Problem-Obsessed AI Execution
Anchor on a few problems, test solutions quickly, and execute winning bets deeply.
- Difficulty
- Moderate
- Time to result
- ~ongoing to results
- Steps
- 6
- Confidence
- 98%
Problem-Obsessed AI Execution separates strategic focus from solution speed. A team first agrees on the singular problem, or small set of problems, that matters most. That stable anchor allows the team to use AI aggressively to generate, evaluate, and iterate through many possible solutions without becoming directionless. Leaders then choose a few concerted bets and execute them deeply rather than repeatedly issuing new strategies. The mechanism preserves consistency for the people doing the work while retaining AI's advantage in exploration and iteration. Ideas unrelated to the agreed problem are deferred, even if they appear exciting. Strategy changes only when evidence shows that the problem definition or chosen bet is wrong—not merely because another prompt produced a new possibility.
Origin
Extracted from Marketing Against The Grain when the hosts discussed the danger of changing too much because AI makes analysis and strategy creation unusually fast.
Core principles
- 01AI speed must be constrained by a stable problem definition.
- 02Teams can test many solutions without constantly changing strategic direction.
- 03A few concerted bets deserve deeper execution than a broad field of ideas.
- 04Consistency protects teams from the disorientation of excessive strategic churn.
How to run it
- 1
Name the Core Problem
Reach explicit agreement on one or two business problems that deserve sustained attention. Describe the observable outcome that would indicate progress.
Pro tip Phrase the anchor as a concrete failure or constraint, not a preferred tactic.
Watch out A vague objective will not filter distracting ideas effectively.
- 2
Hold the Problem Stable
Keep the core problem consistent long enough for the team to investigate and execute. Distinguish changes in proposed solutions from changes in strategic direction.
Watch out Constantly redefining the problem disorients the team and invalidates learning.
- 3
Explore at AI Speed
Use AI to generate, research, compare, and test multiple ways of solving the agreed problem. Move quickly through weak approaches.
Pro tip Ask for competing mechanisms rather than minor variants of one idea.
Watch out Fast ideation can create a false sense that every option deserves implementation.
- 4
Choose Concerted Bets
Select a small number of solutions with the strongest evidence and strategic fit. Make the choice visible to everyone responsible for execution.
Pro tip Prefer a couple of bets that can receive sufficient depth.
Watch out Too many simultaneous bets recreate the loss of focus.
- 5
Execute in Depth
Give the chosen approaches enough time, ownership, and resources to produce interpretable results. Track outcomes against the original problem.
Watch out Do not abandon a bet merely because AI generated a newer idea.
- 6
Reassess From Evidence
Change the solution, and if necessary the problem definition, only when execution evidence supports the change. Capture what was learned before moving on.
In the wild
A company agrees that its critical problem is leads failing to become customers. The team uses AI to investigate qualification, handoffs, messaging, routing, and outreach, rapidly testing several solutions while keeping the conversion problem fixed as the strategic anchor.
→ The team gains speed in solution discovery without being pulled into unrelated AI-generated initiatives.
Common mistakes
Changing Strategy With Every Prompt
AI can generate persuasive new strategies faster than a team can execute them, creating churn and confusion.
Exploring Without an Anchor
Unfocused experimentation produces breadth without accumulating learning against a shared objective.
Running Too Many Bets
Spreading effort across many ideas prevents the depth required to evaluate or implement any one solution well.
Is it for you?
Best for
Leaders and teams who can generate ideas rapidly with AI but need a stable mechanism for focus and execution.
Not ideal for
Emergency situations where the underlying problem itself is changing too quickly to remain a useful anchor.
From the transcript
“So I think there's like a balance in the speed you can move and then having some concerted bets.”
“If all those things, you should believe in a couple and really ensure that you execute in real depth in those things versus going too…”
“You have to be problem-obsessed to anchor you into the things where it's solving.”
From the episode
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