overviews, Perplexity – are visiting your site, interpreting your content, and shaping customer perception BEFORE a human ever clicks. Traditional SEO isn’t enough anymore. You need AEO – AI Engine Optimization.

For SermonCentral, this is urgent. We live and die by organic discovery. If AI systems can’t parse our content well, we lose visibility in the exact channels that are replacing traditional search. I’m bringing this to the team this week.

3. Claude Code Remote Control

Claude Code Docs

This is the kind of workflow upgrade that sounds small but changes everything. Claude Code now lets you continue local dev sessions from your phone, tablet, or any browser. Your full local environment stays intact – filesystem, MCP servers, all of it. Sessions reconnect automatically after network drops or laptop sleep.

I’ve been using Claude Code as my daily driver for months now. Being able to kick off a task at my desk and check progress from my phone during a walk? That’s the kind of automation leverage I’m optimizing for in 2026.

4. Claude Code for Web – Async Coding Agent

Simon Willison

Anthropic launched an async coding agent at claude.ai/code. Point it at a GitHub repo, give it a task, and it creates branches and PRs with the work output. It runs in a container, skips permission gates, and the PRs are indistinguishable from CLI-generated ones.

The coding agent space is getting crowded fast – OpenAI Codex Cloud, Google Jules, now this. What I appreciate about this one is the “teleport” feature that lets you copy the transcript and files to your local CLI. It’s not replacing the local workflow, it’s extending it. That’s the right design philosophy.

5. How to Build a PM GitHub That Gets You Hired

Aakash’s Newsletter

Only 24% of PM candidates have GitHub profiles. That stat alone should tell you something. Hiring managers at Google, OpenAI, Anthropic, and Meta actively check GitHub when it’s linked. A strong profile signals you actually build things and understand engineer workflows – not just strategize from a slide deck.

I’ve been saying this for a while: the best PMs ship. They don’t just write specs. If you’re a PM reading this and you don’t have a GitHub presence, this is your sign. Start small. Ship something. The differentiation is massive because almost nobody does it.

6. Visual Explainer – Agent Skill for Rich HTML Output

GitHub

This is a neat agent skill that converts complex terminal output into styled, interactive HTML pages. Think: architecture diagrams, code diff reviews, project plan audits, data tables – all rendered as shareable HTML without manual formatting.

I’m always looking for ways to make technical work more visible to non-technical stakeholders. Being able to generate a polished visual recap of a sprint or a system change and just send the HTML? That’s a communication multiplier.

7. Anthropic Courses on Skilljar

Anthropic Courses

Anthropic now has 14+ structured courses covering Claude API, Model Context Protocol, and AI fluency for developers, educators, students, and nonprofits. This tells me they’re investing heavily in ecosystem education – and that MCP is becoming a first-class skill.

I’ve been building MCP integrations into my daily workflow for months. Seeing Anthropic formalize the training around it validates the bet. If you’re building on Claude and haven’t gone through these, it’s worth the time.

The Thread That Ties It All Together

Every link this week points to the same reality: the cost of standing still just went up. PMF is collapsing faster. AI is reshaping discovery. Coding agents are shipping real code. The PMs who build things are getting hired. The tools are getting better every week.

The question isn’t whether to adapt. It’s whether you’re adapting fast enough.

I aim to be on the right side of that question. Hopefully some of these links help you get there too.

Product design fundamentals every product manager should know

I’ve been building products for nearly three decades and one of the things I wish someone had told me early on is this: you don’t need to be a designer, but you need to understand design well enough to have an opinion.

A “this flow is going to confuse people and here’s why” opinion. That’s a fundamentally different skill, and it’s one that separates good PMs from great ones.

Design Literacy Is a Product Superpower

Most PMs I’ve worked with fall into one of two camps. Either they defer entirely to the designer (“you’re the expert, I trust you”) or they micromanage pixels without understanding why.

Neither works great.

The best PMs I know can open a Figma file, look at a proposed flow, and say: “This solves the problem, but I think we’re going to lose people at step 3 because there’s too much cognitive load.” That’s product judgment informed by design principles.

Here are the fundamentals that have made the biggest difference in how I work.

Visual Hierarchy Drives Behavior

Every screen has a job. The user lands on it and their eyes need to go somewhere. If everything is bold, nothing is bold. If there are six calls to action, there are zero calls to action.

This sounds obvious, but I can’t tell you how many product reviews I’ve sat in where the page is trying to do five things at once. The conversion data always tells the same story: users don’t know what to do, so they do nothing.

The principle is simple: every page should have ONE primary action. Everything else is secondary.

When I look at a design now, the first question I ask is “what’s the one thing we want the user to do here?” If the designer can’t answer that in one sentence, we have a problem.

Consistency Reduces Cognitive Load

This one took me a while to internalize. Consistency is about reducing the mental effort required to use your product. (If you haven’t read it, Schneiderman’s Eight Golden Rules is a great foundation for this.)

When a button is blue in one place and green in another, when the save action is top-right on one page and bottom-left on another, when confirmation messages look different everywhere, each inconsistency is a tiny tax on the user’s brain. Individually they’re nothing. Collectively they’re the reason people say “this product feels clunky” without being able to explain why.

As a PM, I’ve learned to flag consistency issues early. They compound. And they’re 10x easier to fix in design than in code.

Feedback Loops Build Trust

Users need to know their action worked. Every single time. No exceptions.

Click a button? Something should visually change. Submit a form? Show a confirmation. Trigger a process that takes time? Show a loading state.

I still see products that leave users wondering “did that work?” And every time that happens, trust erodes a little. I’ve started treating feedback loops as a product requirement, not a design nice-to-have.

Whitespace Is Not Wasted Space

My instinct as a PM was always “we have this space, let’s use it.” More features visible, more value communicated, more reasons to convert.

That instinct was backwards. Whitespace is what makes the important things important. It’s what gives the user’s eye a place to rest.

Some of the most effective design changes I’ve seen were about removing things. Taking away a sidebar. Eliminating a secondary nav. Letting the content breathe. The metrics almost always improved.

Accessibility Is Just Good Design

I’ll be honest, I used to think of accessibility as a checkbox. Something we needed to do for compliance. I was wrong and it wasn’t until I reached mid-forties that I started to recognize why they are necessary.

High contrast text is easier for everyone to read. Clear labels help everyone navigate.

