Shopify CEO Tobi Lutke explains Goodhart’s law and why he doesn’t like KPIs or OKRs
“Goodhart’s law is real. The moment a metric becomes a goal, it’s no longer a useful metric… No metric by itself is a complete heuristic for a complex business. There’s a million different tensions in a company, and you can’t keep all of them in harmony by optimizing for one thing.”
For this reason, Shopify doesn’t use KPIs or OKRs. But as Tobi explains, this doesn’t mean they don’t value data and metrics.
“We are extremely data informed. We have invested enormous amounts of money and time into systems that give us basically everything at our fingertips… But what Shopify attempts to do is just not over-fit for what’s quantifiable.”
People love optimizing for highly-quantifiable things because there’s immediate gratification that comes from seeing a number go up. But Tobi thinks that the most important aspects of a product are rarely quantifiable:
“The overlap of the most valuable things you can do with a product and the things that happen to be fully quantifiable are like maybe 20%. Which leaves 80% of a value space unaddressable by the people who only look at quantifiable things.”
He continues:
“Shopify is comfortable with unquantifiable things like taste, quality, passion, love, hate… The sort of deep satisfaction that a craftsperson feels when they’ve done a job well is actually a better proxy if you allow it to be.”
They then have robust analytics systems that tell the company if something’s wrong or a new rollout breaks something.
“We think about it as a cockpit for a pilot. The decisions are still made by pilots, and we think this leads to better results… I think there needs to be more acceptance in business of unquantifiable things… And then metrics take a support function.”
Source: @lennysan (Feb 2025)
Shopify isn’t really SaaS. It’s a headless walled garden of APIs whose real value is the business logic, operational workflows, payments, and ecosystem embedded deep in those APIs over time.
People dramatically underestimate how hard that is to recreate. You can’t just vibe code your way into replacing it.
Today is a hard day. I shared this note with the @linear team today: We’ve made the difficult decision to increase our workforce. This is not a cost-cutting exercise or a reflection of anyone’s performance. We’re simply reimagining every role for the agentic AI era. We’re hiring. We’re sorry about that.
Pues ya tenemos el primer #githubday en A Coruña!! El día 22 de mayo por la tarde, si estás en la ciudad o alrededores anímate!! C.C. @david_bonillaluma.com/bdzu56ru
"I have not looked at the ticker in April.
The ticker has nothing to do with the company.
I work on the fair market value of the company.
The ticker is just other people's game to make trades based on their few assumptions of a future compounding fair market value." @tobi
What do you know now that you wish you had known when you went public about your relationship as CEO to the "the ticker"? @eldsjal@klarnaseb@levie@mcannonbrookes@jeffiel@arielcoco@RamaswmySridhar@lefkofsky
Today's controversial take.
Everyone hates meetings so you make the meetings shorter. Now you never get to a conclusion so you need a follow-up meeting. Let's just take the time to close it out and move on.
I want more 1-hour meetings.
I'm fascinated:
56 weeks is the ETA for the embassy to review and respond an email related to citizenship. No case number to track, no site to track window of processing, and email follow-ups discouraged.
just... how? isn't it interesting that something like this exists?
I can't imagine that people running it are happy, and I choose to believe that they've tried to improve it but something got in the way... I find it interesting to see what could be happening to allow something like this
Meet Cooper, the dog…also the jock, the vet and the dramatic actor. 🐶
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I'm organizing a meetup to talk about Product LLMs "hands on LLMs"
- When: 16th July
- Tinybird offices in Madrid
- 2 Talks
- How we teach LLMs to do analytics
- TBD
Signup here -> lu.ma/59vgcge9
How lucky are we? To belong to the generation that got the before and after for personal computing, internet, smart phones, social media, and now AI. Can you fully understand something without knowing what was there before? How will these decades be remembered?
Let your documents capture the back and forth on your decisions, not just the decision. Helps immensely to build trust - and saves A LOT OF OBVIOUS questions :)