Trail Boss

You run a herd of AI coding agents like cattle, each grazing its own task. When one bogs down or strays — needs a decision, hits a permission gate, or finishes and waits for the next order — Trail Boss is the single pane where it reports in. You ride over, set it right (or wave it on), and your reply lands back in the exact session — so you stop hand-cycling terminal windows hunting for whoever's stuck.

Human on the loop, not in it

Trail Boss turns human-in-the-loop into human-on-the-loop. Classic agentic HITL wires you into the inner cycle — approving each step, answering each prompt — so you are the bottleneck on every iteration. Trail Boss flips it: agents run autonomously by default and you supervise from above, engaged only by exception. When an agent can't proceed on its own — needs a decision, hits a permission gate, or exhausts its turn — it falls through to you.

Put plainly, the human is the failure mode. Trail Boss is a dead-letter queue for a fleet of agents: the happy path never touches you; only stalled work routes to you, you process the exception (reply or skip), and it goes back on the wire. Instead of you polling many sessions to find the one that needs you, each stuck session raises its hand and Trail Boss presents them as one prioritized queue — most-stuck first. Read the context, give the order (reply), or wave it on (skip).

┌─ TRAIL BOSS ────────────────────────────────────────────── 3 stuck ───┐
│                                                                        │
│  ▶ api-gateway         PERMISSION   stuck 2m14s                        │
│      wants to run: terraform apply -target=module.lb                   │
│      [a]llow  [d]eny  [e]dit  [s]kip  [o]pen pane                       │
│  ──────────────────────────────────────────────────────────────────  │
│    search-index        PLAN         stuck 0m48s                        │
│      proposed plan: "Add incremental reindex on write…" (42 ln)        │
│  ──────────────────────────────────────────────────────────────────  │
│    docs-site           QUESTION     stuck 0m11s                        │
│      "Version the API reference per release, or keep one rolling page?"│
│                                                                        │
│  [tab] next   [enter] focus   reply ▸ ____________________________     │
└────────────────────────────────────────────────────────────────────────┘

Why

Long-form agentic coding runs many sessions in parallel, one per terminal window. Each periodically stalls waiting on a human:

• a permission prompt (run this command? edit this file?)
• a plan waiting for approval
• a clarifying question
• or it simply finished its turn and is idle, wanting the next instruction

Discovering those stalls by manually cycling windows is the bottleneck — with N sessions, most of your time goes to finding the one that needs you, not answering it, and a session can sit blocked for minutes while otherwise-parallel work waits. The human is the scarce resource; the system should route the human's attention, not the other way around — engaging you by exception, not on every step.

How it works

Each agent session emits a signal the moment it blocks, via Claude Code hooks — Stop (turn finished, idle, awaiting the next prompt) and PermissionRequest (a hard approval). A small always-on collector tracks every session's state, tails the transcript to extract what is being asked, and serves a single-pane queue ranked most-stuck-first. You answer or skip; your reply is delivered back into the exact session — via tmux send-keys (overlays a terminal workflow with no rewrite) or the Agent SDK's canUseTool / streaming input (a cleaner, programmatic substrate). Full design in docs/plan/plan.md.

Repository layout

• README.md — this file
• docs/plan/plan.md — the complete design: problem, capabilities, architecture, phases, open questions
• docs/research/claude-code-mechanics.md — the Claude Code primitives for detect / correlate / deliver
• docs/research/related-work.md — public prior art and how Trail Boss differs
• docs/notes/decisions.md — naming rationale and key design decisions

Status

Research / design. No implementation yet. The detection model is settled (Stop + PermissionRequest are the two load-bearing signals); the next step is the collector plus the session→pane registry.