One point that really stands out is that AI doesn't eliminate the need for architectural thinking, it actually makes it more valuable. At IT Path Solutions, we've seen that when teams invest time in defining architecture, constraints, and success criteria upfront, AI-assisted development becomes far more predictable, maintainable, and scalable.
Loved the idea of using a decision log to keep AI aligned over time.
I had the same realization recently. The moment an agent gets access to real infrastructure, it stops being a prompting problem and starts being an infrastructure problem. We've been moving more and more of those decisions into runtime policies in Failproof AI instead of hoping the model remembers the rules.
Julian Neagu
500+ AI tools shipped solo. Founder of VisionVix.
The docs-first approach is something Iโve seen make a huge difference with AI projects. If the context only lives in chat, things get messy fast. Keeping decisions somewhere stable makes AI way more useful.