Autonomous software delivery
From task to verified pull request
You assign a clearly described task. The agent completes it in a prepared, isolated environment, runs the tests, and checks the running application. Your team gets a pull request with verification evidence — and keeps the merge decision.
Example task run
- 0:00 Task assigned to the agent
- 0:05 Environment ready — dependencies, services, caches
- 5:12 Tests passed: 86/86
- 8:47 Running application verified
- 9:34 Pull request ready for review
The problem
An agent alone is not enough
Autonomous work on code pays off only when the environment, access boundaries, and verification are prepared as carefully as the model itself.
01
Cold starts burn time and context
Instead of implementing, the agent installs dependencies, repairs the toolchain, and boots services — spending its token budget before it touches the actual task.
02
Unverified code shifts the cost to your team
A fast implementation helps little if nobody ran the tests or the application before review. A person ends up doing that work — on their side, on their time.
03
Broad access is a real risk
Repository credentials and open network traffic should not enter a process that executes code and handles task input from outside.
≈2×
fewer tokens spent on the same task
≈4×
faster from task to a merge-ready pull request
Internal tests: identical tasks run in a prepared environment versus a cold start.
How it works
One task, a controlled process, a clear result
The unit of work is a task with a defined scope and acceptance criteria. The result is a pull request that goes through your team’s regular review process.
-
We connect the repository
We define the tools, the project startup procedure, the allowed integrations, and the checks that define “done”.
-
We prepare the execution environment
Dependencies, toolchains, services, and caches are built and validated before the agent starts. Every task begins with a running project, not an empty machine.
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The agent completes a bounded task
It reads the repository context, implements the change, and iterates on test results and the behavior of the running application. Secrets stay outside its process, and outbound traffic is filtered.
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Your team receives a reviewable change
The pull request contains the code, the check results, and an execution record. A person evaluates the solution and makes the final merge decision.
Principles
Speed comes from preparation, not skipped controls
A prepared environment
A validated agent workspace — dependencies, toolchains, and caches ready before the start, instead of rebuilding the workstation for every task.
Running-application verification
Beyond tests and static checks, the process validates key behaviors of the running system — not just whether the code compiles.
Credentials behind a broker
Secrets never enter the agent process. Services are reached through an intermediary layer whose permissions are limited to the task.
Filtered outbound traffic
Network connections are restricted to allowed destinations, closing off the risk of code and data exfiltration.
Your model, your rules
We match the model, instructions, and execution tools to your stack, risk profile, and organizational standards.
Merge stays with a human
Automation ends with a change ready for review. The deployment decision and accountability remain with your team.
Pilot
Let’s test it on a real task
We will pick a repository, set the access boundaries, and run a pilot on tasks whose outcome can be judged unambiguously. Your team’s review process stays unchanged.
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