
Sourcegraph Cody
The AI coding assistant that understands your entire codebase through global context and advanced RAG.

The Autonomous AI Software Engineer for High-Velocity Teams

Koder is a cutting-edge AI software engineering agent designed to function as an autonomous member of development teams. Unlike traditional autocomplete extensions, Koder operates at the repository level, utilizing advanced Retrieval-Augmented Generation (RAG) and large context windows to understand complex cross-file dependencies. By 2026, Koder has established itself as a leader in the 'Agentic Coding' market, capable of taking high-level requirements from Jira or Linear and transforming them into production-ready Pull Requests. Its technical architecture includes a sandboxed execution environment where it can autonomously run build scripts, execute test suites, and iterate on code until all checks pass. This 'test-verify-fix' loop ensures that the code submitted for human review is not just syntactically correct but functionally sound within the existing architecture. Koder is optimized for enterprise-scale repositories, offering deep integrations with GitHub, GitLab, and Bitbucket. Its market position is defined by its ability to drastically reduce technical debt and accelerate feature delivery by offloading routine maintenance and boilerplate tasks from senior engineers.
Koder is a cutting-edge AI software engineering agent designed to function as an autonomous member of development teams.
Explore all tools that specialize in generate unit tests. This domain focus ensures Koder delivers optimized results for this specific requirement.
Explore all tools that specialize in automated test creation. This domain focus ensures Koder delivers optimized results for this specific requirement.
Executes code in a containerized environment, captures error logs from failed tests, and feeds them back into the LLM for self-correction.
Creates a vector-based map of the entire codebase, including function signatures, dependencies, and call graphs.
Spawns specialized sub-agents for 'Research', 'Coding', and 'Review' to ensure high-quality output.
Generates unified diffs that respect the repository's specific linting and stylistic conventions (Prettier, ESLint, Black).
Directly parses natural language descriptions from issue trackers to derive a technical implementation plan.
Learns from human feedback on previous PRs to avoid making the same architectural mistakes in future tasks.
Automatically scans generated code for common vulnerabilities (OWASP Top 10) using static analysis before submission.
Sign up via Koder.ai using a professional GitHub or GitLab account.
Install the Koder GitHub App or OAuth application to your organization.
Select specific repositories for Koder to index and analyze.
Configure the 'koder.yaml' file in the repository root to define build commands and test paths.
Define 'Agent Guardrails' to limit the scope of files Koder can modify.
Sync your issue tracker (Jira/Linear) to allow Koder to read tickets.
Assign a 'koder' label to an existing issue to trigger the autonomous agent.
Review the 'Proposed Plan' generated by Koder in the issue comments.
Monitor the live execution logs as Koder runs tests in its sandbox.
Review and merge the generated Pull Request once all CI checks pass.
All Set
Ready to go
Verified feedback from other users.
"Highly praised for its ability to handle complex multi-file changes, though sometimes requires manual intervention for very large architectural shifts."
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