Product owners, engineers, and domain experts repeat reviews every release
Your team repeatedly inspect outputs without turning their judgment into a reusable capability.
AI quality systems for product and engineering leaders
Ship AI products with confidence.
Give product and engineering teams a shared, executable definition of quality, so leaders can make release decisions with evidence instead of demos, opinions, and repeated manual review.
A practical half-day workshop
Build Your AI Behavior Harness
~4-hours · next workshop date October 21st 9AM PT · $400 CAD per person
Product owners define the outcome users need. Engineers make behaviours testable. Domain experts define what good looks like in practice. Together, they agree on expected behaviours; observable checks provide shared evidence for release decisions.
The leadership risk
AI quality cannot remain a judgment call every time the product changes.
When expectations live in the heads of product owners, engineers, and domain experts, every release creates another round of manual review. Product and engineering debate whether the experience is good enough, while leaders lack consistent evidence for deciding whether to ship.
Release decisions depend on opinion
Words such as helpful, accurate, and safe hide different expectations until the team makes them observable and shared.
Leadership cannot see where risk remains
The team ships without a common view of which customer-critical behaviors are defined, tested, or still exposed.
Define the behaviours your product depends on. Make them testable.
Start with the user’s goal and the situations your feature needs to handle. Define what a successful response must do, which variations are acceptable, and what must never happen. Those expectations become specifications for repeatable tests.
- Behavior Harness
- Use repeatable tests and evidence to check whether those behaviours still hold.
- Behavioral Map
- Define what the product must reliably do, and under which conditions.
- AI System Model / input map
- Identify the visible and hidden inputs that can change behaviour.
Different valid wording can satisfy the same requirements. The goal is preserving important behaviours under relevant variations—not identical text or a guarantee of every future outcome.
What your team takes away
Leave with a Behavior Harness Starter Pack for one real AI feature.
Capture expert judgment in a quality system the team can reuse, inspect, and improve.
Book the workshop- An input map of visible and hidden variables.
- A behavioural map defining requirements worth protecting.
- 3–5 fully specified eval cases with context, expected behaviour, and evaluator choices.
- Prioritized coverage gaps and fixture/mock requirements.
- A development/regression workflow and 30-day implementation priorities.
This practical working session produces implementation-ready specifications and a plan, not a fully integrated harness or completed CI setup.
From “helpful” to observable requirements.
Illustrative example: a scheduling assistant helping a user arrange an appointment.
Fuzzy expectation: “The assistant should be helpful and book meetings effectively.”
One scheduling feature → three required behaviours
Missing account information
Ask for required information before recommending an action.
Expectation definedAvailable appointment times
Use current tool results, not invented availability. If the tool fails, explain that availability could not be checked.
Examples preparedBooking action
Obtain the required confirmation before committing.
Automated check pendingIllustrative pass: asks for missing account type, then uses supplied constraints.
Illustrative fail: invents missing context and recommends an irreversible action.
A defined expectation is not a passing automated test. Reproduce a newly discovered production failure with its context and add it to regression coverage.
Build Your AI Behavior Harness
~4-hours · next workshop date October 21st 9AM PT · $400 CAD per person
Map what controls the response 30 minutes
Visible input, hidden context, state, tools, and model variation. Input map.
Define behaviours worth protecting 50 minutes
User goals, expected behaviour, boundaries, and acceptable variation. Behavioral Map v1.
Turn behaviours into eval specifications 60 minutes
Select 3–5 high-value behaviours and define scenarios, fixtures/mocks, expected actions, and evaluator choices.
Plan the regression and improvement loop 45 minutes
Determine where tests and production learning fit the delivery process.
Review confidence and next steps 25 minutes
Prioritize gaps, owners, and the next 30 days.
Includes a 10-minute break. Approximately four hours overall.
What to bring
Bring one AI-enabled feature, a few examples of useful or problematic behaviour, and the context behind them. Product and engineering colleagues working together are a good fit. Sanitized or synthetic examples are welcome.
