Generative AI has driven the cost of writing code to near zero. Here's why figuring out *what* to build and how AI search engines find it is the only competitive advantage left.
4 min. read
I had a conversation with a founder last week who was, understandably, a little panicked.
He had just watched a demo of an AI agent spinning up a fully functional web app in a matter of minutes. His question to me was blunt: "If an algorithm can build my product over the weekend for free, what exactly are we doing here? Are product teams obsolete?"
It’s a fair question. Every day there's a new headline predicting the end of software engineering as we know it. But after spending years in the trenches building enterprise platforms and startup MVPs, I can tell you that product development isn't dying.
It’s just growing up.
Today, a team can generate a hundred features in a few days. But without a ruthless product strategy, this superpower becomes a massive liability. We call it the Infinite Software Trap. Because it’s so easy to add "just one more thing," products quickly mutate into bloated, confusing labyrinths that don't actually solve anyone's core problem. Generating code is trivial. Having the discipline to say no to 99 easy features so you can focus on the one workflow your users actually care about? That requires human judgment, empathy, and market foresight. AI can't do that for you. Today, a team can generate a hundred features in a few days. But without a ruthless product strategy, this superpower becomes a massive liability. We call it the Infinite Software Trap. Because it’s so easy to add "just one more thing," products quickly mutate into bloated, confusing labyrinths that don't actually solve anyone's core problem. Generating code is trivial. Having the discipline to say no to 99 easy features so you can focus on the one workflow your users actually care about? That requires human judgment, empathy, and market foresight. AI can't do that for you. Today, a team can generate a hundred features in a few days. But without a ruthless product strategy, this superpower becomes a massive liability. We call it the Infinite Software Trap. Because it’s so easy to add "just one more thing," products quickly mutate into bloated, confusing labyrinths that don't actually solve anyone's core problem. Generating code is trivial. Having the discipline to say no to 99 easy features so you can focus on the one workflow your users actually care about? That requires human judgment, empathy, and market foresight. AI can't do that for you. Today, a team can generate a hundred features in a few days. But without a ruthless product strategy, this superpower becomes a massive liability. We call it the Infinite Software Trap. Because it’s so easy to add "just one more thing," products quickly mutate into bloated, confusing labyrinths that don't actually solve anyone's core problem. Generating code is trivial. Having the discipline to say no to 99 easy features so you can focus on the one workflow your users actually care about? That requires human judgment, empathy, and market foresight. AI can't do that for you.
We are finally moving past the era of the "feature factory." AI is absolutely crushing the cost of execution. But as execution becomes a cheap commodity, the real bottleneck shifts. The hardest part of software development is no longer building the thing right—it’s figuring out the right thing to build.
Think about how we used to build software. Writing and deploying code was expensive, painful, and slow. That natural friction was actually a hidden blessing: because it cost so much to build a feature, you had to think really, really hard before committing to it. Development costs forced prioritization.
AI completely removes that friction.
Today, a team can generate a hundred features in a few days. But without a ruthless product strategy, this superpower becomes a massive liability. We call it the Infinite Software Trap. Because it’s so easy to add "just one more thing," products quickly mutate into bloated, confusing labyrinths that don't actually solve anyone's core problem.
Generating code is trivial. Having the discipline to say no to 99 easy features so you can focus on the one workflow your users actually care about? That requires human judgment, empathy, and market foresight. AI can't do that for you.
There's another massive shift happening that most teams are completely ignoring. The way your customers find your product is changing forever.
We are moving away from traditional Google searches and toward AI answer engines (think ChatGPT, Perplexity, and whatever comes next). This is the rise of Generative Engine Optimization (GEO).
If your digital product lacks semantic clarity, clean architecture, and a hyper-focused value proposition, these AI gatekeepers will simply skip over you. You aren’t just designing interfaces for human eyes anymore; you have to architect products that make immediate sense to multi-agent AI systems. If the LLM doesn't understand exactly what problem you solve, to the end-user, you simply don't exist.
At Praetorix, this shift has completely validated how we work. The days of measuring a team's success by how many "story points" they burned through in a two-week sprint are over.
When we partner with enterprise teams or founders, we focus heavily on senior-led orchestration. Syntax is cheap; strategy is priceless. Through our OPUS Method, we front-load the discovery phase to make sure we are actually solving the right problem before we scale the solution.
The most valuable product teams today are focusing on three things:
AI is finally going to kill the mind-numbing, assembly-line approach to building software. For those of us who actually care about solving real human problems, it’s the best thing that could have ever happened.
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