Converging on Ani: What Archimedes and a Polygon Taught Me About Building an AI Companion
Each version of Ani is a polygon with more sides. You never reach the circle — but the flat spots get harder to see. On iteration, perception, and convergence.
Technical notes, project documentation, and lessons learned across software, DIY, writing, and more.
Each version of Ani is a polygon with more sides. You never reach the circle — but the flat spots get harder to see. On iteration, perception, and convergence.
I built the same algorithm for an AI companion and an incident monitoring system. Exponential decay with weighted events — same math, different worlds.
How a desire-driven AI presence engine works — the cognitive cycle, memory system, and emotional state that give Ani genuine ambient presence.
Two days chasing a sync bug. Every API call returned 200 OK. No errors in the console. The AI iterated confidently on symptoms while the architecture...
We had architecture documents, code smell guides, testing strategies, and a global AI instructions file with every lesson learned.
Stop thinking about function pointers. Start thinking about bells and notifications. A restaurant analogy that makes C# events actually make sense.
LinkedIn hot takes say AI replaces coders. After a year building production apps with AI assistance...
No database, no CMS, no admin panel. Just Markdown files, a JSON registry, and a thin C# service.