I can’t stand the smell of smoke, so I don’t have a dog in this fight, but I gotta say:
Banning outdoor patio smoking while turning a blind eye to rampant public use of narcotics – for all the families and children to witness – is peak SF brain rot.
SFGATE: El Rio, Zeitgeist and more push back on new SF bar smoking ordinance https://www.sfgate.com/sf-culture/article/san-francisco-smoking-ban-22247800.php?taid=69fe47cece5385000126c816&utm_campaign=trueanthem%2B3984&utm_medium=social&utm_source=twitter

I've been coding for 40 years. Here are the top 5 things I wish I knew when I started.
1. 90% of the job is debugging and fixing, not creating new code. Which is still fun if you're good at it.
I used to think programming was mostly writing fresh, clever stuff. In reality, most of your time is spent in other people's (or your own past self's) messy code, chasing down why something that "should" work doesn't. Get really good at debugging early. Learn assembly reading, call stacks, and kernel debuggers. It pays off hugely. The best engineers I saw were absolute magicians at this.
2. Manage complexity from day one (ie: don't write slop and "fix it later" if it goes somewhere).
Very early on, I'd hammer out code and refactor afterward. Big mistake. Now I start with clean, skeletal structure (minimalism first) and flesh it out carefully, with AI or not.
Messy code compounds and becomes unfixable. Upfront discipline on architecture, naming, and simplicity saves enormous pain later, especially in large systems like Windows.
3. Tools and processes matter more than you think
We suffered with basic diff/manual deltas instead of modern source control like Git. Branching, testing, and good tooling would have made porting and collaboration way smoother. Invest in your environment, automation, and reproducible builds early. Good tools amplify your output; bad ones (or none) drag everything down.
4. Understand the problem and existing code deeply before writing
Don't jump straight to coding. Map out the problem, study what's already there (you'll inherit a lot), and plan. Low-level knowledge (hardware quirks, alignment issues on different architectures like MIPS/Alpha) was crucial. Also: assert early and often. It forces clarity.
5. People, politics, and "the right tool for the job" beat pure tech arguments.
Brilliant engineers still argue endlessly. Sometimes it's about ego, not merit. Learn to spot the difference and "steer" the conversation rather than "winning" it.
Bonus from experience: Side projects like Task Manager (started at home because I wanted the tool) can become your biggest hits. Ship small, useful things often. If you're just starting, focus on fundamentals, patterns over syntax, and building resilience for the long haul. It's going to be a wild ride, but the fundamentals still matter.

