When AI agents write code, tolerating technical debt becomes dangerous. The speaker argues for strict consistency and strong conventions instead of shipping code that merely appears to work, especially without adequate test coverage. AI needs robust feedback loops and guarantees built in to reason reliably.
I strongly believe that no matter what you're doing, you need to have consistency and strong conventions, and that the ability for us to have an appetite for what is acceptable tech debt to move forward has to go down significantly. It's a shift in paradigm thinking. It used to be that perfect is the enemy of good enough, and that's still true. But when it comes to what we're shipping and how we're shipping, we really do need to focus on, yeah, if my test coverage isn't good enough, or if I don't have any tests, but it works good enough, let's go. That at this point feels pretty dangerous to me. Like, I need ways that I can maintain guarantees so that my coding agent can continue to get feedback from its environment in a real big meta way. This is like, how do we instill a form of embodied cognition into our coding agents, right? It's a feed forward to get a feedback loop so that we can enhance the cognition of our coding agents.
