lukex

@Simplemart17 @Yuchenj_UW You wrote this with Claude, didn't you?

@Yuchenj_UW Dug through that leaked source this morning. The 15,000 token system prompt tells you everything. Custom diff formats, specific file editing patterns, agent behavior tuned entirely through prompting. The harness isn't just a gap; it's where the actual product lives.

Beyond raw model capability, the real gap in coding tools is the harness. Now that 500k+ lines of Claude Code are out there, every model lab and AI coding startup, including open-source AI labs, will study it and close that gap fast. SF already has Claude Code source walkthrough meetups lol.

@SamBroner Congrats Sam! Welcome to the builder side

This is either brilliant or scary: Anthropic accidentally leaked the TS source code of Claude Code (which is closed source). Repos sharing the source are taken down with DMCA. BUT this repo rewrote the code using Python, and so it violates no copyright & cannot be taken down!

the most entertaining timeline...Claude Code source code has been leaked. here're some upcoming features! h/t @Fried_rice

A CEO from one of our portfolio companies shared this with their team. I’m re-sharing it with their permission, because it resonated and reflects what all founders and CEOs should be communicating. -- We are living through a period of compounding change. And in moments like this, the biggest risk is no longer making the wrong decision. It is moving too slowly while the world moves around you. There are two paths. We can play defense: - Protect what we have - Optimize what works - Wait for clarity It feels safe. It isn’t. Or we can play offense: - Learn faster than the environment changes - Use new tools to solve old problems in better ways - And create entirely new strategies and businesses That’s where the opportunity is. Challenge yourself to do things faster and better than you have ever attempted. Stay uncomfortable. Stay on the front foot.

1000% agree. you don't win your vertical deploying AI to 10x side quests, while your competitors are deploying AI to 10x main quests

@jinglingcookies yes pls!

collated > a list of 60 companies building in the agentic commerce space, across these sectors: cards, standards, tooling, identity, credit, checkout execution, discovery, marketplace, policy control > resources to understand and keep up to date with agentic commerce, includes: agentic commerce infra, cards vs stablecoins, traction, analytics comment down below if you would like access

@levie Been thinking and tinkering on this as well! AI will make data more valuable and kill free APIs. Think it splits into 3 groups: internal data (becomes differentiator/moat), frequently accessed data, infrequently accessed data Discoverability will be a big pain point!

There are some pretty wild downstream effects in a world with trillions of agents using the internet and software. One very big one is what happens with agents with budgets and wallets. There are lots of business models that never ended up working out for the human-based internet that all of a sudden start to make economic sense in an agent-based internet. Think of all the proprietary data and research that’s sitting out there right now behind a paywall that a human will never run into. Finance data, medical research, and so on. Most people won’t sign up for a $100 or $1000 subscription for information they need infrequently. The cost is too high. Equally, micropayments for this data rarely worked at scale because the volume was too low to matter. However, now an agent can have a budget for a specific set of research it’s doing, and the agent might pay $0.1 or $1 to access it in a workflow. And now that data may be relevant in 1,000X’s more use-cases than it was before. Similarly, there are many APIs and tools out there on the web that don’t make sense to have a subscription for, but now an agent may interact with for a specific exchange, and it could cost $.01 or $0.1 per transaction. All of a sudden new kinds of software can get built and monetized that would have been uneconomical before. Some new form of commercial open source, essentially. Obviously lots of infrastructure and agreement across the industry is needed for this -and getting discovered by the agent is going to be a whole new class of search and discovery problem- but there are so many potentially interesting new scenarios here.

@defyneric *5-6 months

a lot of these agent-to-agent ideas are just way too early conceptually they’re cool, but if you’re building products specifically for agents today there’s basically no TAM the smarter approach right now is building agents for humans first we can’t expect agents to start using other agents until humans are actually using agents in the first place at the end of the day the customer is still a human it reminds me of jeff before hyperliquid, back in 2017 he tried to build a prediction market and it failed the idea wasn’t wrong, it was just too early. then polymarket launched years later and it exploded a lot of these agent to agent ideas are similar. the concept is good, but are founders really able to build, raise money, and run payroll for 5–6 years while the market still doesn’t exist?

