Building tools that extend what AI can understand, remember, create, and accomplish.

I explore the systems around AI agents - context, memory, knowledge, tools, workflows, verification - so they become capable collaborators instead of confident guessers.

🧠 Understand - structured, grounded knowledge instead of whatever's in the weights. RAGprovenancestructured data

🗂️ Remember - context that survives the session, the project, the agent. persistent contextstateGit-backed workflows

🤖 Act - the tooling that lets an agent actually get things done. orchestrationMCPautomation

🔍 Verify - measure what happened, don't trust the summary. validationobservabilitydeterministic checks

cdx-manager - orchestration for AI coding agents: isolated environments, sessions, quotas, context handoffs, machine-readable output. One workflow → Multiple agents → Shared context

logics-manager - persistent context and structured workflows for AI-assisted development. A local-first runtime turning ideas into traceable work. Context → Plan → Task → Implementation → Verification

electrical-plan-editor - local-first workspace for designing, validating and exporting electrical plans. Complex domain → Structured model → Validation → Output

meshanvil - lets AI operate on 3D applications while producing measurable evidence of what actually happened. Operate → Measure → Prove

deepvault - governed knowledge sources for AI, with provenance, permissions and evidence preserved. Knowledge → Retrieval → Reasoning → Evidence

day-captain - Microsoft 365 mail and calendar turned into actionable daily intelligence. Deterministic where it matters → Intelligent where it helps

Building the tools that make AI better at building things.