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Loop Engineering

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GitHub stars loop-audit dogfood loop-audit npm loop-init npm loop-cost npm MIT Pages

Loop Engineering

Loop engineering is replacing yourself as the person who prompts the agent. You design the system that does it instead.

A loop is a recursive goal: you define a purpose and the AI iterates (often with sub-agents, verification, and external state) until the goal is complete or the loop decides to hand off to you.

Loop Engineering — Design the system that prompts your agents

→ cobusgreyling.github.io/loop-engineering
→ Read the Loop Engineering essay on Substack

Contents

Quick Links

Start here Description
Loop Engineering essay The concept, primitives, and Grok mapping — read this first
Pattern Picker Which loop to run first — start here if unsure
Primitives Matrix Grok vs Claude Code vs Codex — bookmark this
Loop Design Checklist Ship readiness rubric
Patterns 7 production patterns + interactive picker
Starters Clone-and-run kits (Grok, Claude Code, Codex)
loop-audit Loop Readiness Score CLI (v1.4 + activity detection) — npx @cobusgreyling/loop-audit . --suggest
loop-init Scaffold starters + budget/run-log (v1.2) — npx @cobusgreyling/loop-init . --pattern daily-triage --tool grok
loop-cost Token spend estimator — npx @cobusgreyling/loop-cost
Stories Real wins and honest failures

Why This Matters

Peter Steinberger:

“You shouldn’t be prompting coding agents anymore. You should be designing loops that prompt your agents.”

Boris Cherny (Head of Claude Code at Anthropic):

“I don’t prompt Claude anymore. I have loops running that prompt Claude and figuring out what to do. My job is to write loops.”

The leverage point has moved from crafting individual prompts to designing the control systems that orchestrate agents over time.

The Five Building Blocks + Memory

Primitive Job in the Loop
Automations / Scheduling Discovery + triage on a cadence
Worktrees Safe parallel execution
Skills Persistent project knowledge
Plugins & Connectors Reach into your real tools (MCP)
Sub-agents Maker / checker split
+ Memory / State Durable spine outside any conversation

Full detail: docs/primitives.md · Cross-tool matrix: docs/primitives-matrix.md

Visual Overview

The Five Building Blocks + Memory — Loop Engineering

Anatomy of a Loop (Mermaid)

flowchart LR
    A[Schedule / Automation] --> B[Triage Skill]
    B --> C[Read + Write STATE / Memory]
    C --> D[Isolated Worktree]
    D --> E[Implementer Sub-agent]
    E --> F[Verifier Sub-agent<br/>tests + gates]
    F --> G[MCP / Git / Tickets]
    G --> H{Human Gate?}
    H -->|safe / allowlisted| I[Commit / PR / Action]
    H -->|risky / ambiguous| J[Escalate to human<br/>with full context]
    I --> A
    J --> A
Loading

This reference repo now runs its own validate-patterns + audit workflows on every push/PR (see .github/workflows/). We also added LOOP.md describing the loops that will maintain it.

Patterns

Pattern Cadence Starter Week 1 Token cost
Daily Triage 1d–2h minimal-loop L1 report Low
PR Babysitter 5–15m pr-babysitter L1 watch High
CI Sweeper 5–15m ci-sweeper L2 cautious Very high
Dependency Sweeper 6h–1d dependency-sweeper L2 patch-only Medium
Changelog Drafter 1d or tag changelog-drafter L1 draft Low
Post-Merge Cleanup 1d–6h post-merge-cleanup L1 off-peak Low
Issue Triage 2h–1d minimal-loop L1 propose-only Low

Not sure which to pick? Try the interactive picker or pattern-picker.

Machine-readable index: patterns/registry.yaml (7 patterns)

Getting Started (5 minutes)

# 1. Scaffold a starter (or copy manually — see starters/)
npx @cobusgreyling/loop-init . --pattern daily-triage --tool grok

# 2. Estimate token spend for your cadence
npx @cobusgreyling/loop-cost --pattern daily-triage --level L1

# 3. Audit readiness (budget + run-log now scored)
npx @cobusgreyling/loop-audit . --suggest

# 4. See scores climb: empty → L1 → L2
bash scripts/before-after-demo.sh

# 5. Start report-only (Grok example)
/loop 1d Run loop-triage. Update STATE.md. No auto-fix in week one.

All three CLIs publish to npm from tagged releases — see docs/RELEASE.md. No clone required.

Develop from source (monorepo contributors):

cd tools/loop-init && npm ci && npm test && node dist/cli.js /path/to/project --pattern daily-triage --tool grok
cd tools/loop-audit && npm ci && npm test && node dist/cli.js /path/to/project --suggest
cd tools/loop-cost && npm ci && npm test && node dist/cli.js --pattern ci-sweeper --cadence 15m

Phased rollout: L1 report → L2 assisted fixes → L3 unattended — see loop-design-checklist.

Examples by Tool

Operating & Safety

Caveats

Loop engineering amplifies judgment — both good and bad.

  • Token costs can explode with sub-agents and long-running loops.
  • Verification is still on you. Unattended loops make unattended mistakes.
  • Comprehension debt grows faster unless you read what the loop ships.
  • Two people can run the same loop and get opposite results. The loop doesn't know. You do.

Addy Osmani:

“Build the loop. But build it like someone who intends to stay the engineer, not just the person who presses go.”

Contributing

Share production patterns, tool mappings, and failure stories. See CONTRIBUTING.md, adopters, and GitHub Discussions.

Sources

License

MIT


Practical, tool-aware reference for loop engineering — patterns you can clone, checklists you can ship against, and stories that include what broke.

Essay · Showcase · Cobus Greyling

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Practical reference and patterns for loop engineering, designing systems that prompt and orchestrate AI coding agents (inspired by Addy Osmani and Boris Cherny / Anthropic)

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