Adam can't make it this week, so Danny takes the Broadmatch show solo with a method for anyone buried under a long list of problems. It started when a friend who uses Claude heavily could not see the wood for the trees: a hundred issues, each needing its own fix, and no way to review them all.
Perplexity gave the approach a name, collaborative upstream problem solving. You'll hear how it combines systems thinking, affinity mapping, root cause analysis and collaborative validation, and why the person holding the domain knowledge has to stay in the loop. In this real example, it turned roughly 10 days of work into 2 to 3 hours.
Danny walks through a five-step process, a Claude example about forgotten decisions and stale documents, and a one-paragraph summary you can drop into Claude to build your own skill.
Key Topics
Collaborative upstream problem solving - fixing the shared conditions behind many problems instead of each problem one by one
The four-part method - systems thinking, affinity mapping, root cause analysis and collaborative validation
Leverage points - the smallest set of changes that makes many problems disappear
Why domain knowledge still wins - the human in the loop checks that the right problems were solved
A Claude example - forgotten decisions, contradictory outputs and stale documentation as one shared context problem
Turning the method into a skill - reverse engineer the transcript in Claude
Timestamps
00:00 - Danny goes solo, Adam out this week
00:25 - Perplexity names the method: collaborative upstream problem solving
00:46 - The problem: a friend buried in Claude issues
01:36 - How do you turn 100 problems into a few?
01:58 - The combined approaches: systems thinking first
03:57 - Why domain knowledge matters: avoiding the wrong problems
05:03 - Clusters and markdown handover: 2 to 3 hours versus 10 days
05:18 - The five-step practical approach
06:22 - Claude example: forgotten decisions and stale documents
07:06 - Avoiding fixes that break other outputs
07:25 - A hypothesis, not a diagnosis
07:44 - Turning this into a Claude skill
07:55 - The method in one paragraph
08:23 - Wrap-up
Key Takeaways
Solve the conditions, not the problems - look for the shared causes generating a long list of issues.
Cluster before you fix - affinity mapping turns 100 items into a handful of meaningful groups.
Treat drivers as hypotheses - validate them with the person who holds the domain knowledge before acting.
Test one intervention first - make a small change and check whether several related problems improve.
AI executes, you think - the human in the loop and domain expertise decide whether the fixes are right.
The Five Steps
1. Capture examples - the problems, plus the outcome the person wants
2. Cluster the symptoms - group problems by meaningful relationships using affinity mapping
3. Propose underlying drivers - recurring conditions that might explain each cluster, held as hypotheses
4. Validate together - check the groupings, exceptions, constraints and what is fixed
5. Test one intervention - a small change, then check whether related problems improve
Notable Quotes
"I'm not trying to solve a hundred problems faster. I'm trying to find the smallest set of changes that could make many of these problems disappear." - Danny McMillan
"AI isn't just your assistant. You're driving the process yourself. It's you who's doing the thinking." - Danny McMillan
"I solve the conditions creating the problems, not the problems themselves." - Danny McMillan
Resources Mentioned
Perplexity - used to find a concise name for the thinking approach
Affinity mapping - the established technique for grouping many issues into meaningful clusters
Claude - used to organise the material and build the markdown handover files
Cron job checks - a scheduled way to keep documentation current and replace stale information
Connect
Questions on the method? Email Danny McMillan at danny@sellersessions.com.
Seller Sessions is the leading podcast for advanced Amazon sellers, hosted by Danny McMillan.
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