Monk-versus-Costco AI Resilience Test
Choose bespoke value over commodity output that automation can reproduce.
- Difficulty
- Moderate
- Time to result
- ~weeks to results
- Steps
- 6
- Confidence
- 96%
The Monk-versus-Costco test separates businesses into two strategic games. The Costco-pizza side supplies an adequate, standardized result at low cost and is therefore highly exposed to automation that can produce the same output faster or cheaper. The Monk side offers a scarce, memorable experience tied to craft, story, setting, access, or personal connection—like eating in a tiny restaurant while interacting with the chef. To apply the test, a business identifies what customers truly value, determines which components AI can commoditize, and chooses whether to compete on efficient scale or deepen the elements automation cannot easily reproduce. For premium positioning, every part of the offer must reinforce the distinctive experience. The framework does not claim robots will eliminate human craft; it predicts that abundant automated output can increase demand for genuinely bespoke alternatives.
Origin
Greg Isenberg used a small Kyoto chef-led restaurant and Costco pizza as opposing models while discussing AI pressure on newsletters on Marketing Against The Grain.
Core principles
- 01Automation wins when buyers care mainly about cost and adequacy.
- 02Bespoke experiences compete through scarcity, story, and human connection.
- 03Generic information becomes easier to copy as AI improves.
- 04Premium positioning requires more than claiming higher quality.
- 05The business must decide whether it is deliberately playing a commodity or experiential game.
How to run it
- 1
Name the purchased outcome
Define what customers are really hiring the offer to do. Separate functional adequacy from emotional, social, or experiential value.
Pro tip Interview customers about what they would miss if the human or crafted elements disappeared.
Watch out Do not equate stated feature preferences with the underlying buying motive.
- 2
Locate commodity exposure
List components that AI or automation can reproduce at acceptable quality and lower cost. Assume generic summaries, templates, and routine transformations will become increasingly available.
Pro tip Test current tools rather than relying on abstract predictions.
Watch out Today's weak automation may improve quickly, so avoid basing strategy on temporary defects.
- 3
Choose the strategic game
Decide whether to pursue standardized scale or a premium, bespoke experience. Align operations and economics with that choice.
Pro tip A commodity strategy can still work when the business owns a genuine cost or distribution advantage.
Watch out Trying to charge bespoke prices for commodity output creates a vulnerable middle position.
- 4
Deepen scarce value
For the premium path, strengthen human access, original stories, proprietary judgment, craftsmanship, setting, or community. Make the distinction observable in the customer experience.
Pro tip Design moments customers will remember and describe to others.
Watch out Surface branding cannot substitute for genuinely scarce value.
- 5
Remove generic dilution
Automate or eliminate undifferentiated work so resources concentrate on the premium layer. Ensure each major touchpoint supports the chosen positioning.
Pro tip Use AI behind the scenes when it improves delivery without replacing the valued human experience.
Watch out Excessive automation can destroy the very interaction customers pay a premium to receive.
- 6
Retest defensibility
Periodically compare the offer with new automated alternatives. Increase differentiation whenever technology closes the gap on previously scarce capabilities.
Pro tip Ask whether a customer can now generate an acceptable substitute with a simple prompt.
Watch out Differentiation is an ongoing strategic practice, not a one-time label.
In the wild
Kieran configured Bard to create a daily newsletter containing only positive stories in the style of familiar business newsletters. Because the AI could customize the selection for one person, a standard one-to-many summary lost part of its value. A visually crafted or community-sourced newsletter remained harder to substitute.
→ The example distinguishes commodity aggregation from premium formats with unique production or information advantages.
A tiny Kyoto restaurant offers more than pizza: diners interact with the chef, observe the craft, and acquire a story worth retelling. A robot may eventually make technically excellent pizza, but it does not automatically reproduce that scarce human experience.
→ The restaurant retains premium appeal even as automated food production improves.
Common mistakes
Competing on generic quality alone
AI can rapidly narrow quality gaps in routine output. Premium value needs scarcity, relationship, proprietary judgment, or a distinctive experience.
Calling a commodity bespoke
Premium language and design do not create defensibility when the underlying result is standardized and easily generated elsewhere.
Rejecting automation entirely
The framework does not require avoiding AI. Automation can remove commodity work and free resources for the human elements customers actually value.
Is it for you?
Best for
It is best for content, service, and experience businesses deciding between scaled commodity production and premium differentiation.
Not ideal for
It is not ideal for essential commodity markets where customers overwhelmingly optimize for price and standardization.
From the transcript
“you should be thinking about how can I make it more like monk and less like a Costco pizza.”
“that commodity game is a bad game to play, and it's getting harder in an AI world because it's easier to copy and paste everything…”
“But I also believe that the bespoke experiences are going to be more and more craved.”
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