Tag: AI Overviews

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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.

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The Traffic You Depend On Is Being Answered Without You

I’ve been staring at a traffic chart for the last three weeks that I can’t stop thinking about.

It’s Chegg’s chart. The online education platform lost 34% of its organic visitors in a matter of months. That’s a cliff. Their keyword footprint went from 11.1 million to 3.5 million.

And the culprit wasn’t a competitor outranking them or a Google algorithm update penalizing thin content. It was Google answering the questions before anyone ever clicked.

The Machine That Eats Your Top of Funnel

Google’s AI Overviews are the AI-generated summaries that now appear at the top of search results, and they are fundamentally changing what it means to rank on Google. For years, the playbook was clear: create valuable content, optimize it for search, capture intent, convert visitors.

That model assumed one thing: that people would actually click through to your site.

AI Overviews break that assumption.

When someone searches “how to explain forgiveness to a congregation” or “best illustrations for an Easter sermon,” Google can now synthesize an answer from multiple sources and present it directly in the search results. No click required. No visit to your site. No entry into your funnel.

Tomasz Tunguz laid this out clearly in a recent analysis:

“Content dependency on organic search is no longer a sustainable acquisition model.”

That sentence should be pinned to the wall of every SaaS product leader who relies on organic traffic (understanding these shifts is a critical PM skill) to fill the top of their funnel.

Chegg Is the Preview

The pattern is showing up everywhere. Stack Overflow, the platform that essentially taught a generation of developers how to code (including me), is seeing the same erosion. Informational queries that used to drive millions of visits are now being answered inline by AI.

The New York Times is thriving. Why? How? A $100 million content licensing deal with Google. They’re feeding the AI, on their terms, for revenue.

Here’s what I think the data is telling us:

1. Q&A-style content is the most vulnerable. If your value proposition is answering questions that can be summarized in a paragraph, you’re in the blast radius.
2. Branded, premium, behind-the-paywall content is more defensible. AI Overviews can summarize a sermon topic, but they can’t replicate a full manuscript, a downloadable media pack, or an AI-powered sermon builder.
3. The winners will be the ones who stop treating Google as a given and start building direct relationships with their audience.

What This Means for SaaS Product Leaders

I run product and growth for a content platform that serves pastors. We have 245,000+ sermons and 50,000+ text illustrations, exactly the kind of content library that ranks well for long-tail informational queries.

For years, that library has been our primary discovery engine. Pastors search for sermon ideas, find us, browse free content, start a trial, and convert to paid.

That model still works today, but we’re down around that same 34% mark and from what I can tell so is everyone, across all industries. But I’d be naive to assume it’ll work the same way in 18 months.

Here’s the uncomfortable math: if organic traffic drops by even 20-30%, and organic is your dominant acquisition channel, no amount of conversion rate optimization saves you. You can have a best-in-class trial-to-paid flow and still miss your numbers because not enough people are entering the funnel in the first place.

It’s an exposure problem. And it requires a fundamentally different response than what most product teams are used to.

The Diagnostic Before the Panic

Before you restructure your entire growth strategy, there’s a critical diagnostic step that teams often skip. You need to know whether AI Overviews are actually appearing on YOUR highest-value queries.

Here’s the move:

  • Pull your top 50 keywords from Google Search Console. Look at click-through rate trends over the last 90 days, segmented by week.
  • The signature you’re looking for: stable or rising impressions, but declining CTR. That pattern means Google is showing your content in results, but users aren’t clicking because the AI Overview already gave them what they needed.
  • If your impressions are dropping, that’s a competitor or algorithm problem. If impressions are stable but clicks are falling, that’s AI Overview cannibalization. Different diagnosis, different treatment.

Most teams I talk to are just making this distinction. They’re looking at traffic declines and assuming it’s an SEO problem when it might be a platform shift problem. The difference matters.

Three Moves to Make Now

I’m not going to pretend I have the full playbook figured out. But here’s where my thinking is landing:

1. Shift discovery investment toward owned channels.
Email nurture sequences, community platforms, pastoral networks, partnerships with organizations that already have the audience. Organic search should be one of many channels, not the only one. Every dollar of effort I’m putting into SEO-driven top-of-funnel content I’m asking if that same effort in email or community would be more durable.

2. Make your paywall content genuinely irreplaceable.
AI can summarize a sermon outline. It cannot replicate a curated media pack, a professionally produced video series, or a workflow tool that saves someone three hours a week. The content that survives AI summarization is the content that requires depth, production value, or interactivity: things a search snippet can’t deliver.

3. Explore whether the threat is also an opportunity.
The NYT licensing deal tells us something important: Google is willing to pay for premium vertical content. If you’re the dominant content platform in your niche, there may be a deal to be made.

A licensing partnership could convert a traffic threat into a revenue stream while maintaining brand visibility inside AI-generated results. Worth exploring.

The Bigger Lesson

I keep coming back to something I’ve learned over the last few years leading product: the most dangerous risks are the ones that look like stability. Traffic holding steady today doesn’t mean the foundation isn’t shifting underneath.

Chegg’s team didn’t wake up one morning to a 34% traffic drop. It happened gradually, then suddenly. The chart looks normal until it doesn’t.

