“I am new to agentic development, I’m building something, but I feel like I'm missing some tribal knowledge. Help me catch up!”. I’m temp

Six Principles for Production AI Agents

submited by
Style Pass
2025-07-28 16:30:05

“I am new to agentic development, I’m building something, but I feel like I'm missing some tribal knowledge. Help me catch up!”.

I’m tempted to suggest some serious stuff like multiweek courses (e.g. by HuggingFace or Berkeley), but not everyone is interested in that level of diving.

So I decided to gather six simple empirical learnings that helped me a lot during app.build development. This post is somewhat inspired by Design Decisions Behind app.build, but is generalized and aimed to be a quick guideline for newcomers in agentic engineering.

I’ve been skeptical about prompt engineering for a long time, it seemed more like shaman rituals rather than anything close to engineering. All those approaches “I will tip you $100” or “My grandmother is dying and needs this” or “Be 100% accurate or else” could be useful as local fluctuation leveraging local model inefficiency, but never worked in the longer run.

I changed my mind regarding prompt / context engineering when I realized a simple thing: modern LLMs just need direct detailed context, no tricks, but clarity and lack of contradictions. That’s it, no manipulation needed. Models are good at instruction following, and the problem is often just the ambiguous nature of the instructions.

Leave a Comment
Related Posts