Seattle Turns Hostile to the Great Businesses It Made
Starbucks is moving jobs from Washington state to Tennessee, and it isn’t alone in looking elsewhere.
By Howard Schulz
"Washington state has been my home for more than four decades. I arrived in Seattle with dreams and ambition and ended up building Starbucks into a company known around the world. Many Pacific Northwesterners joined me in shaping the culture, benefits and brand of Starbucks—contributing not only to a business, but also the civic and entrepreneurial life of the area.
I am no longer a resident of Washington. My decision to leave had much to do with family choices and my stage of life. Still, I feel a responsibility to speak up about the business and job climate in a city and state that gave me so many opportunities.
Washington’s economic story over the past half century is extraordinary. Microsoft, Amazon, Costco and a host of other new companies transformed the state into a global center of technology, innovation and logistics. Entrepreneurs exported ideas worldwide. Capital flowed. Wages rose. Imported and homegrown talent flourished.
That ecosystem worked because risk‑taking was rewarded, growth was possible, and civic leadership—while imperfect—understood that private enterprise wasn’t the adversary of the public good. It was one engine for improving the public sphere.
That ecosystem is fractured today. Seattle and much of Washington face serious problems: chronic homelessness, disorder in core business districts, persistent budget deficits, declining public-school outcomes and a slowing technology hiring cycle. These challenges aren’t unique to the state—but Washington’s response to them is.
Seattle’s mayor, Katie Wilson, has chosen to cast business as a foil rather than a partner. Her socialist rhetoric vilifies employers, even while she continues to rely on them for revenue. She has encouraged residents who disagree with her policies to leave.
In the state capital, the Legislature and governor have confronted difficult fiscal trade-offs by emphasizing taxation rather than reform or performance management. The theory appears to be that prosperity can be mandated through redistribution rather than generated through growth.
Washington has a broken tax system. The reliance on sales taxes—10.55% in Seattle—is deeply regressive. The state needs to rewrite its tax code across the board in a way that ensures people and businesses alike pay their share.
But instead of reform, those in power have opted to increase the burden on businesses and successful entrepreneurs in ways that discourage them from growing within the state—at a moment when Washington’s economic situation is growing more fragile.
Microsoft and Amazon—once hiring engines—have slowed recruitment and reduced head counts as they race to build data-center capacity and compete globally. Starbucks recently announced it will shift hundreds of corporate roles to Tennessee.
These companies imported global talent at scale for decades, anchoring an interconnected system of suppliers and startups. As those businesses reduce their local role, Seattle has no clear answer to the question of what will provide the next set of jobs and revenue growth.
Cities and states don’t decline overnight. They drift when public safety, fiscal stability and economic vitality deteriorate together. Downtown vacancies reduce foot traffic. Declining foot traffic weakens small businesses. Employment falls. Revenue shrinks. Services erode. Confidence—something that’s hard to build and easy to lose—begins to evaporate.
Entrepreneurs are accustomed to accountability: If we fail to deliver value, we lose customers. If we misallocate capital, we absorb the loss. Government, too, should be judged by results, not intentions. In Washington, steadily increasing government spending hasn’t delivered commensurate results on a range of issues, from addressing homelessness and drug addiction to poor prospects for new high-school graduates.
Entrepreneurs take risks others won’t. We build before certainty exists. We hire before revenue is guaranteed. We invest locally, pay taxes and support civic institutions. When our companies succeed, entire regions benefit. America can’t afford to forget that.
Leaving doesn’t mean abandoning. My family foundation remains invested in Washington’s future, seeking to help the next generation achieve economic mobility and prosperity. But that future is linked to economic growth and job creation. Across the country, other states are competing for capital and talent by simplifying regulation, reforming tax systems and investing in workforce development. One important initiative comes from the bipartisan National Governors Association, helping states craft pro-entrepreneurship policies.
I hope Washington’s leaders will embrace these policies and forge a new compact—one grounded in job creation, sensible taxation and accountable public spending. Washington once embodied the future of the U.S. economy, and it can again. But the current government needs to learn that future entrepreneurs won’t be attracted by ineffective public systems, especially when joined with policy and political rhetoric that demonize businesses.
Mr. Schultz is a former CEO and chairman emeritus of Starbucks."

Re https://www.latent.space/p/unsupervised-learning-2026
The amazing episode that inspired this article.
@swyx @jacobeffron

this article is long but worth chewing on. tldr:
last week garry merged 14 PRs in 72 hours. 29,000 new lines. he calls this a ratchet: every agent coding session ships tests, docs, and evals alongside the code. each change comes out more solid than the last. the pattern lives in gstack.
i've been seeing this in a few places lately. three weeks ago steipete (behind openclaw) ran 50 codex in parallel and closed 4000 issues. open-sourced it as clawsweeper. same shape, basically.
side by side: agents are loops, humans are events. humans get tired, get distracted, forget. agents don't. or really, the records they leave don't. the systems that actually compound in the agent era are all this shape: every loop ratchets forward one notch, and nobody knows where it stops.
result: faster, more reliable, complexity ceiling pushed up.
if the article felt too technical: just add "and write tests too" to every codex prompt. been doing it this week, the project feels totally different.
Garry Tan: http://x.com/i/article/2054062662225440768