@ccatalini AI commoditizing execution makes data more valuable It's why Google is ironically taking an Apple walled garden approach when it comes to Gemini/AI

"When execution →0, the scarcity that can still carry meaning is human time & attention. Made by humans transitions into a luxury signal: deliberate inefficiency becomes part of the product because it communicates intent, care, and provenance." x.com/sumiturkude007…

The scariest thing about AI in 2026 isn't some sci-fi scenario. It's watching people you know — people with the same credentials, the same caliber — split into two completely different groups in a matter of months. I've seen it happen firsthand. Stanford grads, ex-Meta engineers, startup founders. Three months ago, they were all roughly at the same level. Now? The divergence is so obvious it's uncomfortable. Some of them got really good at AI. Not just "using ChatGPT" good — fundamentally different in how they think, work, and produce. Their output is compounding. Their depth of insight is compounding. They look like they're playing a different game entirely. Others are still running on the resume they built five years ago. And here's the number that haunts me: 99% of people still use AI at the level of "What's the weather today?" or "What kind of flower is this?" The 1% who figured it out aren't even one group. There's massive variance within them — some are orchestrating AI agents to run entire companies, some use it for research that would take a whole team, some have AI write half their code, some have AI write all of it. The income implications are brutal. If someone uses AI to produce the output of 10,000 people, they're worth 10,000x the salary. Someone who can't figure out a single tool? They might not be worth hiring at all. What really unsettles me is how fast our patience is eroding. The moment we feel someone performs below what AI can do, we don't think "they need training." We think "they're worth zero." Not less. Zero. So the real AI danger isn't AI going rogue. It's the epic, unprecedented amplification of the gap between people — in capability, in income, in relevance. One silver lining: the old hierarchy is broken. People who were once untouchable can now be overtaken by someone who masters AI faster. That door is genuinely open. But if you don't walk through it, you won't just fall behind by a little. You'll become invisible. #AISkillGap #FutureOfWork #ArtificialIntelligence #Productivity

@silver_pump @dgt10011 $1B to shout with isn't too shabby :)

@dgt10011 ngl i respect his contrarian stance against the hype even if its like shouting into the void lol

LeCun has been the most aggressive critic of the transformer/LLM consensus for years, and this is his magnum opus "much of real-world sensor data is unpredictable, and generative approaches do not work well." This basically epitomizes his view that real intelligence cannot come from scaling text prediction alone whether he is right or not, im excited to see a another school of thought come to market that in some ways restores agency back to the physical world. Worth "keeping an eye on it" :)

pretty wild

@jenzhuscott @openclaw Pretty cool to see governments moving fast, necessary given the pace of AI

Has @openclaw been launched for a month yet? Moonshot: KimiClaw MiniMax: MaxClaw Alibaba: CoPaw ByteDance: ArkClaw Tencent: WorkBuddy Zhipu: AutoClaw Shenzhen: OpenClaw hardware stores Local governments: we pay you to deploy 🦞 👀

Most friends in the US/West are just hearing about public OpenClaw installs in Shenzhen, and not this yet Government moving at the pace of startups is a sight to behold

@poezhao0605 Government moving at the pace of startups is a sight to behold

OpenClaw mania in China has crossed from tech hype to government policy. Shenzhen moved first. Now Wuxi's high-tech zone dropped a 12-point draft policy specifically supporting OpenClaw-based development. Compute subsidies up to $42K/year. Full cloud platform subsidies up to $140K. And up to $700K for breakthroughs in embodied AI robots and smart industrial inspection. This is how China scales technology. Government sets the table with money and policy. Companies bring the products.

Anthropic is running a masterclass in negotiation-as-marketing right now. The $200M Pentagon contract represents 1.4% of Anthropic’s $14 billion run rate, up 14x from $1 billion fourteen months ago. This is not a number worth compromising a brand over. Amodei knows this. The Pentagon knows this. So why is he personally publishing a detailed statement, point by point, timed for maximum news cycle impact? Because every headline that reads “AI company refuses Pentagon’s demands on autonomous weapons and mass surveillance” is worth more than the contract. Anthropic just bought the most expensive brand positioning in AI history, and the Pentagon is paying for it. The statement is surgically written. Amodei opens by affirming he believes in using AI to defend democracies. Lists every classified deployment Anthropic pioneered. Emphasizes they’ve never objected to specific military operations. Then draws two narrow lines: no mass surveillance of Americans, no fully autonomous weapons. The framing makes it almost impossible to argue against without sounding like you’re pro-surveillance. The Pentagon’s negotiator called Amodei a “liar” with a “God complex.” The Pentagon threatened to invoke the Defense Production Act and label Anthropic a supply chain risk simultaneously. Amodei pointed out those two threats are contradictory: one says Anthropic is dangerous, the other says Claude is essential. That line will be in every news story for the next 48 hours. It was designed to be. Sen. Tillis, a Republican not seeking reelection, broke with the administration on the record. Said the Pentagon was being “unprofessional” and that you should listen when a company turns down money out of concern for consequences. Anthropic didn’t have to lobby for that. The positioning did the work. Every enterprise buyer evaluating AI vendors just watched Anthropic publicly refuse to let a customer override their safety commitments. For a company selling to regulated industries, that demo is priceless. The 5:01pm Friday deadline is tomorrow. Anthropic will either keep the contract with safeguards intact or lose it and gain something more valuable: permanent differentiation in a market where every other lab said yes.

good for humanity