AI problem-solving workspace
Find the right problem
before you build
the wrong solution.
Describe what is going wrong. ProblemForge helps you uncover causes, challenge assumptions, reframe the problem, test solutions, and build an action plan.
No account required. The guided example runs entirely in your browser.
See how understanding the problem can change which solution ranks highest
A real result from the guided example. The numbers are solution-fit points: higher means a better fit for the problem as currently understood.
Before
1.AI study planner
7.752.Flexible deadline windows
3.53.Cross-course deadline coordination
3.25
After reframing
1.Cross-course deadline coordination
7.752.Flexible deadline windows
6.53.Assignment clarity standards
3
▲Cross-course deadline coordination rose to first place·▼AI study planner fell
- You say"We need an AI study planner."
- ProblemForge asksWhat evidence says planning is the primary cause?
- DiscoveryDeadlines may be clustering across courses.
- ReframeReduce avoidable workload spikes.
- ResultA different solution becomes stronger.
Six steps from a vague complaint to a plan you can defend
You move through them in order. You can always step back.
Describe the problem
Tell us what is going wrong, in your own words.
Understand what is happening
Break the situation into people, causes, constraints, and unknowns.
Question your assumptions
Find what you may be assuming without evidence.
See the problem differently
Reframe the problem and watch how that changes which solution ranks highest.
Test before you commit
Run the smallest experiment that could prove your thinking right or wrong.
Build your action plan
Turn what you learned into practical next steps.
Built to be trusted
Under the plain language there is a strict division of labor between the AI and deterministic code.
Facts and guesses are kept apart
Every element is labeled: known, inferred, assumed, unknown, or needs evidence. Those labels are typed data the scoring engine consumes, not words in a paragraph.
The AI never invents the numbers
Models produce structure and categorical judgments only. Every score, ranking, and progress figure is computed by deterministic, unit-tested code you can inspect.
It finds the assumption everything depends on
If flipping one assumption changes which solution wins, that assumption is the one to verify first. ProblemForge detects this by recomputing both rankings, not by asking the model for an opinion.
Why this is not another chat window
Ask a chatbot the same question and you get plausible prose: the assumptions stay invisible, the causal claims stay unexamined, and you get a confident answer to what might be the wrong problem. ProblemForge produces a structured problem model, argues against its own analysis, computes which assumption actually matters, and shows you, not tells you, how reframing the problem changes the right answer. Its most honest outputs are sometimes “this is an assumption” and “we do not know yet, and here is the cheapest way to find out.”
See it on the guided example