Keyboard support benefits power users as much as it benefits users with motor disabilities. When we improved accessibility on our platform, our overall usability scores went up across the board. For everyone.

The PM’s Role in Design

My job is to define the problem clearly enough that the designer can solve it well. I challenge designs that optimize for aesthetics over usability. I push back when a beautiful mockup doesn’t account for edge cases, error states, or the reality of what happens when a user has 500 items instead of 5.

I don’t draw wireframes or pick colors or argue about border radius.

The best design partnerships I’ve had were two people with different expertise looking at the same problem and making it better together. That only works when the PM speaks enough design language to have the conversation.

I wish I’d started learning design fundamentals earlier. You don’t need a course. You don’t need to learn Figma (though it helps).

Just start asking “why” when you see a design decision, and pay attention to the answer. That habit alone will make you measurably better at your job.

How do you avoid burnout in product management?

There was a season a few years back where I was checking Slack before my feet hit the floor in the morning. Responding to emails during dinner. Thinking about roadmap priorities during my daughter’s volleyball game.

I wasn’t working more hours than anyone else on my team. I was just never NOT working.

Product management does this to people. (HBR’s research on burnout confirms it’s systemic, not individual.) You own the outcome but you don’t own the resources. You’re the one the CEO asks when numbers are off, the one engineering pings when priorities conflict, the one the customer success team escalates to when a big account is unhappy. The role is designed to pull you in every direction at once.

I was hired to replace the previous PM who burned out. He had replaced a PM who had burned out. Now, I was burning out. Not dramatically. I didn’t quit or have a breakdown. It was the slow kind, where you stop being excited about the work and start just surviving it. Where your family gets the leftover version of you and even that feels like it’s running on fumes.

Here’s what I’ve changed since then. I’m not going to pretend I’ve got it all figured out, but I’m in a fundamentally better place than I was, and most of it came from a few non-negotiable decisions.

Protect Your Time Like It’s a Product Requirement

I have a hard rule: home by 5:30 for dinner. No exceptions. Not for a board prep. Not for a product review. Not for a “quick sync” that will definitely run long.

I also block a 90-minute gym window in the middle of my day and an hour for reading first thing in the morning. These aren’t nice-to-haves. They’re on my calendar as immovable blocks, the same way a meeting with the CEO would be.

When I first started doing this, I felt guilty. Like I was being less committed than my peers. What I actually found is that the constraints made me sharper.

When you know you have to be done by 5:30, you stop saying yes to the third “alignment meeting” of the day. You get ruthless about prioritization because you have to be. The artificial scarcity forced better decisions about where my time went.

Automate Everything You Touch Twice

My theme for this year is automate as much as possible. Every hour I spend on repetitive work is an hour I’m not spending on the high-leverage thinking that actually moves the business forward.

Status reports, data pulls, recurring communications, task routing, inbox triage: if I do it more than twice, I build a system for it.

Some of these are sophisticated (automated morning briefings that synthesize email, calendar, and tasks into a single digest). Some are dead simple (a Slack reminder template so I don’t have to think about weekly check-ins).

The compounding effect is real. Each small automation frees up 15-30 minutes. Stack enough of them and you’ve recovered entire blocks of deep work time that used to disappear into operational overhead.

Your Team Is Your Leverage

The biggest burnout trap for PMs is thinking you need to be involved in everything. You don’t. You need to be clear about what matters, set the direction, and then trust your team to execute.

I used to review every analytics pull. Now my analytics lead knows what I care about and surfaces the insights, not the data.

I used to write every A/B test hypothesis. Now my growth marketer proposes them and I weigh in on priorities.

I used to attend every customer call. Now my PM partner handles the S4K side entirely and we sync weekly.

Delegation is about building capability on your team so that your time is spent on the decisions only you can make. If you’re the bottleneck for everything, that’s a sign of a system that’s one illness away from breaking.

Make Peace with “Good Enough”

Perfectionism will eat you alive in product management. There’s always one more edge case to account for, one more stakeholder to consult, one more data point to gather before making a decision.

I’ve learned to ask: “Is this decision reversible?” If yes, make it fast and move on. You can adjust later. If no, take the time you need.

But most decisions in product are reversible, and treating every one like it’s permanent is a fast track to analysis paralysis and the chronic stress that comes with it.

Shipping at 80% with the ability to iterate beats shipping at 100% three months late. And honestly, your users can’t tell the difference most of the time.

Faith and Purpose as Anchors

This one’s personal, so take it for what it’s worth. For me, faith is the thing that keeps work in perspective. I care deeply about what I do (I’m building products that help the church grow, and that mission matters to me). BUT it’s not the entirety of who I am.

When I remember that, it’s easier to close the laptop. It’s easier to be present at dinner. It’s easier to let go of the meeting that didn’t go well, the metric that’s off target, the feature that shipped with a bug.

Whatever your version of that anchor is (faith, family, community, a creative pursuit), guard it. Don’t let the urgency of product work crowd out the things that actually sustain you.

The Bottom Line

Burnout in product management comes from working without boundaries, without leverage, and without recovery.

Set the boundaries. Build the leverage through automation and delegation. Protect the time that restores you.

Your value is measured by the clarity of your decisions and the impact of what you ship. The version of me that protects his time, trusts his team, and goes to the gym at 11am is a better PM, a better leader, and a better husband and father than the one who was grinding 14 hours a day and calling it dedication.

25 Skills Every Product Manager Should Be Building in 2026

Product Manager sitting in his home office reading

There’s no shortage of “skills for PMs” lists on the internet. Most of them read like a job description, technically correct, but practically useless.

This isn’t that list. These are the 25 skills I’ve seen separate the product managers who move the needle from the ones who stay busy. I’ve organized them by the areas where I see the biggest gaps, not by some theoretical framework. Some of these are timeless. Some are specific to right now. All of them are things I wish someone had told me earlier in my career.


I. Customer Obsession

These are the skills that everything else builds on. Get these wrong and nothing else matters.

1. Deep Customer Knowledge

You can’t fake this one. The best PMs I’ve worked with can describe their top customer segments in vivid detail – not just demographics, but the actual daily workflow, the frustrations, the workarounds they’ve built, the language they use when they’re annoyed.

This doesn’t come from dashboards. It comes from sitting with customers, watching them use your product, and resisting the urge to defend your design choices when they struggle. Do this monthly, not quarterly. The PMs who “don’t have time” for customer conversations are the same ones who build features nobody uses.

