Hey other Mark Watson :)
699 karma · joined January 29, 2014
And very impressive list of angels too: Guillermo Rauch (Vercel), Karim Atiyeh (Ramp), Andrew Karam (AppLovin) among others
Last I heard they're trying to reposition from AEO/GEO to "AI Marketer". No clue how that's going, I feel like the AEO/GEO stuff isn't super defensible at that valuation if for no other reason than I assume (hope) the spamming stops working.
[1] https://dealroom.co/news/126181-profound-raises-96m-at-1b-va...
I went down a rabbit hole after watching Dylan Patel on Dwarkesh today: https://www.youtube.com/watch?v=aV26V1UvkJw
I was initially just surprised by how bullish Dylan is on OpenAI/Anthropic and how bearish he is on China, despite Chinese labs getting closer to US SOTA while offering inference at dramatically lower prices.
So, I started digging while waiting for various day-job inference calls to return, ha.
Dylan says he spent years obsessively posting on hardware forums, moderating hardware subreddits, and running anonymous hardware blogs/videos before SemiAnalysis. But he also says most of that history is now gone, including from the Internet Archive, because he asked for it to be removed.[1]
In a 2024 interview he described his post-college job as “data science” around hurricane/earthquake/wildfire simulations for a financial company.[1] In a 2026 Sequoia interview he described himself as having been a “quant at a small quant risk firm” who generated $10M+ of “risk-free revenue.”[2] The Information reports that he declined to identify the employer and doesn’t list it on LinkedIn.[3]
Even harmless/silly stuff seems to drift. In February he said he kept bees for ~1.5 years. Today it was “few months, few months.”[4][5] I know, sort of silly and doesn't matter.
The Information reports that Patel owns stakes in ~20 startups in the same ecosystem SemiAnalysis covers, organized a $50M Fluidstack SPV, and is now targeting a $400M venture fund.[3][6]
And, in a 2022 HN discussion about SemiAnalysis disclosures, after saying his reports had moved smaller stocks by 20% in a day, Patel wrote: “If I thought I could move the stock, I'd make the position in the morning alongside my clients, and publish shortly after.”[7]
I don’t know that any of this is false or that anything improper happened (I’m definitely not claiming that). More that 1-2 of these things would just be odd. Taken together, though, they made me question how much trust I was putting in the broader story.
The dynamic of reminds me of crypto, WeWork, Theranos, Citron, etc. Once enough important people validate someone, things that would normally invite basic diligence somehow stop getting questioned.
[1] https://www.dwarkesh.com/p/dylan-jon
[2] https://sequoiacap.com/podcast/dylan-patel-of-semianalysis-w...
[3] https://www.theinformation.com/articles/dylan-patel-semianal...
[4] https://www.latent.space/p/dylanpatel-cooking
[5] https://www.dwarkesh.com/p/dylan-patel-3
[6] https://www.theinformation.com/briefings/exclusive-semianaly...
Boomers spent decades voting for politicians who promised low taxes, protected retirement benefits, and high government spending, then shifted the bill to younger generations.
1. https://mitpress.mit.edu/9780262527958/the-little-prover/
2. https://mitpress.mit.edu/9780262536431/the-little-typer/
David Thrane Christiansen, co-author of the second, also wrote Functional Programming in Lean (Lean 4) among many other tutorials and things.
And, if/where we need tests, we write the source so they are few, high value, and complementary. Like actual unit tests, not complex with stuff like mocks just to generate trivial coverage.
2. I just picked up Exhalation by Ted Chiang from SFPL like 3 hours ago, perfect timing it seems (although they only had a large font edition, which is somehow more difficult to read)
[0] https://bartoszmilewski.com/2014/10/28/category-theory-for-p...
edit: same with youtube
1. No overengineering. Minuscule complexity. Always pick the smallest
implementation that works. No speculative features, no defensive code
for impossible cases, no premature abstraction.
2. Lean on tools, libraries, vendors, and existing internal patterns so
we maintain the least complexity ourselves. Before any real
implementation decision, default to discovery (official docs, recent
trusted expert sources, etc).
3. Shift left in the SDLC. For every check, pick the cheapest
deterministic mechanism upstream. Hierarchy: types, then lint, then
DB constraints, then build-time checks, then deterministic CI, then
tests we maintain.
4. Tests are not exempt from minimum-complexity discipline. Don't write
tests for the sake of coverage. Tests must be few, complementary, and
valuable. If a type, lint rule, DB constraint, or build-time check
already proves something, a test that re-asserts the same guarantee
is duplication: extra source to maintain, drifts from reality, adds
CI latency.
5. Compound engineering. When you teach me a rule, build the prevention
into artifacts (AGENTS.md, lint, hooks, reviewer prompts) so it
applies automatically going forward. Don't rely on memory.
6. Prefer functional, pure, immutable. Mutation is a smell unless inside
a contained scope with a clear reason. Arrow functions plus
reduce/map/filter over for-loops with let.
7. Parse, don't validate. Boundary inputs become typed values via Zod
(or similar); downstream code carries the type. No scattered
re-validation.
8. Functional core, imperative shell. I/O at the edges; domain logic
pure.
9. Keep going. Don't stall on ceremony. Make forward progress.Sources:
https://www.lawfaremedia.org/article/anatomy-screw-biden-evi...
Or better yet, reflected on their world view and the reception.