From capture to expression
Every intent and decision flows into the AI genome. Only the relevant subset surfaces back to the current task.
The thesis
That assumption is wrong. LLMs degrade with context bloat — relevance dilutes, contradictions compound, attention thins, cost climbs.
Biology already solved this. No cell dumps its whole genome into every reaction. That's what Cursor rules do. That's what Memory MCP does. That's what most "context" tooling does today. Cells would die if they tried.
Kawa Code makes the opposite bet. We curate. We deprecate. We express only what matters, only when it matters. The way a cell expresses a gene.
Kawa Code: your project's full decision genome
— expressed only when it matters.
Every intent and decision flows into the AI genome. Only the relevant subset surfaces back to the current task.
Four pillars, working as one. Together they form the project's decision genome — and express it only where it matters.
Automatic instrumentation of decisions from communication channels, code, and AI conversations. The team doesn't write reasoning down — the system extracts it.
Structured types, evolution graph, deprecation. The decision layer prunes itself — instead of accumulating monotonically like every other AI-memory tool.
The technical moatRelevant decisions, surfaced at the right moment. Past reasoning appears at the moment of work — not when you remember to search for it.
Conflict and intersection detection across the team — before merge time, before architectural drift.
Other tools accumulate. Kawa Code curates.
Watch how Kawa Code captures development intent in real time — recording decisions as they happen during AI-assisted coding sessions.
No workflow disruption. No manual documentation. Just quiet, continuous memory.
Watch how Kawa Code helps Claude Code correctly identify the issue, instead of trying to fix the wrong part of the system.
Faster development, higher quality. No more back-and-forth on endless debug cycles.
See where teammates are working before changes are committed. Intersection detection highlights overlapping edits across your team — so you coordinate early, not at merge time.
All the code generated by AI or human contributors can be automatically translated into any human natural language, to make reading the code and validating logic available to anyone on the planet.
Kawa Code works as an MCP server for Claude Code, Cursor, and Windsurf.
Install kawa-intents and follow the setup instructions in the README. The MCP server provides intent tracking, decision recording, and context retrieval tools to your AI assistant.
npx @anthropic-ai/claude-code mcp add kawa-intents -- npx -y @anthropic-ai/claude-code-mcp kawa-intentsFor international teams, install kawa.i18n to translate code, intents, and decisions into your team's preferred languages.
Kawa Code follows a zero-knowledge architecture.
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