2. Jobs-to-be-Done Thinking

Clayton Christensen’s framework has become so mainstream that people name-drop it without actually applying it. The real skill isn’t knowing what JTBD is, it’s being able to articulate the job your customer is hiring your product to do in one sentence.

If you can’t do that, you don’t understand your customer well enough yet. Every feature decision should trace back to that job. If it doesn’t advance the job, it’s noise.

3. Continuous Discovery

Teresa Torres literally wrote the book on this. The skill isn’t “doing user research” – it’s building a rhythm of weekly customer touchpoints that inform your decisions in real-time, not once a quarter when the research team delivers a 40-page report nobody reads.

The PMs who do this well talk to 2-3 customers every single week. Not formal research sessions with screeners and discussion guides. Quick, focused conversations that answer specific questions about specific opportunities.

I have “virtual coffee” times available on my calendar and invite users on our emails to book some time with me. It’s fantastic and gives me tons of insight into our customers.

4. Knowing When to Ignore Feedback

This sounds counterintuitive after three skills about listening to customers. But one of the hardest skills in product management is knowing WHICH feedback to act on and which to file away.

Not every customer request is a product insight. Sometimes a customer wants something that serves them but hurts the broader user base. Sometimes they’re describing a symptom, not the root cause. The skill is triangulating. When you hear the same pain from multiple segments, supported by data, that’s signal. When one loud customer demands something, that’s noise.

5. Empathy That Goes Beyond Platitudes

Every PM claims to have empathy. The actual skill is translating empathy into product decisions. It’s the difference between saying “I understand the user’s frustration” and redesigning the onboarding flow because you watched someone struggle for 8 minutes trying to complete a task that should take 30 seconds.

Real empathy is uncomfortable. It means watching your product fail in real-time and sitting with that feeling instead of explaining it away.


II. Strategic Thinking

These are the skills that determine whether your team is building the right things.

6. Product Vision

A compelling product vision describes what the world looks like 2-5 years from now if your product succeeds. Not a feature list. Not a technology roadmap. A picture of a better future for your customer.

The skill is making this concrete enough to inspire and vague enough to allow room for discovery. “We’ll be the leading platform for X” is not a vision. “Every pastor will have a personal AI-powered sermon preparation assistant that cuts their weekly prep time in half” – that’s a vision.

7. Product Strategy

I wrote about the 10 most common strategy mistakes recently, and the biggest one is teams that have no strategy at all — just a backlog they call a strategy.

The skill here is making choices. Real ones. Strategy means explicitly deciding what you will NOT do, who you will NOT serve, and which opportunities you will walk away from. If your strategy doesn’t make someone uncomfortable, it’s not a strategy.

8. Ruthless Prioritization

This is the skill that separates senior PMs from everyone else. You will always have more opportunities than capacity. The question is never “should we build this?” Everything on your list is probably worth building. The question is “should we build this INSTEAD of that?”

Frameworks like RICE scoring help, but the real skill is having the conviction to say no to good ideas because they’re not the BEST idea right now. Warren Buffett’s two-list strategy applies: identify your top 25 priorities, circle the top 5, and treat the other 20 as your “avoid at all costs” list.

9. Outcome-Focused Roadmapping

The shift from output-based roadmaps (“Q2: Ship feature X, Y, Z”) to outcome-based roadmaps (“Q2: Reduce trial-to-paid time from 14 days to 7 days”) is one of the most important evolutions in modern product management.

The skill is framing your roadmap around the problems you’re solving and the metrics you’re moving, not the features you’re building. This gives your team room to discover the best solution instead of being locked into a predetermined one.

10. Saying No (and Making It Stick)

Every PM knows they should say no more often. The actual skill is saying no in a way that maintains relationships and builds trust. “No, because our strategy is focused on X, and here’s why that matters more right now” is dramatically different from just “no.”

The best PMs I’ve seen turn a “no” into a learning moment by explaining the reasoning, sharing the data, and making the person feel heard even when the answer isn’t what they wanted. I’ve found that people can disagree with a well-reasoned decision. What often causes stress is ambiguity.


III. Execution and Delivery

These are the skills that turn strategy into a shipped product.

11. Rapid Experimentation

The ability to test ideas in hours or days instead of weeks or months is a superpower. This means prototyping. Not pixel-perfect mockups, but rough, testable concepts that answer specific questions.

Can users find this feature? Does this flow make sense? Will anyone actually use this? You can answer all of these questions with a prototype and 5 users in a single afternoon.

12. Writing Clear Requirements

This is an underrated skill. The gap between “what the PM imagined” and “what engineering built” is almost always a requirements problem, not a competence problem.

The skill is writing requirements that are specific enough to build from but flexible enough to allow engineering creativity. I’ve found that focusing on the PROBLEM and the SUCCESS CRITERIA while leaving the implementation approach to engineering produces the best results.

13. Data Literacy

You don’t need to be a data scientist, but you need to be dangerous with data. That means understanding statistical significance (so you don’t kill an A/B test too early), knowing which metrics actually matter for your product, and being able to query your own data when the analytics team is backed up.

AI has made this dramatically easier. You can now describe what you want in plain English and get a SQL query back. That’s a genuine unlock for PMs who previously had to wait days for a data pull.

14. Delivery Management

Understanding how your team ships code, whether it’s sprint cycles, deployment pipelines, feature flags, rollback procedures, makes you a better PM. Not because you need to manage the process (that’s engineering’s job), but because understanding the constraints helps you make better tradeoff decisions.

“Can we ship this behind a feature flag to 10% of users first?” is a much better question than “when will this be done?”

15. Technical Literacy

You don’t need to code, but you need to understand enough about your technology stack to have meaningful conversations with engineering. What’s an API? What are the database constraints? Why does this “simple” change actually require refactoring three services?

The skill is asking good technical questions, not having the answers. When your engineering lead says “that’s a 3-month project,” you should be able to ask “what makes it 3 months?” and understand the answer.


IV. Communication and Influence

These are the skills that get people aligned and keep them there.

16. Stakeholder Management

Your stakeholders have competing priorities, different incentive structures, and varying levels of product literacy. The skill is navigating all of that without losing your strategic direction.

The best approach I’ve found: radical transparency about your decision-making process. Share the data, explain the tradeoffs, make a clear recommendation, and invite disagreement before the decision, not after. People support what they help create, even if they don’t get everything they wanted.

