AI & Product Design

AI is a quality lever and I’ll show you how I integrate it into my workflows.

For me, it is mainly a way to think better: explore more options, challenge assumptions, structure decisions, and test ideas earlier.

It can help things move faster, but the Product Designer still keeps the responsibility for framing the problem, making trade-offs, understanding users, and shaping the final craft.

Where AI helps most

A qualitative view of where I trust AI, and where I deliberately keep more human control.

Time gain

Quality gain

AI trust

Understand

Notes, qualitative feedback, quantitative inputs

Medium

High

Medium

Structure

Problem framing, workflows, decision criteria

Medium

High

Medium

Explore

Options, scenarios, alternatives, edge cases

High

Medium

Prototype

Interactive flows, states, first implementation paths

High

Medium

Evaluate

Critique, test scenarios, risks, blind spots

Medium

High

Medium

Decide

Trade-offs, product risks, solution choices

Medium

High

Medium

Document

Specs, memory, guidelines, design system notes

High

Communicate

Narrative, alignment, presentations, team conversations

Medium

Produce

Screens, assets, components, final implementation

Low

Polish

Visual craft, microcopy, finishing details

Low

This scoring is not a scientific measurement. It is a personal reflection grid to separate areas where AI genuinely improves my reasoning from areas where I deliberately keep a lower level of trust.

My AI-augmented workflow

At every step, I keep the decision and design judgment. AI helps me structure, challenge, explore and document, but it does not decide for me and does not create evidence.

Discovery

Structures notes, qualitative signals and quantitative data

Helps identify patterns and contradictions

Challenges early assumptions

Does not replace user interviews

Does not decide what is a real insight

Does not turn correlation into evidence

Problem framing

Helps formulate multiple problem angles

Makes assumptions and fuzzy areas visible

Suggests clearer reformulations

Does not choose the problem to solve

Does not replace business context

Does not validate product priority alone

Exploration

Broadens the solution space

Generates variants, scenarios and edge cases

Helps compare the strengths and limits of each direction

Does not choose the final solution

Does not replace product taste

Does not guarantee technical feasibility

Prototyping

Creates interactive flows

Documents Figma references in design.md

Documents trade-offs and decisions in Roadmap.md & Memory.md

Does not produce production code

Does not create anything in Figma or in the design system

Does not validate the experience without user testing

Testing

Helps prepare test scenarios

Spots possible bias in questions

Structures observed feedback and signals

Does not replace real users

Does not turn a weak test into strong evidence

Does not decide alone whether a solution works

Arbitrage

Synthesizes options and their compromises

Makes risks, costs and benefits visible

Helps formalize decision criteria

Does not make the final decision

Does not replace product responsibility

Does not decide without human, business and technical context

Handoff

Creates a structured package for the engineering team

Helps produce Design.md, Memory.md, Roadmap.md and Specifications.md

Turns the validated prototype into a more usable support for developers

Does not replace discussion with engineers

Does not guarantee technical quality alone

Must not introduce unvalidated rules

My prototyping loop with coding agents

I don’t ask AI to design on its own. I feed a controlled loop with tasks, design context and validations.

Agent protocolHuman action

Handoff as structured memory

Design.md

UI choices, flows, states, edge cases and interaction logic.

Memory.md

Reasoning, trade-offs and mistakes already encountered. Helps the developer understand why a decision exists.

Roadmap.md

Priorities, task status and next steps.

Specifications.md

Functional rules, constraints and acceptance criteria.

Validated repo

Validated prototype used as a behavioral reference.