TL;DR
Thariq said Claude Code now handles TurboTax pain, while Rauch called microVM sandboxes the new compute layer. Aditya Agarwal pushed memory over loops, and Levie argued AI won’t shrink law—it’ll inflate it.
Claude Code added a TurboTax connector, so tax procrastination just got a lot less painful. It’s a small but very real example of AI agents moving from chat to actually doing annoying life admin inside the tools people already use.
Vercel Sandbox is now the fastest microVM-based sandbox, and he says customers are seeing the real win in production: better performance and reliability, not just lab benchmarks. The pitch is bigger than sandboxes — this is the foundation for coding agents, parallel compute, and whatever weird workloads come next.
He says some VCs preach low valuations when they’re investing, then flip and push for the highest mark possible once they’re on the cap table. His advice: back missionaries, not mercenaries, and backchannel anyone joining your round because the goodwill disappears fast when things get rough.
He’s testing a stricter agent mode in OpenClaw that forces GPT-5.x to keep reading code, calling tools, and making changes instead of stopping at a polite plan. He’s also making the harness pluggable, so Codex or other SDKs can run the agent loop — with Codex taking over threads, resume, compaction, and app-server execution in one setup.
AI will likely create more lawyers, not fewer: more people will ask legal questions, more exotic issues will need review, and AI itself is spawning fresh IP, privacy, and compliance work. He points to the PC/internet era as precedent — when professions get more efficient, demand often rises instead of falling.
He says the real line between a true agent and a looped LLM is long-horizon memory management. The most interesting part of Claude Code, in his view, is its 3-tier memory architecture — a reminder that agent quality is mostly a memory problem, not a prompt problem.
He teased a chat with Figma CEO Dylan Field on whether AI can learn design taste, plus the bigger question of whether design systems help or hurt creativity. The real hook: how Figma plans to compete once AI starts eating more of the design workflow.
He argues agentic systems should keep the harness thin: memory and skills live in markdown, and the brain sits in a git repo the harness just reads. After 3 months of open source used by tens of thousands of agentic engineers a day, his counterpoint is basically: don’t let the wrapper become the product.
She argues the most efficient team structure is basically anti-teamwork: one person owns a task end-to-end and works with agents. Human communication, in her view, should shrink to deciding what to build, defining what “good” looks like, and the parts that actually need empathy or creativity — not status updates and handoffs.
He says the AI customer service market is already crowded enough that it’s basically a solved problem. That’s a blunt take from a FirstMark VC, and it suggests the real differentiation now is elsewhere in the stack, not in yet another support bot.
Stablecoins are becoming the rails for machine-to-machine finance
The Takeaway: Jeremy Allaire thinks the next financial system won’t be built for humans first — it’ll be built for AI agents.
Allaire, co-founder and CEO of Circle, has spent more than a decade chasing the same idea: “a protocol for dollars on the internet.” That started as a way to move money instantly and globally, but his philosophy has sharpened into something bigger. He argues that stablecoins like USDC are the practical answer to the old banking problem of leverage and fragility — a safer, full-reserve form of money backed by short-duration Treasuries, repos, and cash. In his view, that’s why stablecoins matter more than most crypto assets: they’re not trying to escape the system, they’re trying to fix it.
His sharper point is about what comes next. As AI agents begin doing real work, buying services from each other, and coordinating across companies and borders, they’ll need financial infrastructure that works “globally, interoperably, instantly.” That’s where blockchain becomes less like a casino and more like an operating system. Allaire sees Arc as an “economic operating system” built for this machine economy, with USDC as the native money layer.
The twist: he’s not romantic about decentralization for its own sake. He wants infrastructure that financial institutions can actually trust. Or as he put it, the goal is to support “the real economy’s activity, not a kind of shadow economy.”
Peter Steinberger called AI code review the killer dev workflow, while Thariq said Claude Code turned files into a workbench. Cursor bet on specialized models plus brutal RL infra, and Anthropic detailed how it contained Claude across products.
Steinberger said AI agents need lean skills, not bloated prose; Levie argued AI won’t kill jobs, it’ll raise the bar. Yang said Codex tested itself while Claude still owned frontend, and Garry Tan pushed hard evals as the way agents got better fast.
Levie warned AI demos fool CEOs; the hard work starts after. Tan said high agency plus taste beat everything, while Yang urged builders to build the system that builds the MVP first. LeCun kept the pressure on: LLMs help, but they’re not the road to real intelligence.
Levie said AI kills tasks, not jobs, so roles just expand. Masad said Replit’s AI stack can ship MVPs in a weekend, while Tan showed Qwen fine-tunes in hours and personal AI got real. No Priors said Cerebras won by betting on speed before the market cared.
Levie said AI will surface more bugs, making humans the bottleneck. Steinberger argued GitHub’s native PR limits kill bot policing, while Tan pushed the “ship the 60%” rule and Swyx said AI coding should harden codebases, not just move faster.