17. Executive Communication

Executives don’t want details. They want: what’s the problem, what’s the recommendation, and what do you need from them. That’s it.

The skill is compression, taking a complex product situation and distilling it into a 2-minute narrative that leads to a clear ask. If you can’t explain your strategy in the time it takes to ride an elevator, you haven’t thought about it clearly enough.

18. Cross-Functional Leadership

PMs lead without authority. You can’t tell engineering what to build, design what to design, or marketing what to say. You can only influence.

The skill is making other teams WANT to follow your lead because you’ve earned their trust. That means understanding their constraints, respecting their expertise, giving them credit publicly, and never throwing them under the bus when something goes wrong.

19. Writing as a Leadership Tool

Product managers who write well have an outsized advantage. Strategy docs, product briefs, stakeholder updates, customer communications – writing is how PMs scale their influence beyond the meetings they attend.

Jeff Bezos banned PowerPoint at Amazon for a reason. Clear writing forces clear thinking. If you can’t write a coherent one-page strategy doc, your strategy probably isn’t coherent.

20. Storytelling with Data

Data alone doesn’t persuade anyone. The skill is wrapping data in a narrative that makes people care. “Churn increased 3%” is a data point. “We’re losing 40 paying customers every month, and here’s what they’re telling us on the way out the door” is a story that drives action.

Every dashboard metric should have a “so what?” attached to it. If you can’t articulate the “so what,” the metric isn’t useful yet.


V. Personal Mastery

These are the skills that compound over time and separate the good from the great.

21. AI Fluency

This is the new table-stakes skill for 2026. Not building AI products (though that’s increasingly common) but using AI tools to accelerate your own work.

I like Dell computers tagline of: “It’s a you-multiplier.”

Customer research synthesis, competitive analysis, PRD drafting, experiment design, data analysis, all of these are dramatically faster with AI assistance. PMs who aren’t using AI in their daily workflow are leaving massive productivity on the table.

The skill isn’t prompting. It’s knowing which parts of your work benefit from AI acceleration and which parts still require human judgment. Strategy, customer relationships, and cross-functional trust can’t be automated. Research synthesis, first-draft writing, and data analysis absolutely can.

22. Product Evangelism

Your product needs a champion, and that’s you. The skill is inspiring genuine excitement in your team, your stakeholders, and your customers without crossing the line into hype.

The best product evangelists I’ve seen lead with the customer problem, not the product solution. “Let me tell you about a pastor who spent 12 hours preparing a single sermon because our tools weren’t good enough” hits harder than “let me show you our new feature.”

23. Managing Your Energy, Not Just Your Time

PM burnout is real. The role pulls you in every direction: stakeholder meetings, customer calls, sprint planning, strategy reviews, fire drills. You can optimize your calendar perfectly and still burn out.

The skill is recognizing which activities give you energy and which drain it, then structuring your week accordingly. For me, customer conversations and strategy work are energizing. Back-to-back status meetings are draining. I protect my calendar accordingly.

24. Continuous Learning

The product management discipline is evolving rapidly. The frameworks that worked 3 years ago might not work today. The best PMs read broadly, attend selectively, and most importantly apply what they learn immediately.

Books that have shaped my thinking: Inspired by Marty CaganContinuous Discovery Habits by Teresa Torres, The Lean Startup by Eric Ries, Escaping the Build Trap by Melissa Perri, and Chief Customer Officer 2.0 by Jeanne Bliss. But reading without applying is just entertainment.

25. Intellectual Humility

This might be the most important skill on the entire list. The willingness to say “I was wrong” or “I don’t know” is what separates PMs who keep growing from ones who plateau.

Every strong opinion you hold about your product, your customers, or your market should come with an asterisk: “based on what I know right now.” New data should change your mind. Customer feedback that contradicts your hypothesis should make you curious, not defensive.

The best product managers I’ve worked with hold their strategies with conviction AND their assumptions with humility. That balance is the whole game.


The Thread That Connects All 25

If I had to distill all of these into a single principle, it would be this: the best product managers are relentlessly curious about their customers and brutally honest about what they don’t know.

Every skill on this list is either about understanding customers more deeply or making better decisions with incomplete information. That’s the job. Everything else is just technique.

The good news? Every one of these skills is learnable. None of them require a specific degree, a specific title, or a specific number of years in the role. They require intentional practice and the willingness to be uncomfortable while you’re learning.

Start with the ones where you have the biggest gap. Work on them deliberately. And be patient with yourself. The best PMs I know are still working on all 25.


Frequently Asked Questions

What is the most important skill for a product manager?

Deep customer knowledge is the foundational skill that enables everything else. Without a genuine understanding of your customers, their workflows, pain points, and goals, no amount of strategic thinking, technical literacy, or stakeholder management will produce great products. Build a habit of weekly customer conversations and the other skills become dramatically more effective.

How do product managers use AI in 2026?

Product managers use AI primarily for research acceleration like synthesizing customer interviews, generating competitive intelligence, drafting PRDs and experiment hypotheses, and querying data with natural language. The key skill is knowing which tasks benefit from AI assistance (research, analysis, first drafts) and which still require human judgment (strategy decisions, customer relationships, cross-functional trust-building).

What technical skills do product managers need?

Product managers don’t need to code, but they need enough technical literacy to have meaningful conversations with engineering. This includes understanding APIs, database constraints, deployment processes, and architectural tradeoffs. The goal isn’t to make technical decisions, it’s to ask informed questions and understand the implications of technical choices on product capabilities and timelines.

How do you transition into product management?

The most common entry points are from engineering, design, data analytics, or customer-facing roles like support or sales. Each background brings a natural strength: engineers bring technical depth, designers bring user empathy, analysts bring data fluency, and customer-facing roles bring direct insight into user pain points. Focus on building the skills in whichever category you’re weakest. Most transitions fail not because of lack of domain knowledge, but because of gaps in communication, strategic thinking, or customer understanding.

The 10 Product Strategy Mistakes I Keep Seeing (After 10+ Years in SaaS)

An enamel pin about Product Management

I’ve made every one of these mistakes. Some of them more than once. Product strategy reads well in a blog post, but in practice it’s a minefield of competing priorities, stakeholder pressure, and the constant temptation to say yes to everything.

