Engineering 5 min read
Chatbot as Intent Classifier
No-code chatbot builders collapse under their own complexity—here's how treating messaging flows as intent classification problems makes them readable, testable, and scalable.
Mar 30, 2026
Dispatches on making AI actually useful—from the team building vocational training for language models.
No-code chatbot builders collapse under their own complexity—here's how treating messaging flows as intent classification problems makes them readable, testable, and scalable.
Generative AI struggles with design reuse and human-friendly output—templatizing conversations, taming UUIDs, and the liberation of delegating implementation.
Building an agentic task executor with browser automation—from local model orchestration to headless Playwright recordings reviewed via WhatsApp.
Not every service can be set up by an agent—wrestling with Meta's developer portal, managing secrets, and debugging a live LLM classifier in production logs.
Shipping to production without testing locally—how an AI agent handled Dockerfiles, database provisioning, and the case for personal apps over multi-tenant SaaS.
Exploring full agentic coding—starting a project where every line of code goes through an AI agent, from user research to first implementation.