Trump had one of his worst mental health episodes yet last night, posting over 55 times in 3 hours. Here is the list:
10:15 PM - Accuses Obama of attempting a coup in 2016
10:15 PM - Says Obama worked with CIA to overthrow Trump
10:15 PM - Reposts tweet saying Obama is a “traitor” and that he should be arrested
10:22 PM - Attacks dominion voting systems for 2020 election saying they switched votes
10:22 PM - Says Fulton County, GA had their 2020 fraud exposed (there was none)
10:23 PM - Accuses Obama of personally making $120 million from Obamacare (wtf?)
10:23 PM - Cites quack lawyer Sidney Powell on the 2020 election
10:24 PM - Posts fake JFK Jr account that says Obama wiretapped Trump Tower
10:27 PM - Demands Senator Mark Kelly resign
10:29 PM - Claims neither Biden nor Harris were in charge of the Biden admin
10:29 PM - Attacks Fulton County, GA again
10:29 PM - Posts Fox News clip of Rep Ro Khanna
10:30 PM - Demands Jack Smith be arrested
10:30 PM - Accuses Obama, Clinton, and Comey of treason
10:39 PM - Reposts a tweet from a MAGA account saying they have secret intel proving Clinton and Obama committed crimes
10:39 PM - Reposts a MAGA tweet saying Hillary Clinton should be sent to Haiti
10:40 PM - Says the DOJ is “working hard” to arrest his enemies for treason
10:40 PM - Reposts a tweet attacking his own DOJ and Todd Blanche for no arrests of political enemies
10:40 PM - Posts a TikTok video of people stealing from a convenience store
10:41 PM - Posts a TikTok of someone taking a Door Dash order
10:41 PM - accuses Obama, John Brennan, and Clinton of sedition and treason again
10:42 PM - Posts a video of a man on CCTV footage knocking over food a waiter was carrying
10:47 PM - Calls Obama the “most DEMONIC FORCE” in American politics
10:47 PM - Posts a tweet from Mike Flynn saying 2020 election wasn’t fair
10:49 PM - Attacks Dominion again claiming they stole the 2020 election (it wasn’t)
10:51 PM - Reposts a fake Charlie Kirk account that claimed Obama blocked Hillary Clinton from being prosecuted
10:53 PM - Claims Obama was part of Hillary Clinton’s emails in some way
11:28 PM - Claims a senior Democrat just testified under oath that Senator Adam Schiff leaked classified information
1:13 AM - Attacks the New York Times for reporting on the reflecting pool
This man is clearly not well.

A friend's startup is growing at 93% a month. I pointed out that her net worth is also growing at 93% a month, and that she can thus feel, in her own life, the falsity of politicians' claim that you have to do bad things to get rich. They're just focusing on making users happy.

Trump campaigned on bringing down the cost of living "starting on day one," and then: started a trade war; deported much of the farm workforce, bombed Iran, allowed healthcare subsidies to expire, cut food assistance, ran an interest-rate boosting deficit, and attacked fed independence.

Today I’m launching AI IQ — frontier AI models, scored on the human IQ scale.
Instead of endless leaderboard tables, AI IQ shows:
• Where models land on the IQ bell curve
• How frontier IQ is changing over time
• How models compare on IQ and EQ
• What intelligence costs in practice
GPT-5.5, Claude Opus 4.7, Gemini 3.1, Grok 4.3, Kimi K2.6, Qwen3.6, DeepSeek V4, Muse Spark, and more.
Link in the first reply. Curious which chart surprises you most.

We've raised a $50M Series B to keep making everyday calls extraordinary.
After 1,000,000,000 calls and 10x enterprise ARR growth, Vapi's platform approach to voice agents is becoming the standard for businesses building human interfaces.

As someone who was homeless and addicted on the streets of San Francisco, I want to add some perspective to these conversations about the open-air drug markets. 🧵

Delighted to announce our 3rd world modeling workshop! After NYC and Montreal, we are now headed to Chicago!
- August 31st to September 2nd
- CfP and details on the website: https://wm-booth.org
- @ylecun and @Diyi_Yang already confirmed, many more to be announced soon!

