AI Engineering Velocity Audit · $2,500 fixed fee
Jonathan Sullivan helps engineering teams identify AI, architecture, CI/CD, verification, and workflow bottlenecks — and turn them into measurable automation opportunities.
Generation is cheap now. Review, CI and production proof are not — and agents multiply demand for exactly those. If several of these are familiar, the constraint is probably not code:
One focused engagement with a defined end. You get a written audit you own.
Where work actually waits — review, CI, QA, or release approval — measured rather than guessed.
How the system is put together, and how coding agents move through it today.
Pipeline timing and failure modes, quantified wherever the evidence permits.
How you prove deployed behaviour matches intent — and where that proof is missing.
Debt measured at integration boundaries, where AI-assisted development actually concentrates it.
Sequenced, with owners and success criteria. Plus what could ship in the next seven days.
Most engagements start and end with the audit, and that is a fine outcome. When a team wants the findings implemented, there are three ways to continue.
$5,000 – $10,000
Implement the highest-ROI finding from the audit. Fixed scope, seven working days, measured against a day-one baseline.
$10,000 – $20,000+
For a specific, serious problem in production, architecture, reliability, or delivery. Fixed scope wherever possible.
$8,000 – $15,000+/month
Ongoing architecture, agent adoption, release governance, and technical leadership. Monthly, 30 days' notice either side.
For investors, micro-PE, search funds and acquirers — $5,000 – $10,000. Architecture, scalability, code health, security, key-person risk, and AI/agent claims tested against what actually runs rather than what the deck says. Claims that cannot be tested are reported as untested.
A few questions so the first call is a diagnosis rather than an introduction. It takes about two minutes, and Jonathan replies personally with times for a 30-minute AI Engineering Diagnostic.
