Operating Model — Teardown & Installation
Delivery models were designed for humans only.
Book a Discovery CallEvery operating model in production today makes a silent assumption: people write the software. Funding cycles, role definitions, approval gates, capacity planning — all of it assumes human throughput. Put agents into that system and the result is familiar: impressive pilots that never scale, because the surrounding machinery cannot absorb them.
We have run the project-to-product transition twice inside Nordic banks. This is the version built for what comes next.
The Teardown — two weeks, fixed fee. Your last ten initiatives, traced through your actual decision path. Output: the specific funding lines, role boundaries and gates that would block agent-assisted delivery, and who owns changing each one.
The Installation — eight weeks. The evidence gate: no build without a measurable, evidence-backed problem. Work classification: run, grow, transform, debt — typed before anything enters a queue. The product–technology leadership contract that removes the translation layer between "what" and "how". A decision cadence of fixed sixty-minute sessions in place of steering committees.
A note on lineage: the vocabulary here was popularised by Marty Cagan and SVPG. The model is our own, built in regulated institutions where "just empower the teams" meets risk committees.
Delivery Model Teardown
Two weeks, fixed fee. Your last ten initiatives, traced through your actual decision path. The output is specific: which funding lines, role boundaries and approval gates would block agent-assisted delivery, and who owns changing each one.
Control Map
Three weeks, fixed fee, for regulated companies. Your AI delivery mapped against DORA obligations and EU AI Act classification — ending with the missing controls, the evidence each one requires, and the named role who signs it.
What is a product operating model?
The system that decides how work is chosen, funded, staffed and shipped — as opposed to what tools teams use. A product operating model funds outcomes and teams; a project model funds temporary initiatives. The distinction determines whether AI capacity compounds or evaporates.
How is an AI-native operating model different from a normal product operating model?
A standard model assumes people do the building. An AI-native one adds three things: an evidence gate strong enough to be worth automating behind, delivery capacity measured in cost-per-outcome rather than headcount, and governance that can account for work no human wrote.
How long does a transition from project to product take?
The structural change — roles, gates, funding — lands in a quarter. Behaviour follows over 12–18 months. In our experience the shift delivers roughly 40% faster time-to-market, but only when the old model is actually retired rather than run in parallel.
Do we need to reorganise before adopting AI delivery?
No — and doing it in the wrong order is the most common failure we see. Install the evidence gate and work classification first; they work in any structure. Reorganise once you can see where the work actually flows.
Who is this for?
Organisations whose AI pilots impressed and stalled: banks, fintechs, and scale-ups whose delivery has outgrown its decision-making. If your last three "AI initiatives" produced demos rather than production systems, this is the diagnosis.