Building a global postal code API (240+ countries). Just shipped per-country landing pages with format references and regex patterns. $0.000028/query with no tiers, sub-5ms. Bootstrapped, solo.
Building a global postal code API (240+ countries). Just shipped per-country landing pages with format references and regex patterns. $0.000028/query with no tiers, sub-5ms. Bootstrapped, solo.
The insight that multi-agent coordination is fundamentally a type-checking problem — catch structural failures before spending the compute — is the most practical framing I've seen for this space. The adversarial composition example where information partitioning emerges from types rather than instructions is especially elegant. Looking forward to the follow-up on memory architecture.
With my type of development, I haven't run into the types of things, directly, that you very well explained, but I have personally run into the pain, I confess, of being OVERLY reliant on LLMs. I continue to try and learn from those hard lessons and develop a set of best practices in using AI to help me avoid those pain points in the future. This growing set of best practices is helping me a lot. The reason that I liked your article is because it confirmed some of those best practices that I have had to learn the hard way. Thanks!