STEP 01
Connect Your Repo
Link your GitHub, GitLab, or Bitbucket repository. We analyze your codebase structure and tech stack in minutes.
Deploy autonomous coding agents that maintain, build, and architect your codebase perpetually.
Try free with 5 included credits. Starter is $49/month with 50 included credits and automatic additional usage controls.
These agents are not ordinary tools - they operate like an elite background engineering team, shipping code continuously while your humans stay focused on strategy and product velocity.
Agents pick up tasks, write code, open PRs, and iterate - without waiting for you to prompt them.
Watch their work in real-time. Step in when you want to steer direction, or just review the output.
Agents integrate into your existing workflow - same repo, same CI, same review process. Just more throughput.
Everything you need to deploy, manage, and scale your AI engineering workforce.
Agents continuously scan your codebase for linting errors, security vulnerabilities, and outdated dependencies.
Every change goes through automated review. Tests run, types check, and code style is enforced before opening a pull request.
Agents scale up during sprints and scale down when idle. Pay only for the compute hours you actually use.
Agents run in isolated sandboxes with least-privilege access.
Define custom agent behaviors with simple configs. Chain agents together for complex multi-step workflows.
Connect Linear, Jira, or GitHub Issues. Agents pick up tickets, write code, and open pull requests autonomously.
No complex setup. Just connect and deploy.
STEP 01
Link your GitHub, GitLab, or Bitbucket repository. We analyze your codebase structure and tech stack in minutes.
STEP 02
Choose which agents to deploy. Set permissions, define workflows, and customize behavior with simple configs.
STEP 03
Agents start working immediately. Review their PRs, approve changes, and watch your velocity multiply overnight.
This is nocode AI engineering. Guide them with plain English, or just let them run completely free. They carry zero human limitations - no ego, no burnout, no vacation days, no 9-to-5. Just relentless, high-quality engineering output around the clock.
Open Weight by Default
We route to current open-weight coding models like gpt-oss, Qwen, DeepSeek, and Kimi out of the box - keeping quality high and runtime economics disciplined.
Need more horsepower? Enterprise teams can use approved custom or frontier routes.
You are not buying abstract seats or confusing hourly worker slots. You choose the agent tier that should do the work, decide when it is allowed to run, and included monthly credits are used only while it is active.
Try the product with a Junior agent and one background run at a time.
The core self-serve plan for background engineering coverage on autopilot.
For larger teams, higher concurrency, and custom governance.
The same monthly credit pool stretches farther on Junior work and compresses exponentially as you move up to Feature and Architecture runs.
Usage while the agent is actively working.
Usage while the agent is actively working.
Usage while the agent is actively working.
Join the most efficient engineering teams shipping faster with autonomous AI agents. Start free, scale as you grow.
FAQ
Practical answers about how ConstantCoder fits into your repo, review process, and usage controls.
ConstantCoder deploys autonomous coding agents that can maintain, build, and architect software in the background. They pick up defined work, make code changes, and produce pull requests for review.
Connect your repository, choose the agent tier and permissions, then let agents work inside your existing development flow. They use the same repo, CI, and review process your team already relies on.
The default workflow keeps humans in the review loop. Agents prepare changes and open pull requests, while your team keeps control over approvals, merges, and production releases.
Credits are consumed while agents are actively working. Junior work uses the fewest credits, Feature work uses more, and Architecture work uses the most because it is reserved for higher-complexity tasks.
Yes. Agents can be configured around your workflow, concurrency limits, and monthly usage caps so background work stays predictable.
Agents run in isolated sandboxes with least-privilege access. ConstantCoder uses open-weight models by default and can be configured for local or OpenRouter-compatible models when you need different model behavior.
ConstantCoder is currently in private beta. Join the waitlist to get early access and help shape the rollout for real engineering teams.