I’m organizing the 9th Indie Hacker Meetup 🤩
📍 Seoul, Korea
📅 Saturday, June 13
🕣 8:00–10:00 AM
I want to keep these meetups fun, so we’ll start with a run together.
At 8 AM, we’ll run ~8km along the Han River (한강) at a chill pace (~6:00 min/km). Then around 9 AM, we’ll head back to the starting point and hang out.
People have met cofounders, built startups together, and made real friendships at these meetups, so come join us ❤️
RSVP below 👇
.@chamath, I’m building @AntifraudCo, a startup that files qui tams against fraudsters on a repeatable basis with the help of @BarclayDavidP, a former FTC attorney & @hajsharda, an author/lawyer/antitrust whiz.
Ever since I was invited to testify before Congress at age 20 about millions of wasteful bloat at Brown I uncovered through data mining, I realized the government just didn’t have the bandwidth to stay on top of these things without the help of whistleblowers.
The TAM here is huge — 500B per year. Easily a huge market opportunity that can create multiple unicorns.
This is my fifth conversation with @GavinSBaker.
Gavin understands semiconductors and AI as well as anyone I know and has a gift for making sense of the industry's complexity and nuance.
We discuss:
- Nvidia vs Google (GPUs + TPUs)
- Scaling laws and reasoning models
- The economics of AI compute
- Why Blackwell's delay mattered
- The bear case on the AI capex buildout
- Data centers in space
- The mistake SaaS companies are making
Few people love investing more than Gavin. His closing answer about why he loves it turned into a full reflection on his investing origin story, which I had never heard before.
Enjoy!
Timestamps:
0:00 Intro
5:03 The Blackwell Transition
23:15 The Prisoner's Dilemma
27:12 The Bear Case: Edge AI
37:19 Meta, Open Source, and Model Depreciation
43:08 Geopolitics and Rare Earths
50:42 Data Centers in Space
56:06 Power Constraints as a Governor
1:11:31 The SaaS Mistake
1:16:17 Nuclear and Quantum
1:22:25 Gavin’s Investing Origins
As a full-stack engineer with over a decade of experience, I’ve seen the industry evolve at an incredible pace. I’ve always taken pride in being a generalist and have benefited greatly from it.
I may be biased, but I believe the days of being a hyper focused specialist will soon be reserved for those with true, researcher level expertise in a given domain.
The way I see it, for the everyday corporate designer, engineer, or product person, being a generalist might be the only real way to stay relevant.
The pace of innovation is simply too fast, and hyper-specialization is too risky. It’s becoming clear that the more adaptable you are (you know, being able to learn new tools, switch contexts, and connect the dots) the harder you are to replace.
We’ve already seen waves of layoffs and industry shifts driven by macro and micro market forces, along with the constant repositioning of companies trying to stay competitive.
Not to mention every time I look up, another phase of the software lifecycle is being commoditized and abstracted away by more intuitive tools.
I remember when Canva first started making the rounds in the startup scene around 2016, founders with no design experience suddenly had the ability to produce polished illustrations, designs, and presentations, bypassing Photoshop and Illustrator entirely.
A similar shift happened with Lightroom, which empowered influencers with little photography experience, and with CapCut, which gave content creators professional editing capabilities without ever opening Premiere or Final Cut.
Now the same can be said for nearly every phase of the software lifecycle. For discovery, tools like Notion, Fireflies, and ElevenLabs capture and summarize customer feedback, turning conversations into structured insights within seconds. For design, Figma and Uizard translate plain text into production-ready mockups, skipping the wireframe stage entirely.
In development, GitHub Copilot, Replit’s Ghostwriter, and Devin automate large portions of coding and debugging, while low-code platforms like Retool and Bubble abstract entire stacks. Testing is handled by tools like Testim, Mabl, and Codium, which generate and run QA suites autonomously.
Even deployment and maintenance have become intelligent, with GitHub Actions, Datadog, and Harness orchestrating releases, monitoring performance, and suggesting refactors, all with minimal human touch.
Now the question is: are the days of being a specialist gone? Will generalists who can quickly adapt, integrate tools, and connect domains become more valuable?
Or will specialists simply move up the stack of complexity ultimately focusing on edge cases, applying cutting-edge research and academic breakthroughs, and tackling the systems that automation still can’t handle?
His worldview stands outside Western frameworks, offering a fresh global perspective.
He also has a compelling game theory framework that uses history to predict the future. Here are some example lectures.
https://t.co/cnpAXoSOBc
https://t.co/IM38wkfRHJ
Hi @friedberg could we invite Professor Jiang as a guest speaker at the next All-In Summit?
He’s brilliant at connecting history, the present, and the future through anthropology, archaeology, psychology, and religion.
300 engineers across multiple teams working on large-scale enterprise software were tracked over 12 months as they adopted ai coding tools
> 31.8% reduction in PR review cycle time
> 61% increase in shipped code post-adoption
> 44% productivity increase for senior swes
The devil doesn’t rob you, he tempts you.
He buys your dreams for glitter and dust.
He has no use for your soul, but by taking his offer, you give yours away.
And you have no one to blame but yourself.
managing your psychology as a founder is incredibly challenging, yet is rarely ever talked about in public. in private, i've talked to many founders who feel overwhelmed or depressed even if things are actually going really well. a few reasons i've seen up close:
1) you care a lot - the force of will that drives a founder to start a company often works against them psychologically when things don't go as planned. losing a customer or a talented employee often feel like personal faults. as founder you care the most about the company, and it can feel like you're on the hook for everything bad that happens
2) no all the time - founders are in situations where they are constantly being rejected - fundraising, recruiting, sales, etc. hearing "no" 20 times a day is just mentally and physically draining even for the grittiest entrepreneurs
3) most founders learn on the job - there's little training that prepares you to run a start-up except actually running a start-up. i've worked with founders who had to exit a cofounder for the first time, who had to deal with a PR hit-piece for the first time etc. there are lots of "firsts" which leads to stress and a feeling you don't know what you're doing
so what helps? our partner Ben Horowitz wrote a great blog on this years ago (link below) but summarizing a few tips:
- talk to friends. one of the things we strive to create with @speedrun is a community of founder friends to help with the psychological journey. while the job is still the same, the shared perspective can make it feel a bit less lonely. as others have made it through, so shall you!
- focus on the road ahead not the walls. there are a million things that can go wrong with a start-up and most of them you can't directly control. by focusing on the things you CAN control - your next move, shipping that product, making that hire, etc - you make progress one step at a time
the journey is long but there's a light at the end of the tunnel for those who persevere and most importantly, don't quit =)
our engineering and compute teams do incredible work to rapidly scale to meet customer demand for chatgpt.
a lot of blood sweat and tears go into this, and they make it look relatively easy.
i have never seen a team handle a 2.5 year sprint with such grace!