Quality Systems & Test Architecture

What we work on

Most teams add testers when releases get risky. The fix is usually structural: how quality is designed into your pipeline, observability, and release process—not how many people run manual checks.

• Test strategy and pyramid design aligned to your release cadence
• Automation framework selection, build, and team enablement
• CI/CD quality gates that block bad releases without slowing good ones
• Production observability tied to quality signals leadership actually reads
• Workshops and playbook handoff so your team owns the system after engagement

How the engagement runs

Every engagement starts the same way, because guessing at the problem is how consultants burn a client's first month.

Week 1 — Assessment. I read your CI history, not your documentation. Flake rate, mean time to green, which modules generate repeat defects, how long a release actually takes end to end versus how long you think it takes. I sit in on one real deploy. Output: a written diagnosis of whether you have a coverage problem or a structural one.

Weeks 2–4 — Critical path and gates. We map the handful of user journeys that carry revenue, then put automated gates in front of exactly those. Not full coverage—the paths where failure has commercial consequences. This is where most teams stop bleeding.

Weeks 5–8 — Framework and parity. Automation framework selection and build, plus fixing environment parity so a green test predicts production behaviour. If your staging doesn't match production, no amount of test coverage is worth anything, and this is usually where the real work is.

Weeks 9–12 — Handoff. Workshops, a written playbook, and pairing until your team is extending the system without me. I'd rather leave than be renewed out of dependency.

What you actually get

• A written quality architecture assessment—the honest version, including what I'd tell you not to spend money on
• A test strategy and pyramid design mapped to your real release cadence, not a textbook one
• A working automation framework in your repo, running in your CI, owned by your team
• CI/CD quality gates that block bad releases without slowing good ones
• Environment parity fixes so passing tests mean something
• Production observability tied to quality signals leadership will actually read
• A playbook and enablement workshops so the system survives my departure

Who this is for

Series A–C SaaS, healthcare, and regulated product teams with real users and real technical debt—where a failed release has commercial consequences, not just a Jira ticket. Typically 10–60 engineers, with at least one person internally who cares about this and will own it after I leave.

Who this isn't for: pre-product teams still searching for fit (build first, govern later), teams looking to outsource QA as an ongoing function rather than build the capability, and anyone who wants a headcount recommendation rather than an honest diagnosis.

A recent example

A regulated healthcare platform was shipping every two weeks with a senior engineer manually babysitting each deploy, and a UI regression suite that took six hours and caught almost nothing. The assumption in the room was that they needed two more QA engineers.

The CI history said otherwise: the defects that reached production were almost all API contract changes, which the UI suite never touched. We cut the regression suite down, built contract tests at the integration layer, and put a gate in front of the five journeys that carried revenue. Release cycle time dropped roughly 40%, deploys stopped requiring a named human, and the platform has held 99.9% uptime since. They did eventually hire—one person, into a system that could support them, instead of two into a treadmill.

Engagement model & investment

Three ways in, depending on how much certainty you already have:

• Assessment sprint (1–2 weeks). Written diagnosis and a prioritised plan you can execute yourself or with someone else. Often the right first step when a hiring decision is pending.
• Full architecture engagement (8–12 weeks). The four-phase sequence above, ending in handoff.
• Advisory retainer (monthly). For teams executing their own plan who want a second brain on call for design reviews and escalations.

Engagements are fixed-scope with a fixed fee agreed before we start—no hourly billing, no scope creep invoices. Indicative ranges are shared on the discovery call once I understand the size of the system; I'd rather quote you honestly than post a number that's wrong for your context. I take on three to four clients at a time, maximum.

Common questions

Do you replace our QA team? No. I design the system your team runs. If an engagement ends with your team more dependent on me than when we started, I did it wrong.

Do we need to stop shipping during this? No. Everything above is designed to run alongside your normal release cadence—the first phase exists specifically to stop the bleeding while the deeper work happens.

What if the answer is that we just need to hire? Then I'll tell you that in week one, and you'll have a written case for the req. That outcome happens, and it's a cheaper way to find out than a bad hire. More on that in when to hire QA vs fix architecture.