After more than a decade leading product and growth for SaaS companies – including subscription products serving millions of users – I’ve developed a pretty reliable list of strategy mistakes that kill momentum. Not the theoretical kind you read about in business school. The real kind. The ones that cost you quarters.

Here are the 10 pitfalls I keep coming back to, the ones that have cost me the most time, energy, and momentum over the years.

What is Product Strategy, Really?

Before we get into the mistakes, let’s get aligned on what product strategy actually is – because the lack of a shared definition is often the first problem.

Product strategy is the set of choices that connect your company’s vision to the work your team does every day. It answers three questions:

  1.  Who are we building for? (target audience)
  2.  What problem are we solving for them? (value proposition)
  3. How does this create value for the business? (business model)

Marty Cagan, author of Inspired and founding partner at Silicon Valley Product Group, puts it simply: strategy is about deciding which problems are worth solving. Roman Pichler frames it as the path to your product vision – the high-level plan for achieving your goals.

The important thing is that strategy is about CHOICES. Not a roadmap. Not a feature list. Choices about what you’ll do, and more importantly, what you won’t do.

With that foundation, here are the 10 mistakes that undermine those choices.

Mistake 1: Confusing Activity with Progress

This is the one that gets almost everyone. You ship a feature. Then another. Then another. Your release notes look great. Your team feels productive.

But the metrics aren’t changing.

I’ve lived this. We shipped feature after feature and our conversion numbers stayed flat. Lots of effort, but no forward motion. The problem was that we were building things that were nice to have, not things that moved the needle.

This is what the Jobs-to-be-Done (JTBD) framework helps you avoid. When you understand the actual job your customer is hiring your product to do, it becomes much easier to evaluate whether a feature advances that job or just adds noise. Clayton Christensen’s insight was that customers don’t buy products – they hire them to make progress. If your feature doesn’t help the customer make progress on their core job, it’s activity, not progress.

How to avoid it: Before greenlighting any feature, ask “which metric does this move, and by how much?” If the team can’t answer that clearly, the feature isn’t ready to build. This is easy to say, but extremely difficult to do. Use a prioritization framework like RICE scoring (Reach, Impact, Confidence, Effort) to force the conversation beyond gut feel.

Mistake 2: Strategy by Consensus

There’s a version of inclusive leadership that sounds great in theory but kills strategy in practice. You bring everyone to the table. You gather input. You synthesize. You try to find a path that makes all stakeholders happy.

… and you end up with a strategy that offends no one and inspires no one.

Real strategy requires choices. Hard ones. The kind where someone in the room won’t like the answer. If your strategy document doesn’t explicitly state what you’re NOT doing, it’s a wish list.

This is what killed products like Google+. Google had the engineering talent, the distribution, and the resources to build a social network. But the strategy tried to be everything to everyone – a Facebook competitor, a Twitter alternative, an identity platform, a photo sharing service. No hard choices were made and the product sadly died a slow death by committee.

How to avoid it: I’ve learned (the hard way) that my job is to make everyone feel heard, synthesize the inputs, make a clear decision, and then communicate the reasoning. People can disagree with a well-reasoned decision, what they can’t work with is ambiguity. Write down your strategy in one page. If it doesn’t fit on one page, you haven’t made enough choices yet.

Mistake 3: Copying the Competition

Your competitor launches a feature. Your sales team forwards the announcement. Your CEO asks “why don’t we have this?” And suddenly your roadmap has a new top priority that wasn’t there yesterday – classic!

I’ve fallen into this trap more than I’d like to admit. You absolutely should know what your competitors are doing. The real risk is letting their decisions drive YOUR strategy.

When you copy a competitor’s feature, you’re solving for THEIR customers with THEIR context.

You don’t know why they built it. You don’t know if it’s working. You don’t know if they’re about to kill it. You’re making a strategic bet based on a press release.

Gibson Biddle, former VP of Product at Netflix, uses what he calls the DHM Model – Delight, Hard-to-Copy, and Margin-Enhancing. The “hard-to-copy” piece is key but with AI it’s getting more difficult. If your strategy is just replicating what competitors build, you’ll always be behind AND you’ll never build anything that’s uniquely valuable to your users.

How to avoid it: Understand what problem the competitor is trying to solve, then ask whether YOUR users have that same problem. Sometimes they do, and then you should solve it in a way that fits your product, your architecture, and your users’ workflow. Sometimes they don’t, and the right answer is “we’re not building that” – Jeff Bezos has a great framework for this kind of decision.

Mistake 4: Ignoring the Metrics That Actually Matter

Vanity metrics are seductive. Page views are up! Sign-ups are growing! App downloads hit a new record!

But if your churn rate is climbing at the same time, you’ve got a leaky bucket. And no amount of top-of-funnel growth fixes a retention problem.

I’ve been in situations where the dashboards looked green but the business was struggling, and situations where the top-line numbers looked concerning but the underlying health was strong. The difference was which metrics we were watching.

This is what the North Star Metric concept helps solve. Your North Star is the single metric that best captures the core value your product delivers to customers. For Spotify, it’s time spent listening. For Airbnb, it’s nights booked. For a subscription SaaS product, it might be weekly active usage or feature adoption depth.

How to avoid it: For any subscription product, the metrics that matter are: how many people start a trial, how many convert to paid, how many cancel, and what’s the net change. Everything else is context. Build your dashboard around these numbers first, THEN add the supporting metrics that explain why they’re moving.

Mistake 5: Trying to Serve Everyone

This one is especially hard in mission-driven organizations. You WANT to help everyone. Every user segment seems important. Every use case feels valid.

But trying to serve everyone equally means serving no one well.

Your onboarding can’t be optimized for beginners AND power users simultaneously. Your pricing can’t be accessible to individuals AND competitive for enterprises without compromise.

Trying to serve everyone equally means serving no one well.

Kodak learned this the hard way. They saw digital photography coming but tried to straddle both worlds – maintaining their film business while half-heartedly investing in digital. They served neither audience well, and a company that once dominated an entire industry filed for bankruptcy in 2012.

How to avoid it: The best products I’ve used (and the best products I’ve built) made clear choices about who they were for. They explicitly prioritized one audience and designed everything around their needs first. When you do that well, other segments often benefit anyway, from a focused, coherent product rather than a compromised one. Define your primary persona. Write it on the wall. When someone asks “but what about this other segment?” you have your answer ready.

