Technology
Agents that know your codebase
Repository-synced test generation, UAT coverage, and coding agents. Retrieval at method and class level, not character counts.
The problem
Generic code assistance ignores your code
The suggestion is syntactically correct and wrong for your project. It invents a helper you don't have, ignores your service layer, and uses a pattern the team abandoned two years ago.
Adding naive RAG doesn't fix it — character-based chunking cuts a method in half, so the model gets a function body with no signature. Enough to rank well in a vector search, not enough to write correct code against.
Three solutions
What engineering teams build
All three read the same repository memory, so a convention learned by one is available to the others. Pick the one closest to where your team loses the most time.
Code tester
Stays in sync with the repository and generates or updates test cases as code changes. Knows your existing test conventions, your fixtures, and which paths already have coverage.
UAT generation
Generates and maintains user acceptance cases from the code and the requirements behind it. When a feature changes, the affected UAT cases are updated rather than silently going stale.
Coding agent
A full agent that reads the repo, retrieves at method level, and writes code consistent with how your project actually works. Transactional memory writes mean a failed refactor pass rolls back cleanly.
Why it works here
Structure-aware from the ground up
Tree-sitter parses the repository at class and method boundaries, so retrieved code arrives whole. The knowledge graph tracks what calls what, so an agent can retrieve a function and then walk to its callers before changing a signature.
Past review comments persist as memory. A pattern a reviewer rejected in March is retrievable context in September, rather than a lesson only one person remembers.