Manual API docs are slow, outdated, and hated by devs. We built a multi-agent pipeline using Claude Code and open-source linters that auto-generates, validates, and publishes docs —
We tested Claude Code, Cursor, Copilot, Aider, and Cline on a real legacy Java project with tangled dependencies. Only one tool correctly refactored without introducing phantom logic. Here's the exact
I spent 3 weeks building a multi-agent orchestrator from scratch. Instead of writing every line by hand, I used AI coding tools. Here's the exact prompt engineering workflow, the failures,
I gave Claude Code and Cursor the same nasty legacy Node.js API to refactor. The results were shocking. Here's where the tools shine, where they fail, and the exact human-in-the-loop
AI coding tools aren't stupid—they're just context-starved. Here's how we fixed it with a Vietnamese team and a custom context engineering workflow that cut hallucinated code by 73%.
AI coding tools fail because they lack context. I built a custom Context Vault that feeds my agents the right project data. Here's the exact Python setup and the team
AI coding assistants can turn junior developers into passive code acceptors. Here's the data on skill atrophy — and the review-based training loop we use at ECOAAI to keep engineers
AI coding tools hallucinate bad code because they don't understand your project's conventions, patterns, and architecture. Here's how to build a lightweight context pipeline that turns any AI assistant into
I threw the same gnarly production bug at Cursor, Claude Code, Aider, and Codex CLI. The results were shocking. Here's exactly which agent fixed it without breaking anything else.
Every AI coding tool hallucinates when it lacks context. Here's the 3-step context engineering rule our Vietnamese team uses to stop AI-generated bugs before they hit production.
Forget synthetic benchmarks. We threw five popular AI coding tools at a real, nasty production bug. The results were shocking, and only one tool actually fixed the issue without breaking