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 x.com/t_blom/status/20608063…

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)

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

Echoing this. My 'aha' moment with Al is internalizing open-source libraries to make them faster and safer. Lately I'm exploring @leanprover with Claude Code, utilizing it both for formal verification and as the most concise spec for agents (maths) x.com/karpathy/status/202347…

Thanks to good people at @AnthropicAI we now have an official MCP for Excalidraw! Take it for a spin on @claudeai (search for Excalidraw in Connectors, or use in Claude Code and elsewhere). More to come. ✌

With AI, Working code is a low bar. Secure by Design. Elegant by Design.

Really refreshing to see how sync engine Jazz handles decentralized permission in CRDT. With crypto signature, the chain of edits is verifiable like a blockchain. Check against the whitelist of who can read/write the values. (another example of crypto more useful outside CT)

There is no way @claudeai talk about NEA photocathodes when asked to build a landing page, unless it is leaking response of other users's private query

with $NET now it is actually possible for @Cloudflare to pay out for damages for each 5xx on them

The more I realize AI can do my job, the more I feel I should focus on what humans are good at. If I'm not getting enough sleep, I'm definitely doing something terribly wrong

Fund in my Coinbase is still locked with random API error. The non-existent CS motivates me to self-custodial, but wait, I can't

Today developers are shaping agents with skills shared on Github. Very soon it the COO office will be interviewing, onboarding, assigning, reviewing and laiding off agents like the HR today

Sandboxing is no longer just a best practice --- it's a core part of the agentic workflow

Perks for WFH in Singapore What should I stream when claude code is doing the work

The takeaway nobody wants to hear from yesterday, is that perps are a fundamentally unsound market foundation. Just like options markets outsizing equities markets in tradfi, it's unhealthy to have perps markets outsizing spot markets in crypto

As we seen in @shadcn I believe generally there are lots of room to consolidate packages into a few primitives (like radix-ui) and get AI to generate customized libraries / components in order to to boost performance, reduce bundle size and minimize dependencies (attack vector)

🔥Had one of the more productive sessions with AI-assisted coding. - Trying to clone a open source library, swapping the core dependencies to sth else. - As the test spec (evals) is well specified, once I copy them into the repo, AI is able to come up with own implementation seamlessly - Ask AI to generate benchmark (another evals), and just keep pushing it to optimize the performance - Now I have a library that I fully control, well fit into my codebase with no extra dependencies (security vector). Best part is I can quickly identify what doesn't make sense in the architecture and gather data points on the cost (latency) of each to move forward