For engineering teams shipping with AI

AI writes the code. Coderbuds closes the loop.

Your standards inside the coding agents, every change kept moving in Slack, and proof of what improved. One loop, from prompt to production.

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Code stays in your repo
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In your coding agent

Your standards load into every session, before the code is written.

In Slack

Every change kept moving — reviews chased, deploys one click, with your approval.

In your dashboard

Engineering intelligence — trends and receipts that prove what improved.

What's proven feeds the next agent session — the loop compounds.

See a real loop, step by step
Integrates with
GitHub
Bitbucket
Jira
Linear
Slack
Teams
Claude Code, Cursor & any MCP agent

The idea

Agents are only as good as the box you give them.

Engineers already know this. You don't make a coding agent reliable by prompting harder — you make it reliable by shrinking the surface area it can get wrong: tests it has to pass, linting it has to satisfy, CI it can't skip. Inside a well-drawn box, agents are brilliant. Leave a hole, and they'll find it.

But that box ends at one repo and one session. Coderbuds draws a bigger one — your team's box: how big a change should be, how fast reviews happen, what ships when — and carries it into every agent session, every pull request, every deploy, for every person on the team.

That's the box the loop keeps tightening.

Your team's box · Coderbuds

What you already do — one repo, one session

Tests pass Lint clean CI green Types check Agent rules file

What Coderbuds adds — every repo, every session, every person

PRs sized to ship fast Reviews within 24h Merged means deployed Standards in every session Proof it's working

The inner box keeps one agent honest. The outer box keeps a whole team — human and AI — shipping the same way.

The new bottleneck

AI didn't speed up your delivery. It moved the bottleneck.

Coding agents multiplied the code your team produces. Everything after the prompt — review, standards, deploys, knowing what actually shipped — stayed human-sized. That gap is where AI speed quietly dies, and from inside the team it's almost impossible to see. These are the three holes in the box that agents keep finding:

More code, same review capacity
Agents open pull requests faster than humans can review them. Your pace is no longer set by how fast code gets written — it's set by the queue behind it.
Standards don't survive the session
Every agent session starts from zero. Your conventions live in review comments and your head — exactly where agents never look. The 1,200-line PR wasn't malice; nobody told the agent your rules.
Nobody can prove it's working
Leadership asks whether the AI bet is paying off. You have anecdotes and a feeling. "We ship more" isn't an answer when nobody can say what changed, by how much, or why.

"Won't the next model just fix this?"

No — because it isn't a model problem.

A model optimizes one session. Your delivery runs across hundreds of sessions, several humans, a review queue, and a deploy pipeline. What's missing isn't more intelligence — it's memory, shared standards, and follow-through between the sessions. That's a system around the model, and no model upgrade ships it.

Coderbuds is that system: a loop that carries what your team learned into every new prompt.

How it works

One loop, from prompt to production

Coderbuds runs the delivery loop around your coding agents: set the standard inside the agent, keep every change moving in Slack, prove what improved — and feed the proof back into the next prompt.

Set the standard

inside the agent

Keep it moving

in Slack

Prove it

with receipts

Feed it back

loop closed

Step 4 flows back into step 1 — every loop starts tighter than the last.

1 · Set the standard

Your rules load into every agent session

Coderbuds connects to Claude Code, Cursor, or any coding agent your team uses. Each session starts with your team's box — how big a change should be, how fast reviews really happen, what the queue looks like right now. Before a pull request is opened, the change is checked against how your team actually ships.

  • Works with any coding agent your developers already run
  • Opinionated defaults from day one, tuned by your team's real history
  • One toggle — no thresholds to tune, no settings farm
~/app — your coding agent

› Add usage-based billing to checkout

⚙ Coderbuds · work-our-way

Your team's box: PRs under 400 lines · reviews within 24h

Queue right now: 4 open PRs, 2 awaiting review

✻ Change drafted — 645 lines across 12 files

⚙ Coderbuds · assess-change-fit

verdict: caution — over your 400-line standard

Changes this size take your team ~5× longer to merge

✂ Splitting into 2 focused pull requests…

2 · Keep it moving

Your daily pulse, where the team already lives

Opened, reviewed, merged, deployed — the day's flow lands in Slack as it happens. Reviews that stall get chased. Merged work that hasn't shipped gets flagged. Deploys are one click — behind your approval, not instead of it.

And it's a conversation, not a feed: ask @Coderbuds how the sprint is going, why it flagged something, or what to do about it — right in the thread.

# engineering Connected

Coderbuds APP

🔔 turing/web #1016: Strip 4-byte characters from search terms by @maria

11:31

👀 #1012 has waited 26h for review — reminder sent to @sam

13:02

📦 turing/api — 3 pull requests ready to deploy

16:25

Merged to main and awaiting a production deployment.

Deploy now Ask why
@Coderbuds how's our lead time this sprint?

3 · Prove it

Receipts, not vibes

Every intervention is tracked to an outcome and reported in plain language — what Coderbuds did, what happened next, and how it compares to your team's baseline. When leadership asks whether the AI bet is paying off, you read the receipt instead of guessing.

Underneath, everything is measured with DORA and SPACE — the frameworks from Google's DevOps research and Microsoft Research. You get the rigor; your standup gets plain English.