Mistake 6: Having No Strategy at All

This sounds obvious, but it’s shockingly common. My last few roles I’ve called “The Fixer” because years of the company running hard has caused them to lose their focus and they suddenly realize they don’t have a strategy. They have a roadmap. They have a backlog. They have quarterly goals. They ship things on time.

But there’s no unifying thesis about WHERE the product is going and WHY.

Roman Pichler calls this the most common product strategy mistake he encounters. Teams jump straight from vision to execution without the strategic layer that connects them. The result is a collection of features that individually make sense, but collectively don’t tell a coherent story.

How to avoid it: Your strategy should be a testable hypothesis, not a document that lives somewhere on the server. Try this format: “We believe that [target audience] struggles with [problem]. If we build [solution], we’ll see [measurable outcome] within [timeframe].” If you can’t fill in those blanks, you don’t have a strategy yet. You have a to-do list.

Mistake 7: Treating Strategy as Static

You spend weeks crafting the perfect strategy document. Leadership signs off. The team aligns. You print it out and pin it to the wall.

Six months later, the market has shifted, a competitor has launched something unexpected, and your customers are telling you something you didn’t anticipate. But the strategy is “locked.”

Eric Ries built the entire Lean Startup methodology around this problem. The Build-Measure-Learn loop isn’t just for startups – it’s for any team that operates in uncertainty, which is literally every product team. Your strategy should have built-in checkpoints where you evaluate whether your assumptions still hold.

How to avoid it: Set quarterly strategy reviews. Not annual planning sessions where you redo everything – lightweight reviews where you ask: “What have we learned? What’s changed? Do our bets still make sense?” The best strategies are living documents, not manifestos. Jeff Bezos distinguishes between “one-way door” decisions (irreversible, deliberate slowly) and “two-way door” decisions (reversible, move fast). Most strategic choices are two-way doors. Treat them that way.

Mistake 8: Skipping Validation Before Committing

You have a great idea. The team is excited. Leadership is bought in. You go straight to building.

Three months later, you launch to silence. Customers don’t want it, don’t understand it, or already solved the problem another way.

I’ve seen this pattern destroy entire quarters. The excitement of a new idea creates momentum that skips right past the “should we build this?” question and lands on “how do we build this?”

How to avoid it: Before committing engineering resources, validate the problem AND the solution. Talk to 5-10 customers. Run a fake door test. Build a prototype and put it in front of real users. Teresa Torres’ Continuous Discovery framework calls this “opportunity solution trees” – mapping the opportunity space before jumping to solutions. The cost of 2 weeks of discovery is nothing compared to 3 months of building the wrong thing.

Mistake 9: Siloed Strategy Without Cross-Functional Input

Product writes the strategy. Engineering learns about it at spring planning. Design gets brought in when wireframes are needed. Marketing finds out at launch.

This isn’t strategy. It’s a relay race where nobody can actually see the finish line.

The best product strategies I’ve been part of were shaped by engineering constraints, design insights, and market intelligence from day one. Your engineers know what’s technically feasible and where the architecture creates opportunities. Your designers have insights about user behavior that data alone can’t capture. Your sales and support teams hear objections and pain points every day.

How to avoid it: Include engineering and design leads in strategy formation, not just execution. Share customer research broadly. Bring it up in meetings regularly. Make your strategy document accessible to everyone on the team, not locked into a leadership slide deck. When people understand the WHY behind the strategy, they make better decisions at every level.

Mistake 10: Being Unrealistic About Execution Capacity

This is the mistake that ties all the others together. You have a clear strategy. You’ve validated the direction. You’ve made all the hard choices about what to build.

Then you commit to 3x more than your team can actually deliver.

Your roadmap becomes a pressure cooker. Quality drops. Shortcuts get taken. The team burns out. And paradoxically, you end up delivering LESS than if you’d committed to fewer things done with excellence.

I’ve seen this cycle repeat across every company I’ve worked with. The ambition is always bigger than the capacity, and the gap gets filled with overtime and technical debt instead of honest prioritization.

How to avoid it: Be ruthlessly honest about how much your team can ship in a quarter. Then cut 20% from that estimate. Even writing that sounds crazy, but it must be done. Use the OKR framework (Objectives and Key Results) to limit your bets to 3-5 outcomes per quarter – not 3-5 per team, 3-5 total. Warren Buffett’s “two-list strategy” applies here: write down your top 25 priorities, circle the top 5, and treat the other 20 as your “avoid at all costs” list (avoid them entirely until the top 5 are achieved). The same logic applies to product strategy.

The Uncomfortable Truth

Product strategy is about having the discipline to say no to good ideas that don’t align with what matters most right now.

Every mistake on this list comes from the same root: the unwillingness to make a hard choice and live with the tradeoff.

Choose the right things. Decide clearly. Pick your own path. (I wrote about this focus in 5 things needed for business success.) Watch the honest metrics. Serve someone specific.

Strategy is the art of sacrifice. The sooner you get comfortable with that, the better your products will be.

Product Strategy Checklist

Before you finalize your next product strategy, run through this list:

  • Can you state your target audience in one sentence?
  • Can you articulate the core problem you’re solving for them?
  • Does your strategy explicitly state what you’re NOT doing?
  • Is every major initiative tied to a measurable outcome?
  • Have you validated your assumptions with real customers?
  • Does your team have the capacity to execute this quarter’s plan?
  • Have you set a date to review and adapt the strategy?
  • Can your entire team articulate the strategy without looking at a document?
  • Is there a clear North Star Metric everyone is aligned on?
  • Would you bet your own money on this plan working?

If you can’t check every box, your strategy still has gaps. Go back and make the hard choices.

Frequently Asked Questions

What are the most common product strategy mistakes?

The most common product strategy mistakes include confusing activity with progress (shipping features that don’t move metrics), strategy by consensus (avoiding hard choices to keep everyone happy), copying competitors instead of solving for your own users, ignoring retention metrics in favor of vanity metrics, and trying to serve every user segment equally. The root cause of most strategy failures is an unwillingness to make clear choices and accept tradeoffs.

What is the difference between product strategy and a product roadmap?

Product strategy defines WHERE you’re going and WHY. It’s about choices, tradeoffs, and the thesis behind your product direction. A product roadmap is the HOW and WHEN – the sequence of work that executes the strategy. A roadmap without a strategy is just a feature list. A strategy without a roadmap is just a vision. You need both, but strategy comes first.

How do you create an effective product strategy?

