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Infinite Agent Chains

connector.json has no limit on pipeline depth. Each phase’s output feeds the next. Agents chain indefinitely.

Linear Chain

10 phases. 5 different models. Each phase reads the previous phase’s output from scratchpad. Research () → Analysis ($$) → Plan ($$$) → Implement ($$$) → Test ($$) → Fix ($$$) → Review ($$) → Docs () → Changelog ($) → PR ($$). Cost-optimized: expensive models only where reasoning depth matters.

Fan-Out / Fan-In

Parallel workers that converge into a single synthesis.

Recursive Refinement

A chain that loops until quality criteria are met.
Opus drafts → Codex critiques → Opus refines → Codex critiques again → repeat until score ≥ 8 or 5 iterations. Two different AI models in an improvement loop. Each brings a different perspective. Neither is subordinate — they challenge each other.

Multi-LLM Assembly Line

Different AI for each stage, like a factory assembly line.
7 phases. 5 different AI models. Each chosen for what it does best. No single model could do this alone. The chain is stronger than any individual.

Why No Depth Limit?

Every other multi-agent system has practical limits:
  • Claude Teams: In-memory context. Dies when terminal closes.
  • Codex Plugin: Single subprocess call. One shot.
  • claude-squad: tmux sessions. Manual management.
connector.json has no limit because:
  1. Each phase is a fresh PTY session — no context accumulation
  2. Scratchpad is the memory — files on disk, not in-context tokens
  3. Daemon persists — phases can run for hours, days
  4. Sessions are independent — phase 7 doesn’t carry phase 1’s context weight
The scratchpad is the key. Instead of stuffing everything into one AI’s context window, each phase reads only what it needs from shared files. The chain can be 3 phases or 30 — the cost per phase stays constant.