lukex

co-founder, chief janitor | venture partner

[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."

[Claude-Mem @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.

[lukex @Lukex]

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

[Gergely Orosz @GergelyOrosz]

Sage observation from @karrisaarinen (CEO of Linear)

It now makes SO MUCH sense why I see a bunch of eng teams rebuilt a SaaS vendor in-house with AI, brag about and feel good

They are doing side quests... and they don't even know it. And they are not helping their co win!!

[lukex @Lukex]

@jinglingcookies yes pls!

[lukex @Lukex]

@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!

[lukex @Lukex]

@defyneric *5-6 months

[lukex @Lukex]

@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

[Xiaoyin Qu @quxiaoyin]

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

[lukex @Lukex]

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