We move engineering teams up the AI ladder.
Which level are you at?
Cursor and Claude Code in flow.
Streaming UX, tool-use UI, glue code. Real productivity gains in the editor. Around 90% of AI-native teams plateau here.
- Claude
- Cursor
- Copilot
- OpenAI
- Gemini
- Perplexity
- Figma
No vendor lock-in. Tuned to your real stack.
Read every line, or review the diff. The wall is real.
Below the wall vs above. What each looks like day to day. Most engineers can't cross the line on their own.
- Each engineer reads every line of AI output.
- Code-by-hand is faster than directing AI.
- Token bills surprise the CFO.
- New tool every week. Nothing sticks.
- Engineers review AI PRs at the diff level, not line by line.
- Directing AI beats typing. The unlock is learning to spec.
- Token spend is a planned cost per feature.
- One opinionated stack. Documented at every stage.
Eight stages. No handoffs.
The full feature loop. AI does the work that used to need PM, designer, and QA.
Discover
AI drafts the brief from user calls and surfaces the edge cases you would miss.
Design
Twenty minutes for a first-pass UX. The accessibility check comes free.
Plan
Spec to tasks. Two architectures sketched, one picked.
Build
Pair on code. The real win is the debugging.
Review
Pre-merge scans catch what humans skim past.
Test
Tests for the cases you wrote, and the ones you forgot.
Ship
Deploy scripts, observability, the runbook. Easy to forget. Easy to automate.
Iterate
Production bugs triaged before you see them. Telemetry summarized into the next cut.
Inside the workshop.
A dozen workflows we run on production code.
Planning before code
What turns a vague request into a feature AI can ship. The patterns that decide everything else.
Debug in minutes
Stack trace in, confirmed fix out. The moves that beat hours of guessing.
Refactor at scale
Direct large rewrites with the tests passing the whole way. The verification loops that make it safe.
Tests that find real bugs
What changes when AI writes them. What stays your call.
Specialized agents
Why one agent is the wrong shape for most work. How to structure many.
When to think harder
The economics of deeper reasoning. Knowing when it earns the bill.
Two features at once
Two features in flight at once. The setup that keeps them from colliding.
AI in your CI
Code review, test gen, docs, releases. Without a human in the loop.
The team's shared brain
Context that cascades across your repo. Why it determines everything else.
Guardrails AI can't bypass
Where to insert checks that survive contact with reality.
Workflows you build once
Versioned. Shared. Opinionated. They compound week over week.
AI that reads your real systems
Wired into the tools you already use. Not a chat window. Not a pretty UI.
Five workstreams. One installable system.
Every engagement runs all five. Diagnostic finds the level. Skills and agents install the workflows. Evals catch regressions. Rituals make it stick.
- ws · DIAGactive
Diagnostic
Two-day readiness audit. We map the level of every engineer.
- ws · SKLBactive
Skills Library
CLAUDE.md, Claude Code Skills, Cursor rules. Tuned to your stack.
- ws · AGNTactive
Agent infra
MCP servers wiring your design system, Storybook, Linear, Sentry.
- ws · EVALactive
Eval framework
Visual regression, a11y, perf budgets, behavioral correctness.
- ws · RITLactive
Operating rituals
Spec-first workflow. Skills review. Agent-output triage. The retrofit.
The role is forming this year.
Catch the wave or watch it.
90% of AI-native developers are stuck at Level 2. Still reading every line.
Per Shapiro 2026
Junior dev postings dropped 67% between 2023 and 2024. Entry-level work goes to AI now.
Stanford Digital Economy Lab, ADP payroll data
Experienced devs using AI naively are 19% slower than peers without it. They believe they are 24% faster.
METR 2025. 16 senior contributors. 246 issues.
Every cohort runs on your codebase. The current one is full. Get on the list for the next.
30 minutes. We diagnose. You decide if the next cohort is yours.
Questions we get a lot.
No. The full-loop engineer compresses handoffs, doesn't eliminate roles. Your PM still owns the roadmap. Your designer still owns the system. Your QA still owns the harness. The engineer ships the first version of a feature without five handoffs to get there.
No. The workshop is tuned after a discovery call. Most teams that already use AI are at the surface 10% of what these tools can do.
That's the actual workshop. Most engineers top out at L3 because letting go is hard. We teach the diff-level review discipline that gets past it.
A 10-engineer team on Claude Code Max runs $1,500 to $3,000 a month at standard usage. We set up token observability on Day 1 so the bill never surprises you, and teach context economy so it goes down over time.
Both. We come to you for the 3-day intensive on-site (recommended), or run it fully remote. The 30-day practice tail is async with one or two sync calls.
Ready when a seat opens.
We'll talk through your team and stack, then tune the workshop to your level.
30 min · No slides · No pitch
Get on the waiting list.
The current cohort is full. Drop your team details and we'll lock in your seat for the next one.
We start with a discovery call. The workshop tunes to your stack, your team's level on the AI ladder, and the workstreams you actually need.
- 01
You drop your details.
Team size, stack, current level — or your best guess.
- 02
We call when a seat opens.
Discovery in 15 minutes. No pitch.
- 03
We tune the workshop.
Five workstreams, fit to your codebase.