2x Founder, Investor(SBI, WVF), Hacker(Bio, Social) Go Blue
Bay Area
Joined August 2026
- Tweets50
- Following362
- Followers32
- Likes25
Pinned Tweet
I'm Henry. Early-stage deep tech & AI investor @ SBI/WVF and I'm a 2x founder/operator, Michigan Ross MBA. I write down what's potential and technical diligence actually teaches you. A quick intro 📷
#AtomicMachines emerged from 6 years of stealth with $250M raised to date, and SF's physical AI summit starts tomorrow. Most of the debate is models vs. robots, people talking past each other. For micro-machines the binding constraint was never the model. It was tooling.
If the flywheel turns only as fast as its slowest layer, the moat is the metrology loop: every operation inspected, errors fed back to the AI as training signal. The 1,000x-faster claim is company-reported, unverified. Watch deployment data, not the demo. That's the diligence.
Henry Liang.xyz retweeted
In partnership with Vinod Khosla (@vkhosla), I’m proud to introduce Reservoir.
Billionaires have owned their cells for years. Starting today, you can too.
Sign up today: withreservoir.com
Quick read, strong recommend: Speedstrap (preprint from the Third Sphere event in SF, out Nov 8).
Must-read for hardware founders: get to revenue, pick your capital wisely, equity is not your only choice. Building in the physical world is harder. Shout out to @shaunabe and team!
Urgent
Data centers are just the warm-up act: Physical AI is most lethal fossil-fuel-killing engine ever built. Electric trucks, factories, and robots will draw 6,200 TWh/yr, liquidating fossil fuel demand
Ep 105 of the Angry Clean Energy Guy podcast is out
theangrycleanenergyguy.com/p…
Henry Liang.xyz retweeted
Where does money invested into the AI buildout actually go?
For every $100 flowing into the supply chain:
- $50 to chips
- $20 to power
- $15 to networking
- $15 to cooling, buildings, and land
More charts in State of Markets II: a16z.news/p/state-of-markets…
Introducing our State of Markets pt 2, along with a companion podcast where we unpack the data and discuss what comes next.
Tech is the everything cycle.
Supply: putting the buildout in context, just passed railroads as % of GDP. The wisdom of Elon is real: the factory (or the datacenter!) is the product.
Demand: diffusion is so, so early. Median AI vendor spending in the top 1% of companies is 8x that of the top 10%. Only about 30% of S&P 500 companies report a quantified AI impact, which means there’s a substantial opportunity in connecting models to a company's data and workflows. Diffusion into companies is one of the main themes of the next 5 years.
We’re entering the agent work period. Only a few million users today, but applicable to billions of internet users with massive surplus created. META/GOOG monetize US users at $200+ per year today. Agent opportunity is much higher.
Mega-trends the next 5 years: Consumer agents, Robotics, Autonomy, AI x bio, Personal health, Diffusion into enterprise, New era of American Dynamism.
Much more in our SoM report here - a16z.news/p/state-of-markets…
@a16z @sarahdingwang @aleximm @santiago__rdz
sf this week is hot. Basically every building with a queue. Only in sf. #sftechweek – at San Francisco, CA
I asked Instinct today for its top 10 most-requested tasks. It wouldn't tell me 😅
So I'm asking you: what's the most mind-blowing thing Instinct has done for you? Looking for inspiration. 👀
A good FDE, like anyone client-facing, should sense where the client's real pain is and solve it creatively. The best ones find the dirty, messy, ugly work nobody wants, or the high-cost, low-value tasks. That's where the startup opportunities hide.
Great post. On point 2, I'd push back a bit: reorg is a spectrum. Not every job to be done needs the org chart rebuilt, and keeping a human in the loop has real value for a while yet. Many workflows get augmented long before they get replaced.
I am gonna say something risky:
Most of the FDEs I've seen are solving BS problems.
1. Existing enterprise workflows were designed around people, not agents.
2. Real AI gains require rebuilding the org chart.
3. Most execs have no incentive to do that, and most CEOs aren't in founder mode.
4. So FDEs automate the status quo, because that's what's easy to sell. But the status quo is stupid and will be obsolete.
5. If you FDE on critical workflows, 1) enterprises are really this dumb to hand off trade secrets? 2) if you know that, shouldn't you start a competing firm?
If you FDE on non-essential AND soon-obselete workflows, did you learn anything meaningful and repeatable?
6. If you are a smart young FDE, why spend your best years automating dying workflows and managing people who fear AI will take their jobs? Shouldn't you start an agent-native firm from scratch in that industry instead?
Analogy would be, instead of teaching everyone to be AI builders within a tech company, you as FDE build agents that auto-ingest meeting notes for PM, QA, front-end, back-end, devops, UX and help each of them write PRD, Figma, and meeting notes faster for their sync meeting, but the right solution should be to shrink roles, hire full-stack AI builders, and kill meetings. You gain lots of experience with your PRD/Figma/standup meeting sync agents but it's a useless skill.
I am not a FDE expert so I might oversimplify things. I am genuinely curious about this topic and welcome any critiques and comments.
One line I keep coming back to: data compounds, algorithms commoditize. The moats I've seen win are physical infra, proprietary datasets, sticky workflow and regulatory lock-in... things that get harder to replicate over time.