Projects
Agent infrastructure, in the open
Four open-source pieces of the same thesis: the agent loop — not the model — is what makes an agent useful. Runtimes, SDKs, and control layers, published and in daily use.
01
Agent infrastructure
negotium
TypeScript · 2026 — Present
Host-agnostic multi-agent runtime
- Turns a single machine into a durable multi-agent node, running Claude Code, Codex, and Maestro backends with provider-native sessions preserved across turns.
- Generalizes Clawgram's orchestration into a reusable core — composable modules and local-first encrypted state behind a single adapter boundary, so new hosts plug into the same runtime.
TypeScriptBunSQLiteMCPmaestro-agent-sdk
TypeScript · 2026 — Present
Embeddable TypeScript agent SDK
- A composable agent SDK that reaches Claude Code-level agentic coding performance on non-Anthropic backends (DeepSeek, Kimi) — evidence that the agent loop, not the model, is the differentiator.
- Sessions, memory compaction, MCP tools, guardrails, and subagent delegation are independently composable behind one streaming interface.
TypeScriptESMMCPBun/Nodeclawgram
TypeScript · 2025 — Present
Telegram control layer for Claude Code
- In daily use by practicing lawyers on real case work. Private Mode masks PII with a pre-LLM hook before any prompt reaches the model, then unmasks on the response — confidential documents never leave the device unredacted.
- A multi-tenant orchestration layer maps Telegram forum topics to persistent, isolated Claude Code sessions, with MCP primitives that let sessions exchange context and delegate asynchronously.
TypeScriptBunFastAPIMCPPlaywrightbrowser-rs-mcp
Rust · 2026 — Present
Stealth-first browser automation over MCP
- A high-performance browser automation server in Rust exposed only via MCP — a ~5MB single binary alternative to Node-based automation stacks.
- Chrome DevTools Protocol client and browser engine written from scratch (ab-cdp, ab-browser, ab-mcp), with multi-tenant tab ownership so many MCP clients share one browser process safely.
RustCDPMCP
Classical ML implemented from scratch — Gaussian EM, Gaussian processes, HMMs, Fisher LDA, mixture density networks, matrix factorization, PCA, probabilistic graphical models, and restricted Boltzmann machines.