A 3–6 week leadership engagement to align QA, engineering, product, and executives around how quality should work in the AI era.
Engagement
Alignment
Delivery
3–6 weeks · pre-engagement diagnosis · 1-day core session · 3 follow-up reviews
Code
ALN-001
What you buy
Cross-functional alignment, ownership clarity, an org-design recommendation, and a 90-day implementation roadmap.
The promise
In a focused 3–6 week engagement, your QA, engineering, product, and executive leaders align on a new quality operating model, name the role and ownership changes required to make it real, and walk away with a 90-day implementation roadmap. Backed by three follow-up sessions so the strategy actually ships.
Who it's for
QA Directors, VPs of Engineering, CTOs, and product leaders at companies where the QA function is at a structural inflection point and the change requires cross-functional alignment. Not just a tooling decision.
Buyer state. “We know QA needs to change, but the change can't be made by the QA leader alone.”
Before the day
We produce a private Current-State Quality Diagnosis from the intake and interviews. Used to prepare the executive presentation and curate the leadership working session around your specific situation.
Structured intake
~30 minutes. We send the intake when you book; you fill it out before the day.
Optional artifacts
Drop in 1–3 of these if you want the day to discuss your specific examples. Optional, not required.
Strip confidential customer data, credentials, and proprietary architecture details before sending.
Optional stakeholder interviews
20–30 min each · scheduled by us
We can run short interviews with the people whose alignment determines whether the strategy ships. Worth doing for any cross-functional engagement.
The day, hour by hour
The future of QA leadership is not owning testing. It is owning the quality intelligence layer that helps engineering ship with confidence. The day's job is getting QA, engineering, product, and executives to commit to that shift. And to the 30/60/90 changes required to make it real.
9:00 – 9:45
Working session
Align leadership on why the current QA model needs to evolve.
Why QA teams are being compressed. Why more testing isn't the answer. Why AI doesn't fix a low-leverage operating model. Why quality must move closer to engineering. Why QA's future is owning the quality intelligence layer. Not test execution. Why leadership has to change ownership, not just buy tools.
What you walk out with
9:45 – 10:45
Working session
Show leadership how quality actually works today.
Map the real flow from requirements through release and production feedback. Identify where defects are introduced, where they're caught, where QA is acting as a late-stage safety net, where engineering is under-owning quality, where product is creating ambiguity, where automation is brittle, and where AI would help vs. add noise.
Live exercise · Current-State Quality Map
Leadership maps where quality work happens today and where responsibility is unclear.
What you walk out with
10:45 – 11:00
Break
11:00 – 12:00
Working session
Define what each function should own going forward.
Engineering: code testability, unit + integration tests, API correctness, PR-level quality, test IDs, local confidence, flaky-fix work where code or architecture is the cause. QA: test strategy, risk analysis, regression strategy, automation standards, defect escape analysis, release confidence, quality intelligence, coaching. Product: acceptance criteria, requirement clarity, customer impact, risk prioritization, tradeoff decisions.
Live exercise · Ownership Charter
Leadership defines what QA stops owning, what engineering must start owning, what product must clarify earlier, and what gets codified in the operating model.
What you walk out with
12:00 – 1:00
Lunch
1:00 – 2:00
Working session
Review the current team against the future quality model. Get more leverage from the team you have, identify where new talent may be needed.
Current QA roles, technical capability, automation ability, systems thinking, debugging, ability to work with engineering, ability to use AI effectively, ability to move from execution to leverage. Where capabilities can be developed in-house. Where higher-caliber engineering talent may be needed. Which roles must evolve.
Live exercise · Future Quality Capability Map
Leadership maps current people and roles against the capabilities needed for a modern quality function.
What you walk out with
2:00 – 3:00
Working session
You cannot ask QA to become more technical while denying them the access required to do technical work.
Whether QA can add or request test IDs, open PRs, read front-end code, review API contracts, inspect logs, view CI/CD failures, access test data, understand DB state, influence acceptance criteria, review unit/integration/API coverage, and use AI tools safely. Make the access decisions explicit; put guardrails where they're needed.
Live exercise · Access and Permissions Decision Map
Leadership decides what access QA should have, what needs guardrails, what engineering owns, what QA can contribute directly, and what process changes are required.
What you walk out with
3:00 – 3:15
Break
3:15 – 4:00
Working session
Define how automation should change in the AI era.
Unit, integration, API, and E2E test ownership. Manual regression burden. Playwright / Cypress / Selenium strategy. Test IDs, test data, CI/CD quality gates. AI-assisted test generation, AI-assisted failure analysis, AI-generated test review standards. AI shouldn't generate more low-quality test volume. It should reduce recurring effort and move quality closer to engineering.
Live exercise · AI Leverage vs. AI Theater Map
Leadership classifies AI opportunities into: use now · use later · do not use yet · requires process or architecture change first.
What you walk out with
4:00 – 4:45
Working session
Define how leadership should measure quality going forward.
Move from activity metrics (test cases run, bugs found, automation %, manual passes completed) to business-value metrics (regression hours removed, escaped defects, flaky cost, release delays, defect prevention rate, API coverage gaps, test stability, quality risk by product area, engineering ownership of quality, release confidence).
Live exercise · Executive Quality Dashboard Design
Leadership defines what executives need to see, what QA managers review weekly, what engineering managers own, what metrics prove quality value, and what metrics are misleading or obsolete.