There will be no AI jobpocalypse.
The story that AI will lead to massive unemployment is stoking unnecessary fear. AI — like any other technology — does affect jobs, but telling overblown stories of large-scale unemployment is irresponsible and damaging. Let’s put a stop to it.
I’ve expressed skepticism about the jobpocalypse in previous posts. I’m glad to see that the popular press is now pushing back on this narrative. The image below features some recent headlines.
Software engineering is the sector most affected by AI tools, as coding agents race ahead. Yet hiring of software engineers remains strong! So while there are examples of AI taking away jobs, the trends strongly suggest the net job creation is vastly greater than the job destruction — just like earlier waves of technology. Further, despite all the exciting progress in AI, the U.S. unemployment rate remains a healthy 4.3%.
Why is the AI jobpocalypse narrative so popular? For one thing, frontier AI labs have a strong incentive to tell stories that make AI technology sound more powerful. At their most extreme, they promote science-fiction scenarios of AI “taking over” and causing human extinction. If a technology can replace many employees, surely that technology must be very valuable!
Also, a lot of SaaS software companies charge around $100-$1000 per user/year. But if an AI company can replace an employee who makes $100,000 — or make them 50% more productive — then charging even $10,000 starts to look reasonable. By anchoring not to typical SaaS prices but to salaries of employees, AI companies can charge a lot more.
Additionally, businesses have a strong incentive to talk about layoffs as if they were caused by AI. After all, talking about how they’re using AI to be far more productive with fewer staff makes them look smart. This is a better message than admitting they overhired during the pandemic when capital was abundant due to low interest rates and a massive government financial stimulus.
To be clear, I recognize that AI is causing a lot of people’s work to change. This is hard. This is stressful. (And to some, it can be fun.) I empathize with everyone affected. At the same time, this is very different from predicting a collapse of the job market.
Societies are capable of telling themselves stories for years that have little basis in reality and lead to poor society-wide decision making. For example, fears over nuclear plant safety led to under-investment in nuclear power. Fears of the “population bomb” in the 1960s led countries to implement harsh policies to reduce their populations. And worries about dietary fat led governments to promote unhealthy high-sugar diets for decades.
Now that mainstream media is openly skeptical about the jobpocalypse, I hope these stories will start to lose their teeth (much like fears of AI-driven human extinction have).
Contrary to the predictions of an AI jobpocalypse, I predict the opposite: There will be an AI jobapalooza! AI will lead to a lot more good AI engineering jobs, and I’m also optimistic about the future of the overall job market. What AI engineers do will be different from traditional software engineering, and many of these jobs will be in businesses other than traditional large employers of developers. In non-AI roles, too, the skills needed will change because of AI. That makes this a good time to encourage more people to become proficient in AI, and make sure they’re ready for the different but plentiful jobs of the future!
[Original text in The Batch newsletter.]

Very important lesson for Blue Cities here: Every change Lurie has made has been opposed by screaming, bullying activists -- ignoring them has been the path to policy success and extremely high popularity. @skaushik100
https://www.sfchronicle.com/election/article/sf-voters-daniel-lurie-22244870.php

Superlog (@superlogYC) is the observability tool you're not supposed to open: a wizard sets up your logs, traces, alerts, and dashboards daily, and an agent investigates incidents and posts one mergeable PR per issue into Slack.
Sign up here: https://superlog.sh/
Congrats on the launch, @nicolomagnante and @arseniycodes!
https://www.ycombinator.com/launches/QKt-superlog-the-self-installing-observability-tool-that-fixes-your-bugs

Long Lake did the world's first (to my knowledge) AI-driven take private of a public company
-$6.3B acquisition
-100 year old Amex Global Business travel
-Plan to transform it with AI
Spoke w CEO Alex Taubman on @NoPriorsPod about it in his first public podcast ever

Fast mode for Claude Opus 4.7 is now available in research preview on the API and in Claude Code.

In 2024 UC Berkeley began building student housing on an abandoned lot that had been taken over by junkies.
Seething progressives vandalized the construction equipment and the university had to built a fort of containers around the lot to continue construction.
M. Nolan Gray 🥑: For 45 years, Berkeley built virtually no new housing. By the mid-2010s, it was the most expensive college town in America. Shortly thereafter, YIMBYs took over and kicked off a building boom. Today, nominal rents are below 2018 rates—remarkable progress on affordability.

