Signal 01
Users hesitate after the AI responds
The answer may be technically useful, but people cannot judge its confidence, source, limits, or next step.
AI Product Trust SprintOne journey10 working days€10,000 fixed
For teams shipping AI into real decisions
Fix the AI moments that make users hesitate.
Audit one critical AI journey, redesign its trust and failure states, and leave with a prototype your team can ship. Ten working days. One accountable lead. No discovery maze.
Best for B2B SaaS, fintech, marketplaces, internal tools, copilots, recommendations, AI search, and agents where confusion or mistakes have real cost.
The product works. Trust still leaks.
AI friction is rarely one bad screen.
It lives across the full loop: what users ask, what the system does, what it reveals, how people correct it, and what happens when confidence breaks.
Signal 02
Correction and recovery are unclear
Users can generate output, but editing, retrying, undoing, escalating, or recovering from failure feels improvised.
Signal 03
The team debates trust instead of shipping it
Product, design, engineering, legal, and support each see different risks, with no shared journey or priority order.
Signal 04
Usage looks healthy, but value is fuzzy
Dashboards count prompts and sessions while missing whether users completed the task, corrected the system, or came back.
60-second trust check
How much trust debt is hiding in your AI journey?
Select every statement that is true for one important user journey. This is a signal check, not a compliance or legal assessment.
A short path to a real result
Diagnose. Redesign. Ship.
The sprint is designed around one measurable outcome, not a catalogue of methods. Every activity must move the selected journey toward a clearer implementation decision.
01
Days 1 to 3
Find the trust-breaking moments
Review one critical AI-assisted journey, product evidence, support patterns, analytics, states, permissions, and failure paths.
02
Days 4 to 7
Redesign the full interaction loop
Shape clearer inputs, response states, confidence cues, correction controls, fallback behavior, human oversight, and recovery.
03
Days 8 to 10
Make the fix ready to ship
Deliver a tested prototype, prioritized implementation backlog, measurement plan, and a working session with your team.
What you get
Not a deck. A working product decision.
The output is built so product, design, engineering, compliance, and support can see the same journey and act on it.
- Included 01
Trust-state map for one critical AI journey
- Included 02
Annotated review of current friction and product risk
- Included 03
Interactive prototype covering success, uncertainty, correction, failure, and escalation
- Included 04
Implementation-ready UX and content recommendations
- Included 05
Prioritized backlog with impact, effort, and ownership
- Included 06
Measurement plan for task completion, correction, recovery, and repeat value
Why HAAM
Interaction design for AI that has consequences.
Kris Haamer leads the sprint directly, connecting user behavior, interface states, technical constraints, accessibility, and human oversight instead of treating trust as a layer of UX copy.
Decision support
Green Filter
Research-led AI companion work translating complex recommendations into understandable choices, actions, and feedback loops.
See the workHuman supervision
HAAM Automation Studio
A public workflow tool built around permissions, approval gates, fallback behavior, ownership, and measurable outcomes.
See the workTrust as interaction
Trustfall Lab
An experimental environment for exploring how confidence, uncertainty, evidence, and user agency become visible in interfaces.
See the workThis sprint fits
A valuable journey with visible uncertainty.
- B2B SaaS copilots and assistants
- AI search, recommendation, and decision-support products
- Agentic workflows that act across tools or data
- Fintech, marketplaces, support, and internal products where mistakes carry real cost
This is probably not the right format
A broad brief with no journey to improve.
- A general brand refresh with no defined AI journey
- A request for a long strategy report without implementation intent
- A full product rebuild involving several unrelated journeys
Simple commercial frame
One journey. Ten days. €10,000.
The fixed scope includes preparation, review, working sessions, prototype design, backlog, measurement plan, and final handoff. Production implementation is optional and scoped after the sprint.
Before the sprint starts
- 1Send the product, prototype, or journey.
- 2HAAM confirms fit and the exact scope.
- 3Choose the start date and share access.
- 4Kick off with the team that owns the journey.
Questions before you start
The practical details.
Why focus on only one journey?
A narrow scope creates a useful result quickly. The sprint goes deep enough to redesign real states and controls instead of producing a broad list of observations that nobody owns.
Do we need a live product?
No. The sprint can work from a prototype, an internal build, or a live feature. You need a defined user, task, and AI-assisted journey that matters to the business.
Does this include engineering?
The fixed sprint includes implementation-ready design, states, requirements, and handoff. Production engineering can be scoped separately when you want HAAM to help ship the changes.
Will this cover AI governance or compliance?
It covers product-facing governance such as disclosure, consent, permissions, oversight, escalation, correction, and accountability. Formal legal, security, or regulatory advice requires the appropriate specialist.
What happens before we commit?
Send the journey, product link, or prototype. HAAM will confirm whether the problem fits the sprint and identify the exact journey to review before proposing a start date.
The next step is small