In this article, we try to explore the collective thinking into a smaller set of practices and explain the reasoning behind each one, rather than asking anyone to memorize a numbered list.
I write about Deep System design,Engineering, tech, how to build things in tech at a deeper level, AI/ML inference, Benchmarks, LLMs and How to Quants, please checkout some of my posts ( more than 300000 reads) -
built a few agents for my digital products business and the loop pattern here is spot on — the ones that survived production were the ones where I kept the model's decision surface as small as possible. every time I let the model decide "what to do next" instead of just "which of these 3 things to do" it broke within a week.
Personally, these practices highlight an important reality, production AI agents are less about giving models autonomy and more about constraining that autonomy safely, at least in my experience. I found the difficult engineering work is in context management, state, observability, evaluation, and reliable stopping conditions, not in the prompt alone.
Nice one. Great to connect with you.
I write about Deep System design,Engineering, tech, how to build things in tech at a deeper level, AI/ML inference, Benchmarks, LLMs and How to Quants, please checkout some of my posts ( more than 300000 reads) -
https://howtosystemdesigneverything.substack.com/
https://aiinferenceandoptimizations.substack.com/
https://howtobuildtech.substack.com/
[Bookmark: 300000 Reads Top System Design] Weekly Round Up : https://howtosystemdesigneverything.substack.com/p/extended-50-off-discount-top-system?r=14q3sp&utm_campaign=post-expanded-share&utm_medium=web
https://howtosystemdesigneverything.substack.com/p/important-bookmark-shortest-system?r=14q3sp&utm_campaign=post-expanded-share&utm_medium=web
https://howtobuildtech.substack.com/p/how-to-build-tech-2-how-to-actually-c43?r=14q3sp&utm_campaign=post-expanded-share&utm_medium=web
https://aiinferenceandoptimizations.substack.com/p/important-ai-inference-pulse-4-kv?r=14q3sp
built a few agents for my digital products business and the loop pattern here is spot on — the ones that survived production were the ones where I kept the model's decision surface as small as possible. every time I let the model decide "what to do next" instead of just "which of these 3 things to do" it broke within a week.
Personally, these practices highlight an important reality, production AI agents are less about giving models autonomy and more about constraining that autonomy safely, at least in my experience. I found the difficult engineering work is in context management, state, observability, evaluation, and reliable stopping conditions, not in the prompt alone.