The product leaders who navigate this well will be the ones who diagnosed early, diversified before they had to, and built value that can’t be summarized in a paragraph. The ones who don’t will be staring at a chart they can’t explain and wondering where all the visitors went.

I’d rather be asking the hard questions now than explaining the traffic decline later.

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AI Just Walked Into Your Website Without Knocking

Last month I asked ChatGPT a question I’ve asked Google a thousand times: “What’s a good sermon illustration about forgiveness?”

It gave me a solid answer. Three illustrations, structured with context, application points, even a suggested closing line. It was genuinely useful.

And it never sent me to a single website.

That moment hit me differently than it would have two years ago. I run a platform with over 245,000 sermons and 50,000 illustrations. I didn’t just lose a click. I watched an AI system do what our product does, using content that likely came from sites like ours, and deliver it in a way that made visiting the source unnecessary.

That’s a revenue problem. (I wrote about the traffic implications of this shift recently.) (I wrote about the traffic implications of this shift recently.)

The Zero-Click Layer

Most product leaders I know are still thinking about AI as a feature to bolt onto their product: chatbots, smart search, AI-generated recommendations. And that matters. But there’s a bigger shift happening underneath that conversation.

AI answer engines (ChatGPT, Google AI Overviews, Perplexity) are becoming the front door to the internet. They don’t just search. They visit your site, interpret your content, synthesize it, and serve it directly to the user. The user gets the answer. You get nothing.

Google’s featured snippets started this zero-click trend years ago. BUT what’s different now is the depth. A featured snippet pulls a paragraph. An AI answer engine can synthesize an entire page, or multiple pages, into a comprehensive response that genuinely satisfies the user’s intent.

If your business depends on organic traffic as a top-of-funnel engine, this should keep you up at night.

Your Content Library Is Both Your Greatest Asset and Your Biggest Vulnerability

Here’s the paradox I’ve been sitting with.

We spent years building one of the largest structured content libraries in our space. That library is what drives our organic traffic. It’s what Google indexes. It’s what pastors find when they search “sermon on grace” at 11pm on a Saturday night.

That same library is now what AI systems are ingesting to train their models and generate their answers. The very content that built our moat is being used to fill in the moat.

And here’s what makes it worse. The emerging AI-native competitors in our space don’t even need to win Google rankings. They ARE the AI tool. They’re built to live inside AI workflows, not compete for traditional search clicks.

I think this pattern applies to any SaaS company sitting on a large content asset. If you’ve built your growth engine on content that AI can summarize, you’re exposed.

AEO: A Genuinely Different Discipline

There’s a term gaining traction: AEO, or AI Engine Optimization. And I’ll be honest, my first reaction was skepticism. We don’t need another three-letter acronym.

But the more I’ve dug into it, the more I realize it represents a genuinely different discipline.

SEO optimizes for ranking. AEO optimizes for citation. The goal is to be the source that AI systems reference AND link back to. That requires a fundamentally different content strategy.

Here’s what that looks like in practice:

  1. Structured data becomes non-negotiable. Schema markup, clear metadata, explicit problem-solution framing in your content. AI systems parse structure, not vibes. (Schema.org is the starting point.)
  2. Content architecture matters more than keyword density. How your content is organized (headers, relationships between pages, internal linking) determines how AI systems understand your authority on a topic.
  3. Gated content is a double-edged sword. If your best content is behind a login wall, AI crawlers can’t index it. You’re invisible to the answer engine. But if everything is open, you get summarized without a click. The play is in the middle: structured preview content that AI can cite, with depth that requires the visit.
  4. Domain-specific language is your moat. Generic content gets synthesized away. Content that uses the precise language of your audience (the way a pastor describes their Saturday night prep struggle, the specific vocabulary of sermon structure) is harder for AI to replace and more likely to be cited with attribution.

What I’m Doing About It

I’m not going to pretend I have this figured out. But here’s where my head is:

Audit how AI sees us. Before optimizing anything, we need to understand how our top pages render to AI crawlers. What structured data exists? What’s behind login walls that blocks indexing?

Treat AI referral as a distinct channel. We track direct traffic, organic search, paid. AI referral needs its own lane in our analytics. We can’t optimize what we can’t measure.

Build content AI can’t summarize away. The full sermon text? AI can handle that. But a pastor’s framework for adapting a sermon to their specific congregation? A diagnostic tool for matching an illustration to a particular emotional moment in a service? That’s interactive, personalized, and requires being on the platform.

Move faster than the AI-native competitors. They have the structural advantage of being built for AI workflows. We have the structural advantage of 20+ years of trusted content and relationships. The question is whether we can adapt our distribution before they build our depth.

The Strategies That Got You Here Won’t Sustain You

I keep coming back to this. The strategies that built organic growth over the last decade won’t sustain it over the next five years.

That’s a reason to move, not a reason to panic.

The companies that treat AI answer engines as a new channel will capture disproportionate share of the next era of discovery. The ones that keep optimizing for Google page one while AI summarizes their content into zero-click answers will watch their traffic erode and wonder what happened.

I’d rather be early and wrong about the tactics than late and right about the trend.

The AI just walked into your website. The question is whether it’s going to send people your way, or make visiting you unnecessary.