Independent analysis · No tools to sell you
AI Coding Workflow Teardown
Independent analysis of how your team actually uses AI coding tools — what's helping, what's creating rework, and where you're wasting money.
A one-week, manual assessment for engineering teams running Cursor, Claude Code, Copilot, Codex, and the rest — read by a person, not a dashboard.
What this is
Most teams adopt AI coding tools faster than they understand them. Seats get bought, tools start to overlap, review habits quietly change, and no one has a clear read on what's actually paying off.
The teardown is a focused, one-week look at how your team really uses these tools — based on your own PR, review, and workflow history, not vendor benchmarks or generic best practices.
It's deliberately vendor-neutral: nothing here is resold, and no vendor pays for a recommendation — so there's no reason to tell you to keep spending if you shouldn't.
What gets analyzed
Four things, read from your own history.
No surveys, no self-reported guesses — the analysis works from the signals your tools and repos already produce.
Review burden
How much human review AI-assisted changes actually require, and where review time is quietly climbing.
Rework & churn
Changes that ship and then get reverted or rewritten soon after — and the patterns behind them.
Overlapping tool spend
Where two or more tools do the same job on the same seats, and what's safe to consolidate.
Workflow bottlenecks
Where the AI-assisted path adds steps, context-switching, or waiting instead of removing them.
Who this is for
Built for small teams, not enterprises.
A good fit
- 10–80 engineers
- SaaS, devtools, or product startups
- Already running more than one AI coding tool
- Shipping regularly, with PR review in place
- Prefer async, written communication over meetings
- Suspect the tools help but can't see where the cost is going
Not a fit (right now)
- Enterprises with procurement and security-review cycles
- Regulated industries (health, finance, government) with data-handling constraints
- Teams not yet using AI coding tools in earnest
- Anyone who wants a tool recommendation instead of an honest read
How it works
One week, mostly manual.
Send a workflow summary email
A short email: team size, which AI coding tools you're running, and what feels off. A few sentences is enough to tell whether a teardown would be useful. No repo access required for the first assessment.
Share exports or screenshots async
If it's worth doing, you send read-only exports or screenshots — PR and review history, tool usage, seat and billing details. Exports and screenshots are enough to begin; no source code leaves your environment unless you choose to share it.
Receive the teardown report
A written report (PDF) with specific findings and recommendations, ranked by what's worth acting on first. Optionally a short Loom walkthrough so you can follow the reasoning. Follow-up questions over email.
The kind of thing it finds
Patterns, not vanity metrics.
Illustrative patterns from this kind of work — not numbers from any specific team.
Two tools, one job, double the bill
An IDE assistant and a separate autocomplete tool both enabled on the same engineers, doing overlapping work. Per-seat billing on both, no single team owning the decision, and no one tracking which one people actually accept suggestions from.
Faster PRs, slower reviews
AI-assisted changes get opened quickly and tend to be larger. Reviewers spend more time per PR, approvals lag, and overall cycle time gets worse even though "output" looks higher.
Code that ships, then gets rewritten
Generated code passes review because it looks reasonable, then gets reverted or substantially rewritten within a few weeks. Review is catching style, not the design problems that actually cause the rework.
A tool used for the wrong job
Something adopted for one task (say, scaffolding) quietly becomes the default for another it's weak at (say, editing critical, well-tested code), where it adds more review load and risk than it saves.
Next step
Start with a short email.
Most teardowns start over email. No meetings required unless you want one. Send your team size, the AI coding tools you're using, and what feels off — a few sentences is enough to tell whether a teardown would help.
Prefer to talk it through first? A short call is fine too — just say so in your email.