What changed
The standard result space compares costs, capacity, throughput, time series, and other measurable outcomes mathematically.
BUSINESS SOFTWARE / AI-NATIVE
nMODL2
Business modeling built for the AI era.
nMODL2 is a business modeling system designed for people and AI to use together. Either can write a scenario, run it, and inspect the same explicit model.
Built on a domain-specific language and exposed through a CLI, API, MCP interface, and skills, it gives both sides one place to explore how a business might behave before making the change for real.
More than a forecast.
Most simulation ends with KPIs, charts, and time series. nMODL2 keeps those numerical results, then adds semantic output: what changed for the people, roles, work, and dependencies inside the simulated business.
What it means
The semantic result space preserves causes, constraints, tradeoffs, and operational context so frontier AI can reason about why one possible future differs from another.
A hundred possible futures, explored overnight.
Imagine giving the system a goal at the end of the day. By morning, an AI has written and run 100 scenarios, compared each one with the baseline, learned from the differences, and used those findings to shape the next experiment.
You return to a field of tested alternatives and a new possible strategy—not three options someone had time to prepare by hand.
CHANGE MANAGEMENT
8,000 → 7,000
One thousand fewer people. The work still has to happen.
A blunt model removes 1,000 roles and reports the savings. With nMODL2, an AI could simulate reducing the department by 50 people at a time, reroute the work, and test each redesigned organization to form viable new workflow strategies before making a change.
At every stage it can try different arrangements. By morning, leadership could have several viable paths to the target, with the expected performance, workload shifts, risks, and reasoning behind each one.
The output is a strategy.
The useful result is not a winning score or an unexplained AI recommendation. It is a small set of viable paths, with the costs, risks, operating consequences, and evidence needed to choose among them.
The ambition is to make a meaningful part of expensive change-management consulting repeatable and inspectable as software. nMODL2 is now being developed into a full open-source platform for that way of working: humans set the objective and make the decision; AI does far more of the patient scenario-building and comparison in between.
Owen Fowler
AI Systems Builder
Tell me what you’re working on.
A few sentences is enough.