
people @a16z, building @speedrun | ex-@riotgames, @birdride, @ohiostate always
sea / sf
Joined September 2021
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SPEEDRUN
APPS
ARE
OPEN
SR008 APPS ARE OPEN. Up to $1M + $10M+ in credits. 12 weeks in SF, Feb through April. Built to help you land capital, customers and talent. Apply by Nov 1: speedrun.a16z.com/apply
for everyone in the back:
"~1 in 3 teams we accept for speedrun are reapplicants"
Tom Hammer 🔨 retweeted
~1 in 3 teams we accept for speedrun are reapplicants
they use the 3-6 months between applications to:
- narrow in on a stronger idea
- find a cofounder
- get to traction
a "no" is temporary
keep building - that's all that matters
NEW: INVESTOR ADVICE FOR APPLYING TO SPEEDRUN (SR008 EDITION)
Every cohort we sit down with our investors to hear what’s top of mind. This time @ndrewlee got in the booth with @kenanhsaleh, @emilybenn12, @seeamshahidnoor, and @tkexpress11 to talk about:
00:00 - what’s changed in apps this cycle
04:15 - team vs. market vs. traction: how we weigh them
08:14 - hot markets vs. ones that feel inevitable
10:36 - spotting the gaps the frontier models leave
13:35 - where speedrun fits in your founder journey
22:26 - how to make your application stand out
30:05 - common mistakes (AI is not your “why now”)
38:46 - the 10-min interview + co-founder dynamics
45:41 - what you get working with speedrun
SR008 apps close Nov 1. Watch the full roundtable here 👇
Work at startups
A retired NASA engineer who had worked on the Space Shuttle program for 25 years was hired by SpaceX at age 62. He described the first week as the most disorienting experience of his professional life.
At NASA, a design change required 3 meetings, 2 committees, a review board, and 6 to 18 months of documentation. At SpaceX, his new supervisor said "if it works, build it. If it doesn't, change it by Friday."
He sat at his desk after the first day and called his wife. He told her he felt like a man who had been swimming with ankle weights for 25 years and someone just cut them off. He could move. He could decide. He could build something in the morning and test it in the afternoon. The constraint that he had accepted as the nature of aerospace engineering turned out to be the nature of bureaucracy.
Within 6 months he had contributed to more design iterations than he had completed in his last 5 years at NASA. Not because he was working harder. Because the time between having an idea and testing the idea collapsed from months to hours. The same brain. The same knowledge. A different operating system.
He described a specific moment where he proposed a modification to a Raptor engine component. At NASA, the proposal would have entered a queue. At SpaceX, the modification was machined by the end of the day and tested by the following morning. He watched his idea become a physical object in 18 hours. At NASA, 18 hours would not have been enough to schedule the first meeting to discuss whether to schedule a meeting.
He told an interviewer: "I didn't get smarter when I went to SpaceX. I got faster. The intelligence was always there. The system was in the way."
The difference between SpaceX and NASA is not talent. NASA has extraordinary talent. The difference is the time between a thought and a test. SpaceX compresses it. NASA elongates it. The same engineer produces 10x more at SpaceX than at NASA because the bottleneck was never the engineer. It was the meetings about the meetings about the work.
Tom Hammer 🔨 retweeted
ALPHA APPLICATION DEADLINE IS 12AM TONIGHT!!! Last chance to apply to the speedrun alpha fellowship, with up to $250K investment in technical students + recent grads.
👉 Alpha.a16z.com
Cannot wait to meet our next class. Could it be you 👀
my annual sf @Techweek_ reminder that you should go through sfo terminal 2 security regardless of what terminal you fly out of. they are all connected and literally never a precheck line
hangin at the new @safeworldai HQ today 🫡
Today, I’m excited to introduce @safeworldai!
Our mission: improve robot safety for the next billion machines.
AI is moving from screens into the physical world. Robots are becoming more capable, more autonomous, and increasingly operating around people.
But more capable robots require more capable ways to test them. 🧵
Today, I’m excited to introduce @safeworldai!
Our mission: improve robot safety for the next billion machines.
AI is moving from screens into the physical world. Robots are becoming more capable, more autonomous, and increasingly operating around people.
But more capable robots require more capable ways to test them. 🧵
Shield AI selects Seattle area to build X-BAT autonomous fighter jet, plans to add 4,000 jobs by early 2030s geekwire.com/2026/shield-ai-…
hosting a brunch in LA w @jamiebyrne and the head of talent at @upfrontvc on startup culture, company building, and the role of advising
my ideal audience is a head of X at a late stage startup, or a functional leader in a large non-tech company, who is interested in advising
i'm still accepting rsvps for those who are interested in being in the room - thursday 10/15, 9a:
partiful.com/e/DRRSAxuu7tPWp…
TypeSafe AI's Diogo Almeida with a16z's Ben Horowitz and Martin Casado on Jev, the model built to live inside software:
Diogo's elevator pitch for Jev is a simple question - where is all the automation?
AI is unbelievably smart, but outside of chatbots and coding agents, it hardly touches any real work. His diagnosis is the industry built models that generate text for humans to read, and software can't consume that output.
Jev reads natural language and returns a choice from a set of options with a confidence level assigned to each, so developers can build programs that reason about intent and make probabilistic decisions rather than relying on human interpretation.
TypeSafe's philosophy is "We build prod, not God."
0:50 "Where the f**k is all the automation?"
2:50 Jev vs. Claude Code and Codex
6:55 Jev is a classifier and classifiers are sick
7:40 Chat vs. code: is Jev a slider?
9:00 Diogo: From mathlete to Kaggle to OpenAI
12:20 "We build prod, not God"
15:55 Reliability over demos
16:55 2021 thoughts: RLHF is AGI?
20:45 Optimizing for the wrong use case
21:50 Is the real world too messy to automate?
25:00 Nobody expected the Jev launch
26:35 Three kinds of reliability
28:05 Good at syntax, bad at architecture
30:00 The inverse SaaSpocalypse
33:40 Why coding agents automate so little
36:05 Probabilistic programming returns
38:45 Jev as the UDP-to-TCP layer for AI
40:20 The 5 stages of grief for embedding AI
41:30 Utopia: AI that actually does what you mean
YouTube: youtu.be/Ut3LOjKNJaE
@CompleteSkeptic @typesafeai @bhorowitz @martin_casado