What actually is GBrain?
(Y Combinator CEO's personal agent brain)
Every agent memory tool you've seen solves a simple problem: store facts, retrieve facts.
GBrain solves a different one. It gives your agent a knowledge system that wires itself, enriches itself, and compounds while you're not even using it.
Here's what makes it fundamentally different from Mem0, Zep, LangMem, or a CLAUDE.md file.
The standard approach to agent memory is vector-based. Your agent stores memories as embeddings, retrieves them by semantic similarity, and that's the loop. Some tools add a knowledge graph on top.
GBrain flips the model entirely. The source of truth is a folder of markdown files. One page per person, one page per company, one page per concept. Every page follows the same two-part structure:
𝗖𝗼𝗺𝗽𝗶𝗹𝗲𝗱 𝘁𝗿𝘂𝘁𝗵 on top: your current best understanding, rewritten as new evidence arrives
𝗧𝗶𝗺𝗲𝗹𝗶𝗻𝗲 on the bottom: an append-only evidence trail that never gets edited
This is not a vector store with a markdown export. The markdown IS the system of record. You can open it in VS Code, edit it by hand, and 𝗴𝗯𝗿𝗮𝗶𝗻 𝘀𝘆𝗻𝗰 picks up the changes.
Now the part that makes this compound.
Every time a page is written, GBrain extracts entity references and creates typed relationship links: 𝘄𝗼𝗿𝗸𝘀_𝗮𝘁, 𝗶𝗻𝘃𝗲𝘀𝘁𝗲𝗱_𝗶𝗻, 𝗳𝗼𝘂𝗻𝗱𝗲𝗱, 𝗮𝘁𝘁𝗲𝗻𝗱𝗲𝗱, 𝗮𝗱𝘃𝗶𝘀𝗲𝘀. All deterministic, all regex-based, zero LLM calls.
The knowledge graph wires itself on every single write, without spending tokens.
So when you ask "who works at Acme AI?" or "what has Bob invested in this quarter?", the agent walks the graph instead of relying on vector similarity (which struggles with relational queries like these).
Search layers ~20 deterministic techniques in concert: intent classification, multi-query expansion, vector search, keyword search, reciprocal rank fusion, cosine re-scoring, compiled-truth boosting, and backlink ranking. Each catches what the others miss.
But the real unlock is the compounding loop.
GBrain has a 𝘀𝗶𝗴𝗻𝗮𝗹 𝗱𝗲𝘁𝗲𝗰𝘁𝗼𝗿 that fires on every message and captures entities in the background. Person mentioned once? They get a stub page. Three mentions across different sources? Web enrichment kicks in. After a meeting? Full pipeline.
The agent runs a 𝗱𝗿𝗲𝗮𝗺 𝗰𝘆𝗰𝗹𝗲 overnight: scans conversations, enriches missing entities, fixes broken citations, consolidates memory. You wake up and the brain is smarter than when you went to bed.
This is fundamentally different from memory systems that only store what you explicitly tell them to store.
Garry Tan (President and CEO of Y Combinator) built this to run his actual AI agents. It ships with 34 skills, runs on embedded PGLite (no server, ready in 2 seconds), and works as an MCP server for Claude Code, Cursor, and Windsurf.
GBrain: http://github.com/garrytan/gbrain
Garry Tan: http://x.com/i/article/2042922188924424198

This cinches it - I'm going to vote for him. Steyer and Becerra can't talk this long on any issue without blaming Trump or corporations or raising a dubious solution. He has real experience in CA, with CA problems. Not perfect on policy and isn't going to win but it's a primary
Ezra Klein: Here's @MattMahanSJ, on the lessons — both politics and policy — of trying to cut unsheltered homelessness in San Jose to zero

It's so weird how difficult it is for the left to understand that all you have to do to decrease housing costs is to let people build more housing.
M. Nolan Gray 🥑: For 45 years, Berkeley built virtually no new housing. By the mid-2010s, it was the most expensive college town in America. Shortly thereafter, YIMBYs took over and kicked off a building boom. Today, nominal rents are below 2018 rates—remarkable progress on affordability.