MartinLoop keeps the job focused, bounded, checked, and accountable — so you can stop babysitting agents and ship more.
Give it the job. Walk away.
Give it the job. MartinLoop watches the run.
One unattended run cost $65. The bigger cost was having to supervise everything.
Coding agents can write more software than ever. But if you still have to watch every move, check every claim, and clean up every bad loop, you did not really delegate the job.
The agent says yes. You still have to check everything.
One task quietly turns into changes you never asked for.
The loop keeps running even when progress has stopped.
A fix in one place can create three new problems somewhere else.
Retries keep spending while you wait for a useful result.
If the answer is no, the agent is still creating a management job for you.
The new bottleneck is trust. MartinLoop was built after a $65 overnight run showed us how costly constant supervision had become.
"My costs are going up three times every three months. My revenues are not. Everybody has gotten infatuated with Ralph Wiggum loops."
Benchmark results are task-specific, not a guarantee for every run.
Your coding agent still does the coding. MartinLoop keeps the work accountable while you do something else.
Set the scope, goal, budget and what success looks like.
Budget, iterations, time and path limits are agreed before the agent starts.
The coding agent — Claude Code, Codex, Gemini CLI or another — plans and acts.
Drift, runaway retries and runs that stop making sense are cut short.
Configured tests and evidence run before the result is accepted.
Enough state and evidence is preserved to retry, repair or hand off cleanly.
Every run ends as VERIFIED, STOPPED or NEEDS REVIEW, with the stop reason recorded.
The receipt shows what finished, what failed and what it cost.
Reliable agents should not need constant supervision.
MartinLoop keeps the job, attempts, checks, stop reason, recovery information, and cost together so you do not have to piece the story together from terminals, Git history, and billing dashboards.
One npm install. That's the whole setup.
Keep Claude Code, Codex, Gemini CLI, your IDE, Git workflow, CI, and the tools your team already trusts. MartinLoop handles the boundaries, checks, recovery, and run history around the job.
Native coding agents and OpenAI-compatible model endpoints use different execution paths. MartinLoop keeps the job, limits, checks, recovery, and history consistent without presenting raw model endpoints as finished autonomous coding workers.
When one agent becomes many agents and one repo becomes many repos, MartinLoop gives the team one place to see outcomes, failures, and spend.
Every agent run visualized. See where work is concentrated, where it stalls, and where you can cut.
Understand what types of problems your agents hit most — and how often each one gets resolved.
See cost by run, by task, by model — broken down in a way your team and leadership can actually act on.
A full record of every limit hit, every stopped run, and every outcome. Reviewable at any time.
The goal is not more control for its own sake. It is confidence to delegate more work.
The job, the limits, the verification, the recovery and the run record stay the same even when the agent or the model underneath changes. That is the point: you are not locking your process to one vendor's tooling.
Claude Code · Codex · Gemini CLI
The agent already knows how to work in your repo. MartinLoop runs the job around it — scope, limits, verification, stop reasons and a run record you can read afterwards.
Hosted and local endpoints
Available for compatible inference workflows. Full governed workspace editing on this path is being hardened before we promote it, so we do not claim it as a finished coding worker yet.
Same job contract. Different worker. How model-agnostic execution works →
Keep the coding agents, IDE, Git workflow, repository host, CI and specialist tools you already like. MartinLoop handles the work around the coding-agent job, so you do not have to rebuild the same glue around every agent.
MartinLoop Core is Apache 2.0 licensed and free to use. Hosted dashboard and team features are in early access. Get early access →
MartinLoop helps builders and teams give coding agents larger software jobs without supervising every step. It keeps the work focused, stops waste, checks the result, helps recover when things break, and shows what finished, what failed and what it cost. The coding agent still writes the code.
Built for builders, technical founders and engineering teams who want to delegate more real software work to agents without runaway cost, unchecked scope, or no record of what happened.
Read the MartinLoop FAQ · the complete guide to agent loops & Ralph loops · coding-agent reliability · open-source GitHub repository
Clear jobs. Hard boundaries. Checks. Recovery. Explicit outcomes.
Shared history, team visibility, and better understanding of where agents succeed or fail.
Bring the same accountability to other consequential AI work. Roadmap.
Next and Later are roadmap, not shipped. The model will change. The need to trust the work will not.
MartinLoop governs the run. Atlas records what happened. SANSA trace intelligence finds the evidence-backed pattern behind failures, retries and wasted spend. Governed learning turns repeated evidence into controlled improvement candidates.
The black box recorder for coding-agent runs, receipts, failures, spend and recovery.
Connects the trace into recurring failure patterns and evidence-backed explanations.
Surfaces evaluated improvement evidence with approval and rollback boundaries before behavior changes.
Join the early-access group for the hosted dashboard and team workflows.