lukex

co-founder, chief janitor | venture partner

[Bill Gurley @bgurley]

WeChat has been a little quiet on AI front & perhaps even falling into being considered a laggard. But this week, Pony Ma presented a new vision on how to turn "mini-apps" (still no real equivalent in US) into AI handshakes. Manny partners announced. Could be a powerful move. Read more below.

[lukex @Lukex]

@ccatalini @openstandard Great analysis sir!

[Christian Catalini @ccatalini]

1/ Today, more than 140 companies, most of which compete fiercely with one another, agreed to back the same stablecoin. The vehicle is @openstandard, a new and deliberately independent company launching Open USD, or OUSD, and positioning it not as anyone’s product but as neutral infrastructure for payments, trading and the internet economy.

[Thierry from arvy 🇨🇭 @ThierryBorgeat]

🚨 SpaceX just pulled off the greatest financial engineering feat of the century. In about a week.

Here's everything that happened, in order:

– Folded xAI into a rocket company, turning "space logistics" into an "AI infrastructure" story overnight
– Priced the IPO at a flat $135. No book-building, no range. Take it or leave it
– Floated just 4% of the company. 556 million shares against 13 billion
– Raised $75 billion at a $1.77 trillion valuation, near 100x revenue
– Lobbied to get into major indices in ~15 trading days. Amazon took years. Forced buying, by law
– Handed an unusually large slice of the float to retail. Tiny supply, an army of buyers
– Watched the stock rocket past $200, up nearly 20% in a single session
– Saw ~46% of the entire float trade hands in one day
– Then announced a $60 billion all-stock buyout of Cursor, the AI coding tool
– Structured it so the higher the stock trades, the fewer shares it has to print to pay

A company losing $4 billion a quarter is now buying AI startups with paper it manufactured out of a 4% float.

The scarcity that pumped the stock now makes its shopping spree cheaper.

This isn't aerospace. It isn't even AI.

It's the finest financial engineering of the century, and it's only week one.

[lukex @Lukex]

@Cointelegraph Actual space stuff is a drop in the bucket compared to AI apps and infra 😂

[Andrej Karpathy @karpathy]

This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time.

I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!

[Brian Armstrong @brian_armstrong]

Good take

My guess is
- demand for intelligence is near infinite
- but 80% of workloads will be running on 99% cheaper models within 12-18 months
- 20% of workloads will still run on latest gen models where IQ maxing is important (scientific breakthroughs, higher level ochestrator agents?)
- rough analogy might be what % of macbooks or gaming PCs sold have the maxed out specs for CPU/GPU, prices are falling much faster than Moore's law here though
- this leads me to think the limiting factor will be energy and compute, not better models

At Coinbase we're working hard on routing prompts to cheaper models where appropriate, and in some cases have been able to keep costs roughly flat, while token usage continues to grow exponentially.

[Spencer Yang @spenceryang]

SpaceX may soon become one of the first companies to IPO at a $2T valuation, bringing together SpaceX, xAI, and X.

I started my post-college career at Twitter. I watched the platform evolve, grow, struggle, reinvent itself, and even later worked out of its former San Francisco office after it became a co-working space run by BLK71 SF.

To mark the moment, I shipped TrillionMarketCap: a live registry of the assets, companies, commodities, and networks large enough to be measured in trillions.

Gold. NVIDIA. Apple. Bitcoin. SpaceX.

[Spencer Yang @spenceryang]

https://t.co/E44BsFddpZ

[Allie K. Miller @alliekmiller]

The most expensive mistake in enterprise AI right now: treating FDEs as your whole transformation plan.

Forward deployed engineers (FDEs) are important for custom deployments, but they won’t fix the change management issue most enterprises are facing.

It’s likely more the former that Anthropic and OpenAI will continue to prioritize (and hire into the thousands, who knows). Beyond performance and cost, it’s systems integration, ROI, and literal usefulness that drive revenue and stickiness.

*However*

External FDEs, in my opinion, will not make your company an AI-first company.

You can have the sleekest multi-agent orchestrations and still have the majority of your employee base hating AI, avoiding AI, and distrusting leadership decisions on AI.

And we already know this because we see this in traditional SaaS too: you can customize the heck out of your Salesforce deployment, but that doesn’t mean your sales team will improve their data hygiene or even attempt to change the way they track and grow with it.

Buying a fancier car doesn’t mean you magically learn to drive better overnight.

If you’re an enterprise exec and FDEs are sold as the immediate and sole solution to your company transformation woes, walk away.

It’s the combination of tech *and* people enablement *and* process reinvention that compounds into actual business outcomes.

Large complex enterprises will stall out if they only prioritize the first.

