Product–market fit is always on my mind. It's a relatively simple concept: find a real problem, build the solution, iterate. If you believe the "95% of startups fail" stat that everyone loves to quote, I'd argue this is where most of them go wrong. They never truly find product–market fit, so the foundations their business is built on are shaky AF.
But since tools like ChatGPT became ubiquitous, things have shifted dramatically.
ChatGPT is powerful and super useful, and that's exactly the risk. If your product can be replaced by a prompt and a few clicks, your moat, if it ever existed, disappears overnight. As Miqdad Jaffer, Product Lead at OpenAI, put it:
"The biggest mistake I see AI founders make is treating PMF like a checkbox. In the AI world, PMF is a moving target. Your users' definition of 'intelligent enough' changes every month as they interact with better AI systems elsewhere."
The next wave of AI products can't just assist, they have to anticipate. They need to deeply understand context, interpret intent, and execute multi-step workflows on the user's behalf. I call this Radical Context: AI that operates invisibly, integrates with real-world systems, and removes friction instead of adding to it.
In my opinion, this is the new strategy. Tools built on Radical Context don't leave users stitching together tasks, jumping between tabs, or copy–pasting output. Instead, they carry the baton from start to finish: silently, efficiently, intelligently.
First-gen AI tools help you get started.
Next-gen tools will get it done for you.
That's where the opportunity is, and where truly resilient startups will be built.