What you walk out with
4:45 – 5:30
Working session
Turn the strategy into action.
30 days: what QA stops doing, what access gets approved, what ownership changes get announced, what dashboard gets created, what AI pilot starts, what test architecture decision gets made. 31–60 days: regression work reduced, engineering begins owning, roles change, manager cadence starts, automation standards enforced. 61–90 days: leadership review, metrics reported, people decisions, process codified, investment decisions required.
What you walk out with
After the day
Most strategy engagements stall in week 4. The structured 90-minute progress reviews keep ownership decisions, automation pilots, and metrics work moving past the inertia point.
Confirm the ownership charter has stuck and the org-design recommendations have a path to execution.
Focus
Output: Finalized ownership model and role-change recommendations.
Track real progress on the strategy and adjust the roadmap based on what's actually shipping.
Focus
Output: Updated automation, AI, and metrics implementation plan.
Hold the line at the executive level and decide whether the company needs full transformation support.
Focus
Output: Executive progress readout and next-phase recommendation. Including whether the company is ready for the Quality Transformation Sprint.
What's inside
01
Why QA teams are being compressed, why 'more testing' isn't the answer, why AI doesn't fix a low-leverage operating model, why quality has to move closer to engineering, and why QA's future is owning the quality intelligence layer that helps engineering ship with confidence. Not test execution.
02
Map the real flow: requirements → development → unit/integration/API → QA review → automation → regression → release readiness → production feedback → defect escape. Identify where defects are introduced, where they're caught, where QA is acting as a late-stage safety net, where engineering is under-owning quality, where product is creating ambiguity.
03
Engineering owns code testability, unit/integration tests, API correctness, PR-level quality, test IDs, local confidence. QA owns test strategy, risk, regression strategy, automation standards, defect escape analysis, release confidence, quality intelligence. Product owns acceptance criteria, requirement clarity, customer impact, risk prioritization. The Ownership Charter codifies the reset.
04
Where the offer becomes much more valuable than a workshop. We assess current QA roles against the future quality model. Technical capability, automation, systems thinking, debugging, AI usage, communication with engineering. And recommend where capabilities can be developed in-house, where new talent may be needed, and which roles must evolve.
05
You cannot ask QA to become more technical while denying them the access required to do technical work. We make the access decisions explicit and put guardrails on what needs them. Test IDs, PRs, code, API contracts, logs, CI failures, test data, DB state, acceptance criteria, AI tool usage.
06
AI should not help the company generate more low-quality test volume. It should reduce recurring effort, improve analysis, and move quality closer to engineering. We map AI opportunities into Use now / Use later / Do not use yet / Requires process or architecture change first. And lock in the test-architecture direction.
07
Move from activity metrics (test cases run, bugs found, automation %) to business-value metrics (regression hours removed, escaped defects, flaky cost, release delays, defect prevention rate, API coverage gaps, release confidence by product area). Define the executive dashboard, the manager weekly review, and the metrics that prove quality value to finance and the board.
08
Decisions, not directions. What QA stops, what access gets approved, what ownership changes get announced, which AI pilots start, which test-architecture decisions get made, which manager cadences begin, which dashboards get published, which people decisions are made. Sequenced across 30 / 60 / 90 days with named owners.
Deliverables
The boss-approval frame
“This is a leadership engagement, not training. It aligns QA, engineering, product, and executives around how quality should work in the AI era. Including the roles, permissions, skills, process changes, dashboards, and operating model changes required to make it real. It produces strategy, alignment, ownership, and an implementation roadmap. The 90-minute follow-ups make sure the decisions actually ship.”
ROI logic. Pays for itself if it prevents the company from buying another tool that doesn't fit the operating model, recovers a single engineer-month from the current QA / engineering ownership tangle, lands one access unlock that's been blocked for quarters, or surfaces one role decision that's been avoided. The follow-ups protect the value. Most strategy engagements stall in week 4; the structured progress reviews keep them moving.
Up the ladder · Sideways · Related
QA Leverage Review
A one-day private review of your QA team, process, automation, dashboards, and constraints. Through a leverage lens.
See it →Sprint · SPR-001Quality Transformation Sprint
A 6–10 week implementation sprint where we work alongside your team to move QA from test execution to a higher-leverage quality operating model.
See it →People · PPL-001Embedded QA
A senior SDET on your team, beachheading AI-native quality.
See it →The offer ladder
Pick by what you're trying to answer this quarter. Not by what tier looks "best." The depth of change escalates with the question. The entry course is publicly priced; higher tiers are scoped per engagement.
“Teach me the model.”
You leave with the framework, the worksheets, and a 90-day plan you can hand to your boss on Monday.
See this tier →“Apply the model to my current QA team.”
An outside diagnosis built around your team. You leave with the top-5 leverage opportunities, scored, and a 90-day plan ready for leadership.
See this tier →“Redesign our company-wide quality strategy.”
Cross-functional alignment, ownership clarity, and a 90-day implementation roadmap. Backed by 3 follow-up reviews so the strategy actually ships.
This page“Lead the transformation.”
Quality intelligence dashboard, AI/automation pilot, manager operating cadence, and 180-day roadmap. Built into how the team actually works, not delivered as a deck.
See this tier →Most clients move up the ladder one tier at a time. Skipping tiers works only when the depth of change you need is obvious from the start.
90-Day QA Leverage Plan
Use it on Monday · Editable doc + Notion template