[lukex @Lukex]

@yoheinakajima consistently surprises and delights, the man IS the bleeding edge of AI use cases

[Yohei @yoheinakajima]

ran openai's 663 open roles through chatgpt to ask what one could infer about their strategy

nothing particularly new, but it worked well

[tae kim @firstadopter]

Oh look! Anthropic's entire "we are delaying Mythos" narrative was marketing hogwash.

Kudos to FT for confirming what was obvious. Anthropic simply doesn't have the compute.

FT: "Multiple people with knowledge of the matter suggested Anthropic was holding back from a wider release until it could reliably serve the model to customers."

[CMEM.ai @Claude_Memory]

SIXTY THOUSAND (60,000) STARS ⭐️ TODAY

ranked amongst legends, #301 and climbing

[Charly Mwangi @charlythuo]

Just spent a week in China deep diving the general-purpose robotics ecosystem.

Key takeaway: while we’re vibe-coding… China is vibe-manufacturing !

A few things that stood out:

1) China has cracked “vibe manufacturing”
Startups are spinning up hardware like we spin up code.
AGIBot (3 years old) has already built ~10,000 robots.

2) The entire stack is being built in parallel.
Every serious robotics company is full-stack: hardware + controls + foundation models.

3) Data factories are real and massive.
Hundreds to thousands of people teleoperating robots 24/7 to generate training data.
In some cases, the government is literally buying robots, generating data, and selling it back to companies.

4) The supply chain is overwhelming.
Foxconn, BYD, LYitech - everyone is plugged into the same dense, hyper-responsive manufacturing base.
This is why iteration speed is so high.

5) Structural paradox: Labor is both tailwind and headwind.
Cheap, abundant skilled labor powers the supply chain…
But it also makes automation harder to justify domestically.

→ Weak ROI for robotics inside China
→ Strong incentive to export

6) Hardware is impressive. Intelligence is not (yet).
Amazing kinematics—dancing, acrobatics.
But limited ability to execute simple instructions reliably.

7) Everyone is moving up the stack
Every major CM/ODM is building their own robots—humanoids + wheeled.
Today’s suppliers will be tomorrow’s competitors.

8) Dexterity remains unsolved
Lots of prototypes. Very few real demos.

So what does this mean?

Physical AI requires strength in both bits and atoms.

Right now:
China → dominates atoms (manufacturing, supply chain, scale)
US → leads in bits (models, autonomy, software)

We are dangerously behind in atoms.

If we want to compete, incrementalism won’t cut it.

We need to:

- Build depth and breadth across the electro-mechanical supply chain
- Scale CMs / ODMs / JDMs domestically
- Move 100x faster, think 100x bigger on scaling manufacturing infrastructure

Hats off to those doing their part to advance domestic manufacturing supply chain - @makematterco, @VulcanForms, @brightmachines, @thebotcompany @gs_ai_ , @MytraUS, @mind_robotics, @tesla_optimus, @atomic_inc, @Senra_Systems, @pathrobotics, @machinalabs_,@figure_robot, @HadrianInc , @agilityrobotics

[Peter Steinberger 🦞 @steipete]

I'm working on character evals and noticed that Claude would constantly pick itself as #1, so I removed the model names from the judge and changed things.

[lukex @Lukex]

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

[lukex @Lukex]

@SamBroner Congrats Sam! Welcome to the builder side

[Gergely Orosz @GergelyOrosz]

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!

[lukex @Lukex]

the most entertaining timeline...Claude Code source code has been leaked. here're some upcoming features!

h/t @Fried_rice

[Josh Kale @JoshKale]

Anthropic just accidentally leaked Claude Code’s entire source… seriously 😳

Buried in the code are 4 secret features they haven’t announced yet.

Here’s what’s coming:

BUDDY
- A Tamagotchi-style AI pet that lives next to your input box
- 18 species. Rarity tiers. Shiny variants. Permanent personality.
- Teaser drops April 1. Full launch May 2026.

KAIROS
- “Always-On Claude.” A persistent agent that runs across sessions.
- Watches, logs, and proactively acts without you typing anything.
- Has a nightly “dreaming” cycle that consolidates its memory.

ULTRAPLAN
- 30-minute deep planning sessions in the cloud.
- Claude explores and builds a plan. You approve or reject in browser.
- Can “teleport” the session to your local terminal when ready.

COORDINATOR MODE
- One Claude spawns multiple worker Claudes in parallel.
- Workers report back with status, token usage, duration.
- Multi-agent orchestration built directly into the CLI.

This is the compiled code behind feature flags. They’re actively building all of this in secret.

[Alfred Lin @Alfred_Lin]

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.