CrewPEA product of EnWithAI
One workspace. Your team and AI, building together.
CrewPE brings your repos, docs, knowledge and conversations into one place, with AI that finds answers, takes action, designs securely and builds alongside your team.
ExampleOne story, from the ask to the merge
- PMIntent“Retry failed payment webhooks”
- 1Spec4 acceptance criteria
- 2Plan
payments-apiledger-service - 3Code2 pull requests
- 4Check4 of 4 criteria pass
- ELReady to mergeYour lead reviews and approves
# Original ask
Finance reports missing payment events since Tuesday. Find out why webhooks are dropped and stop it happening.
# What we know 4 captured · 1 assumed
Stop losing payment events when webhook delivery fails.
Stated by the product managerpayments-api receives provider webhooks; ledger-service records settled payments.
From the product mapBounded retries, a dead-letter queue and an on-call page after repeated failures.
Decided by the engineering leadFinance operations and on-call engineers.
Confirm in the threadSpec lockedConversation
2 Oct
Finance reports missing payment events since Tuesday. Find out why webhooks are dropped and stop it happening.
Retries in payments-api have no ceiling and no dead-letter queue, so events are dropped once the provider times out.
Worth considering:
- Replaying events that were already lost
- Alerting finance when the dead-letter queue grows
Retry for up to an hour, then dead-letter. Page on-call after 8 failures.
Every engineer got an AI coding tool. Team delivery moved by single digits, because the work around the code did not change: context, specs, coordination and review.
- 7.76%
- median gain in pull-request throughput from AI coding assistants, across 400+ organizations
- 5–15%
- the range where most of those organizations land
- 32.7%
- of AI pull requests merge within 30 days, against 84.4% of manual ones
Sources: DX, AI coding assistant pricing and ROI guide (2026); LinearB, 2026 Software Engineering Benchmarks Report.
One workspace for your product. One crew to build it.
Knowledge, conversations, stories, agents and controls, in the place your product and engineering teams already plan their work.
Workspace
It knows your whole product, and works alongside you.
Repos, tickets, docs and conversations in one context. Ask about your work, let your agent draft changes and run routines, and teach the crew your conventions with skills.
Acme Checkout · EntitiesExample
Crew
From story to ready-to-merge, across every repo.
The crew writes the spec, plans the change across repos, writes the code and checks it against every acceptance criterion before anyone reviews it.
PAY-2143 · Spec v2Example
AC1Failed deliveries retry with exponential backoff
AC2No retry waits longer than 1 hour
AC3The same event ID is recorded once
AC4After 8 failures, dead-letter and page on-call
Plan: payments-api (AC1, 2, 4) · ledger-service (AC3)Approved
Control
Run AI as a team, not a pile of tools.
Approvals, models, prompts, spend and audit in one place, for the crew and the AI tools your engineers already use.
Approve spec v2?Waiting
4 acceptance criteria across 2 repos. Raised by finance operations.
It knows how your whole product fits together.
CrewPE maps your repos, the APIs, events and tables between them, and the tickets, docs and conversations around them. People and agents start from the same picture. Pick a service to see what a change to it would touch.
From story to ready-to-merge, in five steps.
You set the intent and approve. The crew does the rest.
- 1
Read the story
The crew pulls the story and the repos, docs and conversations it touches.
- 2
Write the spec
Acceptance criteria for each repo. A person approves them.
- 3
Plan and code
Changes and tests in every repo the story touches.
- 4
Check
Every criterion checked. Failures go back with the reason.
- 5
Hand back
Ready-to-merge pull requests, and the ticket updated after approval.
When the check fails, the crew gets the reason. A person gets the last word.
Each failed criterion goes back to the crew with the reason. If the change still fails at the loop limit you set, it stops and goes to a person with the full trail.
- Loop 1Returned
AC2: retry delay has no ceiling.
- Loop 2Returned
AC3: a replayed event is recorded twice.
- Loop 3Returned
AC3 still failing. Loop limit reached.
- EscalatedA person decides
The engineering lead sees every loop, every reason and the diff.
Example of a change that reaches the loop limit.
How we measure
Proven changes per $1,000 of AI spend.
One number to judge us by. AI spend covers seats and usage across every coding tool you pay for, so you have a baseline before CrewPE, and it does not move when our prices do.
IntendedToday
The change traces to an approved spec with acceptance criteria.
VerifiedToday
Every criterion passed a check run by something other than the agent that wrote it.
DurableIn build
The change is still in main 30 days later. Not reverted, not rewritten.
A change counts as proven when it meets all three.
Where teams put their AI crew to work first.
Teams start where the work is hard, spread across repos, or has to stand up to review.
Prove parity, module by module.
Agents can rewrite a legacy module in an afternoon. The hard part is knowing the new one does everything the old one did. CrewPE writes that down first and checks it every time.
- Parity criteria written from what the module does today
- A check result for every migrated module
- Blast radius known before each cut-over
Billing migration · 4 modulesExample
Not another coding tool. The layer that governs them.
Your coding and review tools keep doing what they do. CrewPE governs the work around them: the spec they build against, the approvals, and the evidence that the outcome was delivered.
Works with what you already use.
CrewPE reads your trackers, source control and docs, and sees the AI tools your engineers already use. Nobody has to switch.
Trackers
Stories and tickets come in
JJiraLLinearCClickUpAAsana
Source control
Repos read, pull requests opened
GGitHubGGitLabBBitbucket
CrewPE
One workspace on top of the tools your team already uses.
- Reads
- Stories, repos, docs and conversations
- Writes
- Pull requests, and tracker updates once a person approves
- Sees
- Usage from your AI coding tools Rolling out
Knowledge and chat
Docs and decisions in context
CConfluenceNNotionSSharePointSSlack
AI coding tools
Usage matched to your work
CClaude CodeCCodexCCursorGGitHub Copilot
From one team to your own numbers in six weeks.
A typical pilot. We agree the scope with you first.
- Day 0
Agree the scope
One team, one repo and the stories to start with.
- Week 1
Connect one team
Tracker and source control for one team. Engineers change nothing.
- Week 2
First approved specs
CrewPE drafts specs, your lead approves them, and the crew starts.
- Weeks 2 to 6
Results build up
Stories built, checks passed and AI spend, for the team.
- Week 6
Review
Decide what to expand, with your own numbers in hand.
Before you start.
Something we have not covered? Talk to us
Does CrewPE replace our AI coding tools?
No. Your coding and review tools keep doing what they do. CrewPE governs the work around them: the specification they build against, the approvals and the evidence that the outcome was delivered.
Is it only for new code?
No. CrewPE is strongest on existing, business-critical applications. It captures current behavior and domain rules first, so every change is measured against a known baseline.
What results can you show?
We run proof-of-value engagements and measure against a documented baseline: rework, review cycles, time from approved specification to accepted change, and cost per accepted outcome.
Who does the delivery work?
Your choice: your own team on CrewPE, your team with our engineers beside you, or an EnWithAI team that delivers an agreed scope. Compare ways to buy
Try CrewPE on one real story.
Bring a story your team is about to build. We will show you the spec, the plan across repos and the checks before anything is merged.