Use case
AI software development companies juggling many repos
Agencies and dev shops switch between client repos all day, each with its own stack and standards. Agentcode does the context-switching for you.
Last updated: August 2026
No card to start · Review-first: the agent never merges
In short
Agentcode is an autonomous AI coding agent that helps agencies and AI software development companies work across many client repositories. You describe a task in any client project, and the agent plans it, edits that codebase, runs that project's tests, and opens a pull request your team reviews and merges. It is review-first and never merges on its own, so every client change is approved by a human first. It works on each client's existing GitHub or GitLab repo and CI, and it never trains on your code.
The problem
You jump between client repos all day, and reloading the context of each one burns hours you cannot bill.
How Agentcode helps
Run Agentcode against each client repository it has access to and let it absorb the context for you. For a task in any project it plans the change, edits the right files, runs that project's test suite, and opens a pull request that fits that client's conventions. Your engineers review and merge, keeping ownership of quality across every account. You move faster on more projects at once without ever letting an unreviewed change land in a client's codebase.
What the agent brings to this work
See it run
From task to pull request
Pick a task
Plan
- planning
Files changed
Test run
Pull request
You review and merge. Agentcode never merges on its own.
Questions teams ask
How do AI software development companies use coding agents?
Agencies and dev shops use coding agents to clear well-scoped client tickets faster: the agent drafts the change, runs the tests, and opens a pull request that a developer reviews before it reaches the client. Agentcode fits this because it works on the client's own GitHub or GitLab repo and keeps a human on every merge.
Can an agency deliver client work with an AI coding agent?
Yes, as long as review stays with your engineers. The agent handles implementation and testing and returns a reviewable PR, and your team approves and merges, so deliverable quality is still owned by a person. That keeps agency accountability intact while cutting the time spent on routine build tasks.
Does client code stay private with an AI coding agent?
With the right vendor, yes. Agentcode never trains on your code and works within your repository's access controls, which matters when the code belongs to a client. Always confirm a tool's data-handling and training policy before connecting a client repo, since that varies by vendor.
How does an agency bill for AI-assisted development?
Most agencies keep billing the client for scoped outcomes and treat the agent as a cost of delivery. A flat tool price makes that clean: Agentcode is $29 a month with no meter, so the tool cost is fixed and predictable rather than a variable token bill that has to be reconciled per project.
Last updated: August 2026
Further reading
Client work raises questions a single-repo team never hits. Running an agent across multiple repos covers the practical side of switching between codebases, and whether AI coding agents keep your code private is the answer you will need when a client asks. If clients run GitLab, agents and GitLab covers host support.