Explore canvas-first workflows for research synthesis, customer discovery, product strategy, project reviews and turning scattered sources into grounded decisions.
These examples explain how to structure a canvas-first workflow. They are not customer case studies or a claim that every AI or integration capability is already available.
01 / WORKING QUESTION
Research synthesis
What do these sources agree on, and where do they disagree?
Bring the working set
Research papers and reading notes
Interview transcripts
A question with a clear scope
Research papers and reading notesInterview transcriptsA question with a clear scope
A clearer decision
THE WORK / NOT JUST THE ANSWER
Group sources by theme, not just by file type.
Connect the evidence supporting each finding. Keep contradictory material alongside it.
Ask for a synthesis that separates established findings, competing explanations and unanswered questions.
The useful output: An evidence map and a brief you can trace back to the original material.
Keep in mind: Check whether an apparent consensus comes from independent sources or repeated references to the same claim.
02 / WORKING QUESTION
Customer discovery
Which customer problem is recurring, urgent and still underserved?
Bring the working set
Customer call notes
Survey responses and support themes
Your current product assumptions
Customer call notesSurvey responses and support themesYour current product assumptions
A clearer decision
THE WORK / NOT JUST THE ANSWER
Keep observations separate from your interpretation.
Connect recurring problems across interviews while preserving who said what.
Compare frequency, severity and the strength of the evidence before proposing a priority.
The useful output: A shortlist of customer problems, the evidence behind each and the next interviews to run.
Keep in mind: A vivid quote is not automatically representative. Look for missing voices and contradictory feedback.
03 / WORKING QUESTION
Product strategy
Where should we focus next, and what would change our mind?
Bring the working set
Market research
Customer feedback
Revenue forecasts and product constraints
Market researchCustomer feedbackRevenue forecasts and product constraints
A clearer decision
THE WORK / NOT JUST THE ANSWER
Bring the working set together around one decision.
Connect proposed opportunities to evidence and constraints.
Draft options with trade-offs, assumptions and the information needed to make a choice.
The useful output: A strategic brief that makes both the recommendation and its uncertainty visible.
Keep in mind: Keep estimates distinct from observed facts. Do not let a confident summary hide a weak assumption.
04 / WORKING QUESTION
Project review
What changed, what is blocked and which decisions need attention?
Bring the working set
Meeting notes and project documents
Decision logs
Relevant issue or discussion excerpts
Meeting notes and project documentsDecision logsRelevant issue or discussion excerpts
A clearer decision
THE WORK / NOT JUST THE ANSWER
Arrange context around milestones and decisions.
Connect blockers to the source that explains them.
Separate completed work, open questions and proposed actions in the review.
The useful output: A review brief with a clear set of decisions, owners to confirm and next steps.
Keep in mind: App connections are planned. Today, use files or exported material rather than assuming a live project sync.
05 / WORKING QUESTION
Learning & knowledge building
How do these ideas connect, and what am I still missing?
Bring the working set
Course notes and reference documents
Your own questions
Worked examples and competing explanations
Course notes and reference documentsYour own questionsWorked examples and competing explanations
A clearer decision
THE WORK / NOT JUST THE ANSWER
Start with a question you can test or explain.
Connect examples, definitions and your notes into a visible structure.
Ask for comparisons and gaps, then return to the source to verify the explanation.
The useful output: A map of the subject and a focused list of what to study next.
Keep in mind: AI can produce a plausible explanation that is wrong. Verify unfamiliar claims with authoritative material.
Bring a real question.
We can walk through your workflow in a demo. Use a non-confidential sample; the interesting part is how you work, not your private files.