Book the workshop
Why Evan · Startup 0-to-1 & Fortune 50 AI
Startup speed. Enterprise complexity. A shared standard for AI quality.
After his HealthTech startup was acquired by Virgin Pulse in 2019, Evan went on to work on agile delivery at enterprise scale and, in the Bay Area, on scaling the reliability of consumer-facing AI experiences.
That experience shapes his approach to a familiar leadership problem: how do you keep moving when product owners, engineers, and domain experts each have a different view of “good enough”? His focus is turning those perspectives into explicit behaviours and repeatable evidence, so release confidence does not depend on another round of subjective review.
The workshop brings that approach to one real feature: agree on what good looks like, define how to evaluate it, and prioritize implementation. When hands-on delivery is needed, Prototype Devshop can help turn that plan into an executable harness and regression workflow.
Half-day workshop
Build Your AI Behavior Harness
$400 CAD per person
Work through one AI feature with Evan. Agree on the behaviours that matter, turn 3-5 priorities into evaluation specifications, and leave with a Behavior Harness Starter Pack your team can use to begin implementation.
Book the workshopPrefer to start on your own?
Turn AI quality from a recurring leadership risk into an ongoing engineering capability.
Define the behaviours that matter, then build repeatable checks that make release decisions clearer.
BeforePractice to establish
Implicit expectationsExplicit requirements
Repeated manual reviewReusable test specifications and evidence
Invisible riskVisible coverage gaps
Isolated fixesReproducible regression cases
Want us to implement it?
Get hands-on implementation of an AI Behavior Harness for your feature. Done-for-you engagements start at $15,000 CAD.
Explore done-for-you implementationMake AI quality visible before you ship.
Use three-line sticky notes to define who the user is, where they are starting, and what a useful response must do. Turn one broad expectation into testable behaviours and see where evidence is still missing.
Download the free starter guideFree four-page introduction, worked example, and sticky-note worksheet. No email required. The paid workbook takes those notes onto a simple canvas and through a baseline harness implementation.
Before you book
Who is the workshop for?
Product and engineering teams building or improving an AI feature. Product owners, engineers, and domain experts each bring a useful perspective on what the feature should do and how to judge its behaviour. A feature in development and a clear user goal are enough to work from.
What will I leave with?
A Behavior Harness Starter Pack for one feature: a map of its inputs and expected behaviours, 3-5 evaluation specifications, and priorities for implementation. It gives your team a concrete starting point for turning quality expectations into repeatable checks.
Do I need to know how to code?
You can contribute to defining behaviours and deciding what good looks like without writing code. Engineering knowledge helps when planning how to capture outputs, implement checks, and fit them into your team's workflow. No specific evaluation platform is required.
What should I bring?
Choose one AI feature or workflow you want to evaluate. Bring a short description of who uses it, what they are trying to accomplish, and a few examples of the behaviour you expect. Use examples you can share with the group.
Will I build a complete harness during the workshop?
The half-day workshop gives you the specifications and implementation priorities for your first harness. You will define what to check, the scenarios to recreate, and what passing looks like. Your team can then use that work to implement the checks in your own system.
What happens afterwards?
Your team has a clear starting point for implementation. Use the Starter Pack to build the highest-priority checks, compare results after changes, and add new scenarios as you learn from real usage. Each specification connects a behaviour to the situation being tested and what passing looks like, so engineering can move from discussion to implementation. If you would like us to handle that work, explore our done-for-you implementation service.
How is the workshop different from the self-guided PDF?
The $16 CAD workbook lets you work through the canvas and baseline harness example at your own pace. The workshop adds Evan's guidance as you apply the method to your feature, work through ambiguous expectations, and decide which behaviours to prioritize.
Give your team a clearer basis for its next AI release.
Work through one feature and leave with the behaviours to protect, the first eval specifications, and a practical implementation plan.
Book the workshop