Six AI debates: 1. Frontier models get cheaper vs. more expensive 2. The world is underinvested vs. overinvested in compute 3. The gap between frontier and open source shrinks vs. widens 4. AI is job-destroying vs. job-creating 5. AI detection & regulation keeps pace with generation vs. never catches up 6. AGI/ASI is in sight vs. unachievable Answers vary heavily based on age, job, industry, time-spent-on-Twitter.

I'm 80 years old and somehow I woke up in my 25 year old body for just 1 day. I catch my reflection in the bathroom mirror. No deep lines. No gray hair. Only my younger face, staring back at me. For 24 hours I could do anything. Call the people I'd lost. Say the things I never said. Watch a sunset without looking at my phone. So I opened up my laptop, forked GStack, and applied to YCombinator.

.@GammaApp grew to $100M ARR with AEO as their primary channel to acquire customers. This is the first episode of my new podcast with @ZargaryanArthur, Distribution, and we have @ravishagrwal who leads Growth at Gamma joining us. This is an absolute masterclass on AEO, including: - 04:23: How Gamma Grew 8x Off ChatGPT Referral Traffic - 08:50: Writing for LLM Crawlers vs Human Readers - 16:23: Why Reddit Is the Single Most Important Channel for ChatGPT Citations - 16:34: Ranking Top Platforms for AEO: Reddit, YouTube, LinkedIn, X & Owned Content - 36:53: The Half-Life of an AI Citation & How to Stay Ranked Over Time

Varick is hiring an Operations Associate. Join the #1# applied AI company on the planet with an elite team and exponential growth. Looking to hire asap. You'd own payroll, recruiting coordination, our document and contract system, and executive support for me and the team. What we're looking for: - Incredibly well organized, can track multiple work streams at once - Wants scope and ownership - Instinct to kill inefficiencies - Either has 2+ years of past experience, or can prove why that doesn't matter for them The role is in office 5 days, San Francisco. Generous comp (120k-160k), health care, 401k, free lunch and dinner, etc. Must be authorized to work in the US. DMs are open.

Completely agree. But people misunderstand what “apps” means in the enterprise space. The enterprise value in apps does not come from your vibe coded LLM wrapper. This has not only a switching cost of 0, but also a creation cost of 0. You’ll get destroyed on both ends. Instead the value in apps means who will go deepest into a company, understand how things work today, re-engineers processes for an AI native future, and then builds the AI application for this future state on top of your existing systems of record. Varick.

Great post both if you’re driving AI in an enterprise or building for an enterprise. AI productivity gains are going to wildly vary - much wider than you think - because what you can do at the frontier is so significant if you fundamentally change your workflows to support agents. The challenge is that most people won’t or can’t naturally do this because of the complexity it entails. Thus, a large amount of automation with agents is going to come from just getting agents wired up into a workflow that the user never ends up noticing or caring about: “For everybody else, the work has to get done without them changing how they work, which means the AI goes into the background. Why do you need AI to be prompted by a human anyway? Just figure out what the most repetitive processes are, build agents in your existing systems of record that employees are used to” This is the real work ahead for most enterprises right now that want to get significant gains from AI. A lot less “let a thousand flowers bloom” and more “pick off the 10 highest leverage things in the enterprise and apply automation to them”. There’s no real shortcut here.

Most people judge AI models by what they can do today. @rahulgs judges the slope. When we started Ramp, people had tasted better software at home and could no longer tolerate the tools they were handed at work. So we built something better. Same thing is happening now with AI. Our customers use these models every day. They know what speed and intelligence feel like — and anything that makes them repeat themselves or wait for an answer feels broken. Rahul builds for that. Not for the best model today, but for where models will be in 3–6 months. Studying traces. Improving the harness. Cutting CI time. Giving agents real work with real guardrails. He gets into all of it with @bcherny, @Anthropic's Head of Claude Code, and our staff engineer @austospumanto.

Hiring a growth engineer. Requirements: - cracked - proven growth on social media channels - proven ability to do outbound - top 1% communicator - understands the ai scene to a T Role is in person in SF, will relocate you if needed