Published lab notes only.
KyaniteLabs publishes notes after there is a real build, lesson, product, or workflow to explain. The blog covers open-source AI tools, MCP systems, agentic media, developer learning, implementation notes, and the work behind the proof.
The useful agent pattern is not a prettier prompt. It is a tool surface the agent can call, inspect, verify, and revise.
Repo history is a product signalA repo is not just storage. It is evidence of decisions, repairs, release behavior, naming drift, test gaps, and what the builder actually knows how to finish.
Implementation help is part of the product surfaceA useful open-source tool still needs a path from public repo to working environment. That path is product work, not an afterthought.
Why mcp-video mattersmcp-video is a video editing MCP server that gives AI agents direct handles on timelines, effects, FFmpeg, and finished media.
Infinite monkeys, LLMs, and the room around the machineThe argument behind the video: output quality is not just probability. It is architecture, filters, and human taste.
What a working AI tool needs before people can use itA practical checklist for turning a working tool, workflow, or rough app into something other people can understand, install, and use.
MCP server implementation checklistThe checklist Kyanite uses to decide whether an MCP server is a toy, a usable tool, or something worth implementing.
Repo archaeology turns history into proofWhy commit history is one of the strongest proof sources for learning diagnostics, implementation help, and engineering trust.
AI discovery needs more than a sitemapWhat Kyanite adds so search engines and AI assistants can understand the tools, products, proof, and support path.
The repos are proof before the pitch.
Public repositories show what Kyanite builds, learns, breaks, fixes, and releases. The paid path helps people get those tools working in real environments.
