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.