Summary
KodHau launched as an MCP-based context layer that feeds architecture decisions, constraints, and tribal knowledge into AI agents before they act. The product is designed to stop agents from writing locally plausible code that ignores undocumented team rules.
What changed
KodHau launched its public MCP product for injecting team decisions, design constraints, and review context into AI agents at run time.
Why it matters
A growing share of agent failures comes from missing organizational context rather than model weakness. Products like KodHau are betting that governed context injection becomes a durable control layer for production coding agents.
Evidence excerpt
KodHau says it injects architecture decisions, constraints, rejected approaches, and review comments into AI agents before they write code.