AI coding agents that know your codebase.
Buda gives dev teams persistent AI coding agents for code review, PR analysis, repo research, documentation, and release notes — with context that builds across every commit.
Dev teams lose context every time the PR closes.
Reviewers read the diff, find the related issue, understand the change intent, and check for edge cases — none of which carries forward.
There is no agent that walks a new engineer through the repo, module boundaries, or relevant history.
Docs are written once, then ignored after every merge until engineers stop trusting them.
Summarizing commits, PRs, and resolved issues is recurring engineering tax.
AI coding agents that build on your codebase, not just assist one developer.
One AI engineering pod per repo
Each repo gets a shared agent workspace with code reviewer, repo researcher, doc writer, and test analyst agents — all sharing the same codebase context.
See capabilities
Code context persists across every commit
Buda stores PR history, issue context, architecture notes, and prior run outputs in a shared Drive. Agents continue from the last known state of the module.
Start with context
Reviewable output before it touches production
Every agent output is a structured artifact — review notes, PR summary, doc patch, release entry — approved before it reaches a reviewer or release tag.
See workflowsSix AI coding agents for the engineering team.
Buda gives engineering teams persistent agents for review prep, PR summaries, repo research, docs, tests, and release notes.
Code review agent
Reads the PR diff, related issues, and prior module context, then surfaces review notes, edge cases, and potential regressions for approval.
PR analysis and summary
Summarizes intent, scope, risk, and dependencies of any PR so reviewers spend less time parsing diffs and more time evaluating logic.
Repo research agent
Answers what a module does, where it is called, and what changed recently so engineers spend less time spelunking the codebase.
Documentation agent
Drafts and updates module docs, README sections, and API references from code changes, PR notes, and architecture decisions.
Test coverage analysis
Identifies untested paths in a PR, suggests test cases, and surfaces coverage gaps before code hits the review queue.
Release notes automation
Pulls merged PRs, resolved issues, and breaking changes into a structured draft release note for EM review.
Get your first AI coding workflow live in 30 minutes.
Pick one repo workflow, add real context, run the first artifact, and review before expanding.
Start with the engineering workflow that costs the most time per sprint.
Choose one repeated engineering workflow with clear inputs, a visible owner, and a reviewable output.
PR review prep
PR opens. Buda agents read the diff, related issue, prior review comments, and architecture context, then draft review notes and edge cases.
Start this workflowOnboarding new engineers
Agents answer repo questions, surface relevant history, summarize architectural decisions, and generate a starter guide before the first standup.
Onboard fasterRepo research and refactor planning
Agents map callsites, surface related PRs and issues, identify breakage points, and draft a phased refactor plan for review.
Plan refactorsRelease engineering
Agents pull merged PRs, resolved issues, and dependency changes into a categorized draft changelog ready for review and tagging.
Draft release notesPilot AI coding agents with your team in four weeks.
Start with one repo workflow, load real code and issue context, run on one PR or sprint, then expand after review.
Pick your first engineering workflow
Start with PR review prep, onboarding, repo research, docs, tests, or release notes.
Load repo and issue context
Add codebase files, PR history, issues, architecture notes, and prior review comments to the workspace.
Run on one real PR or sprint
Let agents produce review notes, a doc patch, test suggestions, or release notes for human review.
Expand to the full engineering team
Once the first workflow is trusted, add more repos, agents, and review owners.
Give your engineering team AI agents that know the codebase.
Run code review prep, PR summaries, repo research, docs, tests, and release notes in one persistent Buda workspace.