Teams are generating more code faster with the help of AI but the way they review and maintain code is still stuck in the past. Review queues pile up as engineers can’t keep up with review demands and progress stalls while everyone waits for approvals.
Many existing tools were built for single agent, single developer use cases. We believe there is a better way that optimizes for team throughput.
Why multi-agent matters
A single agent is too general purpose to capture the nuances required to operate effectively in enterprise codebases. Just as teams have subject matter experts who specialize in parts of your code and systems deeply, we believe multiple specialized agents are needed to improve quality and speed of code changes in complex codebases.
Your agentic team – Gitar lets you create expert agents (security, dependency‑upgrades, framework migrations, style enforcement) and share them with your team for re-use. Expert agents keep their knowledge up-to-date as your codebase evolves.
AI native workflows – Every Gitar agent runs builds, tests, and custom checks before creating code changes. They respond to comments during review and iterate with your team. You can ask them in natural language to wake up and run on commits, on a schedule, or on other events to truly automate any kind of non-stop maintenance work.
Persistent memory – Gitar’s knowledge graph of your code grows with every run, so agents remember patterns, project conventions, and past decisions. You can chat with agents using natural language to help them change their behavior as your teams’ needs evolve or even ask them questions that they can answer from their experience.
Agent reviews for AI-native teams
Existing code review tools expect developers to sift through diff hunks line by line. This is not a scalable approach with agents generating more code everyday. Gitar lets you
Review agent actions, not just code. Inspect what the agent did and why, guided by context it surfaces automatically.
Ask questions directly. Ask your agents - “Why switch to this API?” or “Can you roll this into one commit?” Agents answer or revise instantly.
Iterate until it’s right. View and review your team’s agents and take over to iterate with them.
A quick look at our own numbers
As we ramped up our usage of Gitar on our own codebase, we measured the pace at which we hit every 1,000 pull requests:
PR #5000 → #6000 – 80 days (pre‑agents)
PR #6000 → #7000 – 44 days (early Gitar agents)
PR #7000 → #8000 – 15 days (full Expert agent rollout)
Every thousand PRs take roughly half the time! That’s 5x the throughput with the same team size and PR complexity. Our new bottleneck isn’t writing code, it’s reviewing all the clean, well‑tested changes our expert agents produce. We are able to review agents and work with them to ship changes at a pace unprecedented for a very small startup team.
We’re betting on an agentic future
Engineering teams are becoming AI-native and adopting agentic workflows. Developers are evolving to become Software Pilots and wielding multiple agents to scale themselves. We are building the platform of expert agents and agentic reviews to enable that future.
Gitar is the only agentic AI platform purpose built to learn, maintain and scale changes across enterprise teams and codebases. Gitar is built on the concepts of teams creating and reviewing expert agents tuned to specific parts of their codebase.
Ready to build your agentic team? Schedule a Demo
