Velocity Engineering
Through AI Adoption.

AI tools are fast. Your pipeline isn't.

Your engineers write code faster than ever. But builds queue, tests flake, CI bottlenecks, and deploys wait for approvals. You didn't speed up — you just moved the bottleneck. We fix the whole thing.

40+ years combined engineering leadership

Uber Alto Pharmacy Fiserv Enterprise Partners

The problem

Everyone's adopting AI.
Almost nobody's getting faster.

Where the bottleneck actually moves

AFTER AI TOOL ROLLOUT

Code ⚡
Build 🐌
Test 🐌
CI 🐌
Deploy 🐌

AFTER VELOCITY ENGINEERING

Code ⚡
Build ⚡
Test ⚡
CI ⚡
Deploy ⚡

The Entire SDLC

Code generation is solved. The rest isn't. We accelerate builds, testing, CI/CD, deployment, and review — the full software development lifecycle. Not just one piece of it.

Champions, Not Mandates

Top-down AI mandates get ignored. We find your early adopters, build the curriculum with them, and they teach their teams. Adoption spreads because people see it working — not because they were told to.

Measurable Outcomes

We measure what matters — deploy frequency, lead time, throughput. No vague promises. You'll see the difference in your engineering metrics within weeks, not quarters.

The difference

We're not another
AI consultancy.

Typical AI Consultants

  • Roll out a tool and hand you a training deck
  • Focus on code generation and ignore everything after
  • Junior consultants who've never shipped production systems
  • Leave and adoption dies within a month

App Vitals

  • Accelerate the entire pipeline — builds, tests, CI, deployment
  • Build champions inside your org who teach their own teams
  • 40+ years engineering leadership at Uber, Alto, enterprise scale
  • Your team owns the results — we leave, the velocity stays

Start here

The AI Velocity Assessment.
4 weeks. No commitment beyond that.

Before we fix anything, we need to understand where you are. A focused, four-week engagement to diagnose your bottlenecks and design a plan that actually fits your org.

Week 1

Access Sprint

Kick off with your engineering leadership. Get access to repos, tools, and calendars. Identify key people for 1:1s. No interviews yet — just getting in the door.

Weeks 2–3

Discovery

1:1s with your engineers. SDLC review — where does AI fit and where doesn't it? Map bottlenecks: technical, human, and process. Identify your champions.

Week 4

Report & Plan

Written assessment with maturity arc placement, bottleneck diagnosis, and a prioritized plan for what to do next. Presented to your leadership team.

The assessment is a standalone engagement. At the end, you get a clear picture of where you are, what's blocking you, and a concrete plan. You decide what comes next — no lock-in, no pressure.

The full engagement

Three phases.
Each one earns the next.

Assessment first. Then systems. Then adoption. This order matters — broad AI rollout before systems work creates churn. We've learned that the hard way.

1

Assessment

4 weeks

Diagnose bottlenecks across your SDLC. 1:1s with engineers, champion identification, maturity mapping. Ends with a written report and engagement design.

2

Systems

4 weeks per project

One service at a time. Clear goals, embedded engineers, measurable outcomes. Fix builds, testing, CI/CD, and deployment — the infrastructure that makes AI tools actually useful.

3

Adoption

4–6 weeks

Org-wide rollout led by your own people. We build the curriculum with your champions — they deliver it to their teams. Mavens, not mandates. Velocity metrics go live.

2–3×

Faster shipping velocity

4 wk

Assessment to action plan

Zero

Quality compromised

If you speed up code generation but your CI takes 45 minutes, you didn't get faster. You just moved the bottleneck.

The velocity engineering thesis

Your engineers are ready.
Your pipeline isn't.

30 minutes. No pitch deck. Just an honest conversation about where your bottlenecks are and how to fix them.

Book a Discovery Call