Agentic Dev
Pillar 3
The Execution Layer

Deterministic Engineering
Triage Loop

Automate issue triage, parallel execution worktrees, self-healing rebases, and multi-agent review verification. Seamlessly matching autonomous developer throughput to human approval bandwidth.

Pillar 01 — The Operating Model

agentic-enterprise

The repository-backed operating model: governance layers, process loops, policies, and templates. Humans decide, agents execute, Git governs.

Pillar 02 — The Knowledge Layer

agentic-kb

The layered, vendor-neutral knowledge-ops spec with the /kb command — keeps humans and agents on the same page.

Pillar 03 — The Execution Layer

agentic-dev

The production-ready engineering loop that schedules tasks, resolves rebase conflicts, and verifies code via tests.

The Challenge & The Solution

Scaling multi-agent developer squads without overwhelming human managers.

PR Backlog Flooding

Without limits, agents work on all open backlog items concurrently, opening dozens of PRs that quickly overwhelm review pipelines and lead to stale code.

Context & Rebase Rot

Main branches move forward, leaving agent-authored PRs out-of-date or conflicting. Resolving this manually wastes developer cycles.

Rate Limit Exhaustion

Running isolated agents on complex dispatches causes heavy API utilization, causing rate limits that crash execution tasks without a fallback chain.

Backpressure Flow Control

Enforces configurable limits (e.g. `open_pr_cap_per_repo`) so agents stop creating new PRs once the human review queue is full.

Self-Healing Fast-Rebase

Automatically detects PRs behind base branches, attempts clean Git rebases first, and falls back to LLM models to resolve conflicts safely.

Multi-Agent Fallback Chain

Configures custom CLI pipelines (e.g. Codex -> Claude -> AGY SDK) that smoothly cascade to next models if one hits context or rate limits.

Engineered for Production Ops

Designed to operate continuously and safely in background servers.

Deterministic Triage Scanner

Uses local Git and GitHub REST APIs via `detect.py` to identify pending actions. By executing zero LLM calls during scanning, it minimizes token costs and runs instantly every minute.

Parallel Worktree Isolation

Dispatches individual issues to transient systemd service units. Each runner checks out code in an isolated git worktree, preventing workspace pollution and enabling parallel builds.

Test-Gate Verification

Enforces local test and linter execution prior to declaring work complete. If tests fail or code style drops, the issue is kept in progress for fixing or returned to the backlog.

Atomic Claim Locking

Maintains persistent lock files under the state directory. Prevents duplicate dispatches on the same issue across overlapping tick runs while releasing locks automatically on task exit.

The Path to Autonomy

How to incrementally introduce agentic development to your repositories.

1

Dry Run & Auditing

Configure `TRIAGE_ENABLE_DISPATCH=0` in the service. The scanner will run and log planned actions, locks, and concurrency checks to let you inspect the loop's behavior risk-free.

2

Collaborative Engineering

Enable dispatches, but keep `automerge=false`. The agents will pick up issues assigned to them, open PRs, run code reviews, and write suggestions, but a human retains merge rights.

3

Automated Operations

Enable `automerge=true` for specific repositories. PRs that are successfully authored, pass CI tests, and receive green reviews from verification agents are merged automatically.