
🤝Fractional CTO/CISO @fractalboxdev Building secure, private and compliant-by-design solutions for agents
Base in Singapore, from HK
Joined July 2022
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debuggingfuture retweeted
Only AI can keep up with AI. That's what will guide the entire security model of the next decade.
Replying to @devanshmehta
Check out those cool research ideas at @SafeWithAtlas
docs.google.com/document/d/1…
Replying to @trq212
This post-processing workflow is incredibly inspiring.
I'm wondering how you use Claude to direct product demos—like having it go through user flows like typing in the terminal or clicking on Mac apps—and then stitch the screencasts together with zoom-in effects and overlays?
This is the actual bottleneck. The models are smart enough already. What is missing is the company-specific context locked in senior people heads. Whoever cracks knowledge extraction at the company level unlocks the rest.
As you work on this, please consider using GBrain as your OSS retrieval layer
xitter.cf/t_blom/status/20608063…
Imagine replacing 90% of your employees with a team of geniuses who have no idea how your company operates.
Total chaos. Nothing works.
That’s what AI feels like today.
The missing piece is extracting all the domain knowledge from people’s heads and providing that as structured context to the models.
debuggingfuture retweeted
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)
Many case 3d animations really helps understanding how things are linked together from different perspectives
It's pretty insane how AI has been transforming the way I study Math. On top of @karpathy 's wiki idea, I can immediate generate visualization and generate @leanprover programmable proofs to keep myself engaged and really ponder the concepts