Explore the live demo dashboard
This month's receipts Proven
🪓 A 645-line change was split after a caution verdict → PR #808 (179 lines) merged in 2h.
👀 Review nudge on #1012 → reviewed 3h later against a 26h wait.
🚀 4 merged PRs flagged as undeployed on Friday → shipped the same day.

Median PR size

612 → 240 lines

Time to merge

40h → 8h

4 · Feed it back

The loop closes — and compounds

Standards that prove out are loaded into the very next agent session, automatically. Your team's way of shipping stops evaporating between prompts and starts compounding — every loop starts tighter than the last.

— next session, any developer, any agent —

⚙ Coderbuds · work-our-way

Your team's box: PRs under 400 lines (proven: merges 5× faster)

The standard travels with the work.

Where it lives

Three surfaces. One loop.

No new tab to remember. Coderbuds shows up inside the tools your team already lives in — and keeps a dashboard for the days you want to go deep.

In your coding agent

Claude Code, Cursor, Copilot — any agent your developers run. Standards load at the start of the session; changes get a fit verdict before the PR opens.

Connects in one click, per developer.

In Slack

The daily pulse, deploy buttons, approvals, and a coach you can ask anything. Coderbuds proposes; you decide — until it has earned the autonomy not to ask.

Microsoft Teams supported too.

In the dashboard

Depth when you want it: delivery trends, team health, every receipt — built on the DORA and SPACE research so the numbers hold up in any room.

Poke around the live demo

Picture this: 6 months from now

You walk into the board meeting with a single slide. DORA Elite status. Lead time down 75%. Deployments up 20x. AI agents did the work — you have the proof.

That's exactly what Patchstack did

From Guessing to Elite in 6 Months

Security Platform • 12 Engineers
GitHub & BitBucket

Lead Time

~4 days

Before

~1 day

75% faster

Deploys

Bi-weekly

Stressful

Daily

20x more

DORA

None

Guessing

Elite

Top tier

Dave Jong
"Now I walk into leadership meetings with data, not guesswork — and the team finally knows what 'good' looks like."

Dave Jong

CTO, Patchstack

Get the Same Results Read How They Did It

No credit card • No sales call • Results in 5 minutes

Engineering Intelligence

From the Blog

Actionable insights on DORA metrics, code review, and engineering team performance.

Engineering

From Code Reviews to AI Agents: We Didn't Plan This. Nobody Did.

We started as a peer code review tool. Now we ship autonomous AI agents that run engineering teams. Here's the messy, honest story of how the job of building software changed underneath us — and what it tells you about what's coming next.

Coderbuds Team
View all posts

Frequently asked questions

What is the SPACE Framework?
SPACE is a research framework developed by Microsoft Research, Google, and the University of Victoria that measures 5 dimensions of productivity: Satisfaction & Well-being, Performance (DORA metrics), Activity (work output), Communication & Collaboration, and Efficiency & Flow. It provides a holistic view beyond just code output.
Are you just another DORA dashboard?
No. Dashboards show problems — agents fix them. Coderbuds tracks all 5 SPACE dimensions (Satisfaction, Performance, Activity, Collaboration, Efficiency) and pairs each with AI agents that take action. Review Chaser improves turnaround. PR Size Coach reduces PR bloat. Outcome tracking proves what worked.
How do you measure developer satisfaction?
We use anonymous weekly pulse surveys (3 questions, ~1 minute) and monthly deep dive surveys (15 questions, ~5 minutes) to track happiness, focus time, collaboration quality, tools satisfaction, and growth opportunities. Team leads only see aggregated team-level scores to protect individual privacy and encourage honest feedback.
Why measure multiple dimensions instead of just velocity?
Single metrics can be gamed. If you only track PRs shipped, teams create tiny PRs. If you only track deployments, quality suffers. SPACE's 5 dimensions create a balanced scorecard—you can't optimize one without the others staying healthy. It's how elite teams maintain sustainable performance.
How quickly can I see results?
Within 5 minutes of connecting your repositories. Trial users get 30 days of historical data imported and analyzed. Subscribers get 6 months of history for deeper trend analysis.
Do you store our code?
Never. We only store metadata — timestamps, PR titles, and statistics. Your source code stays in GitHub or Bitbucket.
What makes Coderbuds different from LinearB or Swarmia?
AI agents that don't just show you metrics — they act on them. Review Chaser nudges slow reviewers, PR Size Coach suggests splits, Deploy Health responds to failures. Every agent tracks outcomes so you can prove what worked. Built for 5–50 person teams with transparent pricing and no implementation project.
How does Coderbuds help engineering leaders?
AI agents handle improvement at scale — chasing slow reviewers, flagging oversized PRs, and responding to deployment failures. You enable an agent, it takes action, and outcome tracking proves whether things improved. Leaders get measurable results without micromanaging.
More questions? See all FAQs

One Plan. Everything Included.

Start free. Upgrade when you trust the agents.

AI agents that improve your team

Enable agents that fix bottlenecks and prove what worked. Walk into leadership meetings with measurable improvements.

What's included

  • AI agents: Review Chaser, PR Size Coach & more

  • Outcome tracking with before/after proof

  • DORA metrics and SPACE framework dashboards

  • GitHub, Bitbucket, Jira & Linear integration

  • Slack reports, alerts & agent notifications

  • Your code is never stored

$12 USD

Per developer per month

2 months free when purchased annually

Compare to LinearB, DX, Swarmia & Haystack