Cursor has spent its entire existence competing with every major AI lab and incumbent in the toughest market in tech—and has continued to win. So much so that @elonmusk bought them for $60 billion to help SpaceX win the AI race. They've done this by building one of the most talent-dense teams in history. Adam Ward (@wardadamp) is Head of Talent at @Cursor_AI—who acquired his legendary recruiting firm after he spent 20+ years building the most elite teams in tech—and in our conversation he shares the entire playbook for building high talent-density teams. We discuss: 🔸 Why the traditional recruiting funnel—the "funnel of doom"—guarantees mediocre hiring 🔸 Adam's three-step playbook for hiring the top 1% 🔸 The rise of the forward-deployed engineer 🔸 Today's "tale of two cities" talent market 🔸 The biggest mistake founders make with their first recruiting hire 🔸 The worst question you can ask when sourcing talent (you've definitely asked it) Watch the full episode right here 👇

PMs: What's one specific way AI has significantly and consistently impacted your productivity? What's something you do very differently now vs. a couple of years ago that makes your work much faster/better? (Other than prototyping, and using AI to craft/give feedback on your docs/writing)

My biggest takeaways from @danshipper: 1. The future of work will happen inside Codex or Claude Code. Instead of putting AI into your SaaS tool, you’ll use your SaaS tools inside your favorite AI agents' in-app browser. Dan spends all his time in Codex now—writing documents, managing email, doing research, everything. He's using Google Docs, PostHog, and everything he needs within the agent's in-app browser. The agent can see what he’s doing, and has all of his context, so he and his agent collaborate quickly and super effectively. 2. Automation is a lie—every automation needs a human. Dan's company doubled in size this year despite being incredibly AI-forward. Why? Because in order to make automation work well, you need humans making sure everything keeps working. This is why benchmarks are misleading—they measure AI on problems we’ve already framed and can score, but there’s always a higher frame. 3. PMs will win the AI era. Marcus, a former PM who previously ran Axios’s writing product, joined Every after getting super AI-pilled. Now he runs their product Spiral, and ships faster than anyone on the team. He pairs technical knowledge with spiky product sense, deep user empathy, and an eye for what matters. Dan thinks any PM who gets really AI-native will be incredibly dangerous because the building is done for you—what matters is figuring out what to build and if it’s great. 4. Full-stack designers are becoming superheroes. Designers used to make beautiful interactions that engineers didn’t want to build or couldn’t execute properly. Now designers don’t need to hand things off; they can build it themselves. Designers are naturally creative people, and AI is the perfect tool for them because it lets them bring their vision to life without the traditional bottlenecks. 5. SaaS is not dead. In fact, Dan is bullish on SaaS stocks. When users bring their own AI (via Codex or Claude Code) to use SaaS products, the user—not the SaaS company—pays for tokens. This saves SaaS company’s margins. Since the agents need their own seats, Dan predicts that agents will create massive new demand for SaaS because there will be tons of agents using these products at high volume. 6. Every company will have one “super-agent” inside their Slack that every employee will use. Dan initially thought every employee would have their personal work agent, like a shadow AI org chart, but he’s completely flipped his view. He realized agents need humans who care about them. When someone gets tired of maintaining their personal agent, it becomes useless. The winning model is one forward-deployed engineer or AI-savvy person who maintains a company-wide agent (like Shopify’s River or Viktor), and then it trickles down to more specialized team agents as models improve and become less fiddly. 7. The AI job apocalypse is not happening, but you do need to evolve to stay relevant. Models make yesterday’s human competence cheap. But because everyone uses the same models, it all looks the same if you use it the default way; it becomes commoditized slop. Humans then take that frozen competence and use it to make something new and interesting for their specific situation. The key: “ride the models”—use them for everything you do, try new models when they drop, keep turning over rocks. 8. We will read way more AI-generated writing, and we will like it. Human writing is incredibly important for things that matter, but for internal docs, planning, and email, AI-generated is often better because most people are bad at writing strategy documents. 9. Build software for humans and agents to use together. The current model is building a CLI that an agent uses independently. Instead, you and your agent should be using the app together. This creates new design challenges—agents can make a billion requests in three seconds, so you need approval flows, inboxes that summarize what happened, logs, and easy rollback. 10. Forward-deployed engineers are the new most essential role. The big model companies have teams of people managing their internal agents, and those teams aren’t going away. It’s different from traditional software building, and certain engineers love it. As models get better, this role will evolve—you’ll be managing more agents doing more things.

.@danshipper: "The AI jobpocalypse is not a thing. The mass unemployment thing that AI lab CEOs are talking about—that's not going to happen. AI models make yesterday's human competence cheap. But what's interesting is that since everyone's using the same models, it all looks the same. So it becomes commoditized. It's not valuable anymore. And what humans do is we go in there, and we're like, yeah, we have all this frozen human competence from yesterday, how do I use this to make something new and interesting, today?"

Automation is a lie. CLIs are over. The SaaSpocalypse is dumb. A year ago @danshipper came on the podcast to predict where AI was heading. He was remarkably right—including the call that everyone was sleeping on Claude Code. Dan has a unique lens into where things are going because his team at @every is possibly the most AI-pilled group of people in tech. I always learn a ton talking to Dan. So I brought him back for round two. We'll score these in exactly a year: 🔸 Every company will have one “super-agent” in Slack. 🔸 Codex and Claude Code will become the new operating system for knowledge work. 🔸 The AI job apocalypse is not happening. 🔸 PMs and designers will thrive. 🔸 We will read way more AI-generated writing and we will like it. 🔸 "I would buy SaaS stocks right now." Listen now 👇

Engineers don't write code. PMs are shipping to production. The design process is dead (there's no time). Marketing can ship their own campaigns. SDRs are being replaced by AI. Everyone's a data scientist now. What a time to be alive.

Not enough people are talking about how much AI is impacting the role of data science. I was chatting with a DS friend, and he said that most of his team's work now is reviewing half-assed AI data analysis from PMs and engineers. And that 50% of the time, that analysis is wrong. The role is becoming less fun.

A few lesser-known products I love and use a ton: 1. for screenshots 2. replaced Loom for me, so clean 3. for frequent snippets 4. for emojis 5. for focus