Building something new. Once, I told a librarian that she'd be out of a job because all books would soon be on the internet. I was 8. SF via Chicago via CR.
San Francisco, CA
Joined November 2008
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Just posted my annual reading recap.
Traveling from SF to Mexico City, Vienna, Budapest, and South Africa, I circled one theme: ideas rewrite the world.
Standouts: Zweig on collapse, MacKenzie on financial models that shape markets.
Link to the blog below. What did you read?
What's old is new. Pretty incredible how little things change in ~200 years. @TimothyTTaylor excerpts de Tocqueville, "Why the Americans Appear So Restless Amid Their Well-Being" conversableeconomist.com/202…
This weekend, at a wedding, I had a sudden realization: The Killers' Mr. Brightside is actually Beethoven. When I told my wife, she thought I might be having a stroke, then she heard it, too.
Listen to it, especially the instrumental bit at the end, and lmk if you figure it out.
A disorienting thought experiment from @satpugnet at the @onewayvc Summit: AI will soon have more thoughts per year than all humans have collectively thought since the beginning of time. What does that mean for our future?
Hard to understand this and put it into perspective.
Anyone else's Dot disappeared from Codex tonight? @OpenAIDevs what's up with that? Still available via chat on web.
Banked restarts should auto-apply at expiry time, instead of just disappearing.
Since we got an unexpected 10am restart I'm now spinning up a bunch of Astra Ultra agents, but if I miss the 1:22pm cutoff I'll be screwed.
Avy Faingezicht retweeted
Do I know any great consumer growth people? Do you know someone I should know?
I'm building a new AI fintech and looking for a founding hire in SF to get it into people's hands. Someone who's all-in on agents, likes the messy early days and figuring out what works. 💰
DMs open.
Do I know any great consumer growth people? Do you know someone I should know?
I'm building a new AI fintech and looking for a founding hire in SF to get it into people's hands. Someone who's all-in on agents, likes the messy early days and figuring out what works. 💰
DMs open.
Whether your browser auto-completes g to gmail or github says a lot about who you are and how you spend your time at work.
Avy Faingezicht retweeted
You’re 25x more likely to be a millionaire than be homeless in the US
everyone thinks for some reason that they are closer to becoming a millionaire than becoming homeless.
Readers added context they thought people might want to know
Recent polling shows a majority of US voters believe they are more likely to become homeless than a millionaire. US data show roughly 23.6 million millionaires versus ~746,000 experiencing homelessness on a given night.
dataforprogress.org/blog/2026/8/13…
investopedia.com/new-report-rev…
hud.gov/news/hud-no-26…
Avy Faingezicht retweeted
Moats in 2026:
- having conviction for more than 5 days
- thinking for yourself
In the age of AI agents writing most of the code, do we care about test coverage, or is that also out the window?
Great things take time.
Our work, like capital, compounds. Congrats, @Erik_Syvertsen and the @usvc_ team!
For 15+ years I've worked with venture funds: 10-year fund lives and waiting for DPI. Today, @usvc_ 's Q3 Schedule TO arrived at my house offering to buy back my shares at NAV. Every shareholder got this same offer. Worth every late night.
A subtle difference I've noticed in Codex in the last couple of weeks is that they're hiding git branching and worktrees from the UI, letting the agents make choices about source control more and more.
This looks very cool. Pointers in your LLM tokens!
You already gave the LLM the answer. So why is it writing it out from scratch?
Introducing a new AI model architecture: Constrained Decoding Models (CDMs)
LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable.
CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive.
Not just a decision model, but a family of 3 CDMs live today:
• Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection.
• Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction.
• Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests.
Built for production:
• 1M tokens of multimodal (text + image) input, 31x larger than Jev
• 77.2% on DecisionBench vs Jev's 72%
• 200x faster, 467x cheaper than frontier LLM APIs
• $0.05/M input tokens. Output is free (yes, even for summarize)
Live on your favorite platforms today:
@OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus
Get 50M input tokens for free (for the first 50 hours) at link below 👀