Tune AI agents to write production-grade code
Claude Code / Cursor / Codex / Cline — wired with memory, hooks, MCP and a feedback loop that catches the bad output before you do.
Most teams use coding agents at 10 % of their capability — no memory, no hooks, no project rules, no verification loop. I set up the same stack that runs on my own machine: total-agent-memory for cross-session knowledge, a2abridge for multi-agent coordination, CLAUDE.md / .cursorrules with real architecture rules, hooks that gate edits, and a feedback loop (tests/build/lint) that runs after every change.
What you get
- MCP servers wired in: total-agent-memory (persistent knowledge), filesystem, A2A bridge.
- CLAUDE.md / .cursorrules / AGENTS.md with real architecture, code-quality and git rules.
- Hooks: pre-edit guards, post-edit lint/test, memory_save reminders, no-stub enforcement.
- Multi-agent setup: Claude + Codex / DeepSeek / local Llama via AISWARM-style orchestration.
- Feedback loop: tests + build + lint + grep on every change; agent never reports "DONE" on red.
- Hand-over: written playbook for your team, plus a 1-hour walkthrough call.
Stack
- Claude Code
- Cursor
- Codex
- MCP
- total-agent-memory
- a2abridge
- AISWARM
Process
Email or a 20-min intro call → written proposal → contract → ship.