Ai

Structured AI agent teams with memory and coordination Most people interact with AI assistants one prompt at a time. I wanted to see what happens when you design a full development team of AI agents — each with a defined role, personality, diagnostic methodology, and persistent memory — and have them collaborate on real engineering work. The setup: Five specialized agents, each with a distinct archetype and working style: Leader — Delegation, scoping, planning. Operates through a 5-field briefing format and dual quality gates. Backend — Django/DRF/Postgres specialist with a diagnostic loop that has a hard stop: after 2 failed hypotheses, escalate instead of brute-forcing. Frontend — Next.js/TypeScript, 4-states rendering rule, and a QA checklist that runs before any PR. Designer — Full state specifications and a feasibility gate that forces consideration of edge cases before committing to designs. Security — 7-category Django-aware review that runs after every Backend or Frontend task, before the second quality gate. Memory architecture: ...

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Offline voice I/O for macOS A complete text-to-speech and speech-to-text system for macOS that runs entirely on-device. No cloud APIs, no subscriptions — just local AI models doing real work. The problem: I spend hours reading and writing text on screen. I wanted a way to have my Mac read anything to me with a single hotkey, and transcribe audio without sending data to external servers. What it does: Press ⌥S and whatever text you’ve selected (or copied) gets read aloud using Kokoro-82M, an 82-million parameter TTS model running locally on Apple Silicon. The system automatically detects whether the text is Portuguese or English and picks the right voice. Audio starts streaming in under a second — no temp files, no waiting for the full synthesis to finish. ...