Ideas Weave Every Narrative with AI.
Hyper-Markdown isn’t a new tool or a rival format. It’s a simple realization: your existing .md files are already valid .hmd files. Add wiki links and rich visuals when you want, and your flat notes become a living knowledge graph — without a single migration.
The biggest mistake in enterprise AI is treating LLMs as the brain of the system. They are the translator, not the decision-maker. Structured predictions need task-oriented models, deterministic constraints need rule engines, and complex relationships need knowledge graphs. Orchestration, not replacement, is the winning strategy.
Most AI coding agents leak your data or run wild on your system. Claw-coder is the first local agent that solves both: sandboxed Docker execution, local RAG, and a knowledge graph — all without sacrificing power. The real moat isn’t the model; it’s the orchestration layer that guarantees safety and privacy.
The boundary between a relation and an entity isn’t technical—it’s existential. Use six simple questions to decide whether to entity-ize a relationship in your knowledge graph. Avoid bloat and information loss by focusing on business lifecycle, not attribute count.
AI-generated PRDs look flawless in isolation but are dangerously blind to cross-module dependencies. The problem isn’t your prompt or context window—it’s that your product knowledge is a graveyard of documents that record changes but can’t reconstruct current reality. The real competitive advantage belongs to companies that build machine-readable product models where state, dependencies, and impact chains are always live.
LKML-reader takes the Linux Kernel Mailing List — the most important and most unreadable communication channel in open source — and makes it interactive, searchable, and navigable. Built in Rust, it reframes LKML from a chaotic archive into a queryable knowledge graph, lowering the barrier for new contributors who’ve been locked out by twenty years of unthreaded email noise.
I mapped 8.5 million research papers into an interactive WebGL atlas with LLM summaries, entity linking, and citation graphs. But the real value isn’t the visualization — it’s the MCP server that lets AI agents query the entire corpus. We’ve been so focused on helping humans read papers that we missed the bigger shift: agents that can navigate 8.5 million papers at once change what literature review even means.