Speak with Quality gives quality engineering teams the behavioral intelligence to influence decisions, frame risk, and operate as strategic partners instead of testers.
You've been handed all three, and AI is supposed to make them possible. Some of that is real. Code volume is up. Cycle time is down. Suites that took a quarter to build now take a week.
And quality is the easiest line to trim, because it has always been sold to you as a cost center instead of a control.
Your own scoreboard already says so. DORA has measured software delivery performance for more than a decade, and its research across roughly 5,000 practitioners found AI buying speed and spending stability to pay for it.
drop in delivery stability for every 25 percent rise in AI adoption, measured in 2024
the year throughput recovered. Stability did not.
downtime cost when change failure rate moves from 5 to 6 percent, in DORA’s own worked example
So half the mandate is landing. Ship faster is real. Spend less depends on stability, and stability is moving the wrong way.
And it is not confined to software. Across industries, organizations thinned the quality layer, handed the judgment to AI, and published what happened next.
E-commerce / Software Delivery
orders estimated lost in a single six-hour outage
Amazon mandated AI coding tools across its engineering org and targeted two billion dollars in savings. Between December and March it took at least four Sev-1 incidents. The internal escalation memo grouped them under gen-AI assisted changes and high blast radius. The fix was a new requirement for senior engineer review of AI-assisted production changes.
Automotive / Quality Engineering
projected cost reduction after the reversal
Ford shed 5,300 salaried roles and put 900 AI cameras on the line, betting automated inspection could carry quality. The engineers who held the context had already left. Three years and roughly 350 rehires later, Ford topped the J.D. Power Initial Quality Study for the first time since 2010.
Banking / Service Operations
redundancies reversed, with a public apology
Commonwealth Bank of Australia cut 45 service roles and replaced them with an AI voice system. Call volumes rose instead of falling. The bank reversed the redundancies and apologised publicly.
Amazon added senior review. Ford rehired veterans, and it took three years. CBA brought its people back and apologised. Every fix was the same one: put experienced human judgment in front of the decision.
The people closest to your risk are already on your payroll.
They have the judgment. Getting it into the room where the decision happens is the part nobody has trained them to do.
Sources: CNBC and TechRadar reporting on Amazon internal memos; J.D. Power 2026 Initial Quality Study; Bloomberg; Google DORA, State of AI-assisted Software Development, 2024 and 2025.
QA professionals are S or C behavioral styles.
Wired for precision, process, and getting it right before they speak. The engineers and PMs they brief are mostly D and I styles, wired for speed, momentum, and the headline first.
So the scope gap gets raised carefully, in a thread nobody escalates. The risk arrives as coverage data and defect counts, which answers what the team did rather than what leadership should do. By the retro it reads like quality missed it, when quality named it and nothing moved.
The Leaders' QA Consulting, Tester Personality Report 2024
That call is human. It only counts if the person making it can hold the room when senior leaders push back.
Field hard questions from senior leaders without getting defensive and without drowning them in detail.
Leave the room with a decision on the table, rather than a document for somebody else to interpret.
Open with what it costs the business and how likely it is, instead of opening with what the team tested.
The workshop builds the first two into your team in a day. The third is a longer piece of work, and it usually starts with one leader rather than a room.
DISC-based team training built for the rooms your quality team already sits in. Half-day and full-day formats, virtual or onsite, with assessments included.
Private coaching for QA and quality engineering leaders who need to land the recommendation, hold the room when senior leaders push back, and be read as a strategic partner rather than a reporting function.
Erika Chestnut has been in that room. Twenty years leading quality and engineering teams, on the side of the table that gets asked to explain itself.
She has been the person who caught the risk, documented it properly, raised it through the right channel, and watched the release go anyway. Speak with Quality is the training she built out of that.
This is not a communication workshop with QA examples bolted on. Every scenario, role play, and tool was built for the rooms quality teams actually sit in: the sprint review standoff, the risk conversation with a D-style VP, the retro where the scope decision gets relitigated as a testing failure.
