AI Product Strategy & Design Consulting

AI in your product that solves a real problem - and earns user trust.

The problem

AI features are getting built around the wrong problem - added because they're possible, not because they help. Users would barely notice if they disappeared.

The hard part isn't the model; it's deciding where AI genuinely improves the experience, and designing for the trust, control and fallback that make people rely on it.

Who it's for

Product teams and leaders deciding where AI belongs in their product and workflows - who want use cases that stick rather than demos that impress and then get switched off.

How we work together

AI strategy and design engagements that move from opportunity mapping to shippable patterns: in-product agents, internal automation, and the trust and evaluation model around them.

How I approach it

Find the right AI problem - Separate the AI use cases that genuinely improve outcomes from the ones that just add surface area, using a simple test: would your user notice if it disappeared?
Design for trust - Build the control, transparency and fallback that let people rely on AI features - the difference between a copilot and a crutch.
Put AI into the workflow - Apply AI to internal automation and in-product workflows to cut complexity and improve decisions, not just to generate output.
Ship and evaluate - Move from prototype to production with a way to measure whether the feature actually earns its place in the product.

What you can expect

AI use cases prioritised by real user value, not novelty
In-product agents and automation that people actually keep using
Interaction patterns designed for trust and control
A clear view of which AI features are earning their place

Hands-on AI product work - including the Green Effort AI carbon platform - plus original writing on AI in product design read across the industry.

Related work, workshops & thinking

Discuss ai product strategy with Carl