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One method for every problem
SOLVED is a way of working through real problems with AI without surrendering judgement. You bring the situation; the framework provides the structure.
It is six moves, always in the same order, always the same six. The problems get harder, the tools get more capable, but the method does not change. That is the point: something durable you can trust when you do not know where to start.
The method in two minutes
Six moves, always in the same order: the problems change, the method does not.
Simplify
What is the real problem?
Open Routes
What are the realistic ways this could be solved?
Lock the Route
Which approach fits this situation?
Visualise Done
What exactly must exist or be true at the end?
Execute
How do we do the work?
Determine
Is the result genuinely good enough?
The loop closes back on itself. Checking a result often reveals a sharper problem or a bigger opportunity, and the loop begins again with better information. That is the framework working, not failing.
The six stages
Turn a vague situation into a useful working understanding.
Most requests arrive as a solution in disguise or a feeling that something is wrong. Simplify separates the situation from the assumed fix, asks a small number of high-value questions, and produces a working problem statement with its constraints, knowns and unknowns.
What to do
- State what is actually happening, not what you plan to build.
- Separate the situation from any solution already assumed inside it.
- Name the constraints that genuinely bind this situation.
- Write down what is established and what is still uncertain.
- Keep the statement provisional: it will be corrected as you learn.
What goes wrong
- Accepting a requested solution as the problem itself.
- Running a long intake questionnaire before being useful.
- Polishing a generic answer instead of asking one good question.
In plain words
- Constraint: anything a solution has to live with, like a budget, a deadline, or the people available.
- Working problem statement: a short, honest description of what is going wrong. It is expected to improve as you learn more.
The commandments
Twelve working principles make the framework honest in practice. You will meet each one at the moment it matters, in the Hour and in the Course. Here they are in one place.
Reality before technology
Never force a technological solution before the real problem is understood.
Context before generic advice
Prefer a few high-value questions over a polished but generic answer.
Confusion is productive
Unfamiliar terms, tools, costs and risks are learning moments, not embarrassments.
Exploration before commitment
The first plausible route is not automatically accepted.
Fit before sophistication
The simplest suitable route may be better than the most impressive one.
Define done before substantial execution
Large tasks should not begin without a reasonably explicit output state.
Ask what AI can actually do
Make AI capability visible: what it can do, what it cannot, and what stays human.
Keep the latest understanding current
The first description of the problem is provisional; the latest confirmed understanding governs the work.
Validation scales with consequence
A social caption and a financial forecast should not be checked the same way.
Complexity is nested, not abandoned
Large work contains smaller SOLVED loops; the framework does not change, the problems do.
Progress means less scaffolding
Completion is not competence; independence is the goal.
Keep your agency
AI can recommend, reason and work, but you should understand every consequential decision.
How this studio teaches it
The Brief
About 10 minutesThis page. The whole framework at a glance: read each stage, see what it guards against, and understand the loop.
The Hour
About an hourOne complete SOLVED loop over a realistic problem, in the industry you pick: community, trades, health, hospitality. You make the decisions, you meet the classic failure patterns, and you see exactly why each move exists.
The Course
Self-pacedEight structured modules: the foundations, one deep module per stage, and transfer. Each ends with a practice encounter and an application to your own work.
The Workbench
OngoingWhere it becomes real. Bring an actual problem and run it through the loop in a persistent workspace: your understanding, routes, definition of done, checks and decision, all in one place.
Where to go next
If you are new, take the Hour: one loop, one realistic problem in the industry you choose, about sixty minutes. If you prefer depth first, start the Course. And when a real problem is on your desk, open the Workbench and bring it.