An effective product strategy begins with a clear understanding of your target audience, the problem you’re solving, and how solving it creates business value. Frameworks like Jobs-to-be-Done help identify what customers actually need. Validate your assumptions through customer discovery before committing resources. Set a North Star Metric to track progress. Review and adapt quarterly. Most importantly, be explicit about what you will NOT do – that’s ultimately where the real strategy lives.

How often should you update your product strategy?

Product strategy should be reviewed quarterly and updated when market conditions, customer needs, or business goals change significantly. It should NOT change weekly based on competitor moves or stakeholder requests. The best approach is setting lightweight quarterly checkpoints where you evaluate whether your core assumptions still hold, while keeping the overall strategic direction stable enough for the team to execute with confidence.

25 Skills a Product Manager should focus on in 2025

I’ve been in product leadership long before the term ‘Product Management’ became a common buzzword. Over the past eight years, I’ve held various titles with ‘Product’ in them, and yet, every day brings new lessons and insights. As I approach 2025, I’ve realized the importance of grounding myself in the principles that have guided me so far. This list serves as a personal reminder—a collection of foundations I’ve built upon, shaped by insights from books like Crucial Conversations, INSPIRED, The E-Myth Revisited, and The Mom Test.

I. Foundational Principles

  1. Embrace the Product Mindset: Product management is not just a job; it’s a mindset 1. It requires a passion for solving customer problems and a commitment to continuous improvement.
  2. Deep Customer Knowledge: Become an undisputed expert on your customers2. This involves understanding their needs, pain points, and desires through both qualitative and quantitative data3.
  3. Data-Driven Decisions: Be comfortable with data and analytics4. Use data to understand how customers are using your products, analyze A/B test results, and inform product decisions.
  4. Master the Product: Be an expert on your actual product and your industry. Share your knowledge openly and generously.
  5. Continuous Learning: Stay intellectually curious and quickly apply new technologies to solve problems for customers5.

II. Team Dynamics & Collaboration

  1. Build Strong Product Teams: Focus on building and nurturing strong, collaborative relationships with your product team. A product team typically includes a product manager, a product designer, and engineers.
  2. Empowered Teams: Champion empowered product teams that are equipped to solve business problems. Ensure your team understands the company vision and how their work contributes to the larger purpose6.
  3. Cross-Functional Collaboration: Work effectively with product designers, engineers, and product marketing managers. Ensure product marketing is embedded with the product team7.
  4. Effective Communication: Communicate product learnings clearly and consistently. Keep stakeholders informed and engaged8.
  5. Delivery Management: Recognize the importance of delivery managers in removing obstacles for the team. Their work ensures that the team can focus on building valuable products9.

III. Strategic Product Development

  1. Product Vision: Develop a compelling and inspiring product vision10. Use it to articulate your purpose and inspire the team11.
  2. Product Strategy: Define a clear product strategy that serves as a path to achieving the product vision. Ensure alignment between the product strategy and overall business strategy12.
  3. Product Principles: Complement your product vision and strategy with a set of guiding principles that define the nature of the products you want to create13.
  4. Outcome-Focused Roadmaps: Shift from output-based roadmaps to those focused on business outcomes14. Ensure every roadmap item is tied to a specific business objective.
  5. Embrace Discovery: Prioritize product discovery, which involves collaboration between product management, UX design, and engineering. Tackle risks before writing any code.
  6. Prioritize Ruthlessly: Focus on a single, scalable idea rather than jumping on every good one15.
  7. Problem-First Approach: Focus on solving the underlying problem. Don’t get caught up in the solution before you’ve fully understood the problem16.
  8. Customer Discovery Programs: Use customer discovery programs to ensure that you’re building a product that customers love.

IV. Product Discovery and Delivery

  1. Master Discovery Techniques: Utilize various discovery techniques to understand customer needs and validate ideas. This includes opportunity assessment, customer letters, and startup canvases.
  2. Rapid Experimentation: Use prototypes to conduct rapid experiments17. Test ideas with users, customers, engineers, and business stakeholders in hours and days, not weeks and months18.
  3. Usability Testing: Conduct regular usability tests to identify friction points in prototypes. Use these tests to learn about how customers use your products19.
  4. Continuous Delivery: Strive for frequent release cycles to ensure teams move quickly and release with confidence.
  5. Iterative Approach: Understand that it typically takes several iterations to get the execution of an idea to the point where it delivers the expected business value20.

V. Leadership & Growth

  1. Product Evangelism: Become an effective evangelist for your product. Inspire your team, stakeholders, and customers by “selling the dream”. Use prototypes to communicate the product vision21.
  2. Adaptability: Be prepared to adapt to changes in the market and new trends22. Be flexible with the details, but remain stubborn on the overall vision.

Conclusion

Product management in 2025 will demand a combination of deep technical knowledge, strategic thinking, and a genuine passion for solving customer problems. By focusing on these 25 areas, product managers can position themselves for success and contribute to the creation of truly impactful products. It’s not about having all the answers, but about asking the right questions and embracing a continuous learning mindset.


