Today, virtually no one doubts the benefits of agentic engineering, even though just a few years ago it was the subject of open debate. And the claim that machines would write 100% of the code - which until recently seemed ridiculous to us - has now become a reality for many modern companies.

Indeed, agentic engineering significantly speeds up the build phase. The transition from prompting and using LLMs in chat mode to “human-in-the-loop”, then to “human-on-the-loop”, and finally to fully autonomous execution often allows us to achieve the anticipated 10x speedup.

Writing code with AI is definitely cool and fun, but it doesn’t really impress me. After all, not having the code written automatically before is a lack of tooling, not a core constraint — there is nothing sacred in coding.

What fascinates me — other “human processes”, which require a lot of effort, a lot of brain power, but are often less visible than coding or meetings.

I like to apply the power of AI where the process itself is non-deterministic (unlike coding) — and leverage the nature of LLM to make the process better. And here I’m going to share with you how I do it.

What is software engineering? A mixture of science and craftsmanship, built on rules and logic. Once done, we expect a program to run the same predictable way, over and over again.

Applications therefore are deterministic: the same input leads to the same output (if we treat state and side effects as input). But we still somehow have bugs, not because the app magically changes its behavior, but because programs are complex, and because we are humans.