  1. “The art of Product Management is the art of life itself. Surround your-selves by great people, focus on your mojo, build great stuff with integrity, hold strong opinions but lightly. And Marty is one of the best teachers of this art.” —Punit Soni, Founder and CEO, Robin, Former Google APM ↩︎
  2. “you need to become an acknowledged expert on the customer: their issues, pains, desires, how they think—and for business products, how they work, and how they decide to buy.” —INSPIRED, Marty Cagan ↩︎
  3. “Without this deep customer knowledge, you’re just guessing. This requires both qualitative learning (to understand why our users and customers behave the way they do), and quantitative learning (to understand what they are doing)” —INSPIRED, Marty Cagan ↩︎
  4. “… product managers are expected to be comfortable with data and analytics. They are expected to have both quantitative skills as well as qualitative skills. The Internet enables unprecedented volume and timeliness of data.
    A big part of knowing your customer is understanding what they’re doing with your product. Most product managers start their day with half an hour or so in the analytics tools, understanding what’s been happening in the past 24 hours. They’re looking at sales analytics and usage analytics. They’re looking at the results of A/B tests.” —INSPIRED, Marty Cagan ↩︎
  5. Be “intellec-tually curious, quickly learning and applying new technologies to solve problems for customers, to reach new audiences, or to enable new business models.” —INSPIRED, Marty Cagan ↩︎
  6. “The product teams need to have the necessary business context. They need to have a solid understanding of where the company is heading, and they need to know how their particular team is supposed to contribute to the larger purpose.” —INSPIRED, Marty Cagan ↩︎
  7. “… because that’s where they are connected to the experience that the customer is having an opportunity to engage with.” —INSPIRED, Martina Lauchengco ↩︎
  8. “Evangelize continuously and relentlessly. There is no such thing as over-communicating when it comes to explaining and selling the vision. Especially in larger organizations, there is sim-ply no escaping the need for near-constant evangelization. You’ll find that people in all corners of the company will at random times get nervous or scared about something they see or hear. Quickly reassure them before their fear infects others.” —INSPIRED, Marty Cagan ↩︎
  9. “In growth-stage and enterprise companies, many product managers complain that they have to spend far too much of their time doing project management activities. As a result, they have almost no time to address their primary product responsibility: ensuring that the engineers have a product worth building.
    Delivery managers are a special type of project manager whose mission is all about removing obstacles—also known as impediments—for the team. Sometimes, these obstacles involve other product teams, and sometimes they involve non-product functions. In a single day, they might track down someone in marketing and press them for a decision or an approval, coordinate with the delivery manager on another team about prioritizing a key dependency, persuade a product designer to create some visual assets for one of the front-end developers, and deal with a dozen other similar roadblocks.” —INSPIRED, Marty Cagan ↩︎
  10. “The product vision describes the future we are trying to create, typically somewhere between two and five years out. For hardware or device-centric companies, it’s usually five to 10 years out.
    Note that this is not the same as the company mission statement. Examples of mission statements are “organize the world’s information” or “make the world more open and connected” or “enable anyone any-where to buy anything anytime.” Mission statements are useful, but they don’t say anything about how we plan on accomplishing that. That’s what the product vision is for.” —INSPIRED, Marty Cagan ↩︎
  11. “Start with why. This is coincidentally the name of a great book on the value of product vision by Simon Sinek. The central notion here is to use the product vision to articulate your purpose. Everything follows from that.
    Fall in love with the problem, not with the solution. I hope you’ve heard this before, as it’s been said many times, in many ways, by many people. But it’s very true and something a great many product people struggle with.” —INSPIRED, Marty Cagan ↩︎
  12. “Communicate the strategy across the organization. This is part of evangelizing the vision. It’s important that all key business partners in the company know the customers we’re focused on now and which are planned for later. Stay especially closely synced with sales, marketing, finance, and service.” —INSPIRED, Marty Cagan ↩︎
  13. “Where the product vision describes the future you want to create, and the product strategy describes your path to achieving that vision, the product principles speak to the nature of the products you want to create.” —INSPIRED, Marty Cagan ↩︎
  14. … focus “on outcome and not output. Realize that typical product roadmaps are all about output. Yet, good teams are asked to deliver business results.
    Most of the product world has the same definition for product roadmap, but there are a few variations. I define product roadmap as a prioritized list of features and projects your team has been asked to work on. These product roadmaps are usually done on a quarterly basis, but sometimes they are a rolling three months, and some companies do annual roadmaps.” —INSPIRED, Marty Cagan ↩︎
  15. “Startups are about focusing and executing on a single, scalable idea rather than jumping on every good one which crosses your desk.” —The Mom Test, Rob Fitzpatrick ↩︎
  16. “This is another reason why typical product roadmaps are so problematic. They’re lists of features and projects where each feature or project is a possible solution. Somebody believes that feature will solve the problem or it wouldn’t be on the roadmap, but it’s all too possible they are wrong. It’s not their fault—there’s just no way to know at the stage it’s put on the roadmap.
    However, there very likely is a legitimate problem behind that potential solution, and it’s our job in the product organization to tease out the underlying problem and ensure that whatever solution we deliver solves that underlying problem.” —INSPIRED, Marty Cagan ↩︎
  17. “… use prototypes to conduct rapid experiments in product discovery, and then in delivery, we build and release products in hopes of achieving product/market fit, which is a key step on the way to delivering on the company’s product vision.” —INSPIRED, Marty Cagan ↩︎
  18. “If we can prototype and test ideas with users, customers, engi-neers, and business stakeholders in hours and days—rather than in weeks and months—it changes the dynamics, and most important, the results.
    It’s worth pointing out that it isn’t the list of ideas on the roadmap that’s the problem. If it was just ideas, there’s not much harm in that. The issue is that anytime you put a list of ideas on a document entitled “roadmap,” no matter how many disclaimers you put on it, people across the company will interpret the items as a commitment. And that’s the crux of the problem, because now you’re committed to build-ing and delivering this thing, even when it doesn’t solve the underlying problem.” —INSPIRED, Marty Cagan ↩︎
  19. “You will need to define in advance the set of tasks that you want to test. Usually, these are fairly obvious. If, for example, you’re building an alarm clock app for a mobile device, your users will need to do things like set an alarm, find and hit the snooze button, and so on. There may also be more obscure tasks, but concentrate on the primary tasks—the ones that users will do most of the time.
    Some people still believe that the product manager and the prod-uct designer are too close to the product to do this type of testing objectively, and they may either get their feelings hurt or only hear what they want to hear. We get past this obstacle in two ways. First, we train the product managers and designers on how to conduct themselves, and second, we make sure the test happens quickly—before they fall in love with their own ideas. Good prod-uct managers know they will get the product wrong initially and that nobody gets it right the first time. They know that learning from these tests is the fastest path to a successful product.” —INSPIRED, Marty Cagan ↩︎
  20. “…even with the ideas that do prove to be valuable, usable, feasible, and viable, it typically takes several itera-tions to get the execution of this idea to the point where it delivers the expected business value that management was hoping for. This is often referred to as time to money” —INSPIRED, Marty Cagan  ↩︎
  21. “The product vision needs to inspire. Remember that we need product teams of missionaries, not mercenaries. More than anything else, it is the product vision that will inspire missionary-like passion in the organization. Create something you can get excited about. You can make any product vision meaningful if you focus on how you genuinely help your users and customers.” —INSPIRED, Marty Cagan ↩︎
  22. “Determine and embrace relevant and meaningful trends. Too many companies ignore important trends for far too long. It is not very hard to identify the important trends. What’s hard is to help the organization understand how those trends can be leveraged by your products to solve customer problems in new and better ways.” —INSPIRED, Marty Cagan ↩︎