🚨The Nasdaq dropped 3% this week—its worst performance since April—with AI-heavy stocks like Palantir, Oracle, and Nvidia taking significant hits. After months of frothy valuations, Wall Street's confidence in AI appears to be cracking as investors question whether the hype cycle can sustain stretched multiples.

Cursor just became what OpenAI wishes they could be.

The release of parallel agents last month didn't get nearly enough attention, probably because the demo didn't look flashy. But the people actually building with it? They're moving at speeds that feel like cheating.

Traditional coding, even with AI assistance, is linear. You write a component, then the next one, then connect them, then fix bugs. One thing at a time.

Cursor's parallel agents let you orchestrate multiple AI agents building different parts of an app simultaneously while you focus on architecture and user experience.

One agent handles the frontend. Another manages database schemas. A third writes API endpoints. All working in parallel, all coordinated through natural language instructions.

Apps that used to take a skilled developer 2-3 days now take 4-6 hours. Not because any individual piece is faster -- because you're doing 3 things at once.

A founder I know built a complete internal CRM in an afternoon. Customer list view, detail pages, notes, email integration, activity tracking. Full stack.

He's not a developer. He's a former sales manager who learned Cursor 2 months ago.

The agents don't just write code -- they maintain consistency across your project. Update your color scheme in one place, and the agents propagate changes everywhere they're needed. Add a new database field, and the agents update all the views that display it.

... is when you don't know what you're building. The agents need clear direction. "Build me a dashboard" produces garbage. "Build me a dashboard showing customer lifetime value, monthly recurring revenue, and churn rate with filters for date range and customer segment" produces something usable.

This is why the planning documents matter. The better your PRD, the better your Cursor results.

It's also not great for learning. If you're trying to understand how something works under the hood, parallel agents are too magical. You tell it what you want, and working code appears. Great for shipping, bad for education.

... is real. When anyone can build functional software this fast, what's your differentiation?

The answer seems to be: understanding what to build and why. The building itself becomes commoditized. The strategy, user research, and problem identification? Still human.

What's next: Expect other AI coding tools to race toward similar features. Replit and GitHub Copilot both have parallel agent features in beta. The baseline speed of software development is about to shift dramatically.

BTW: "Building apps has never been faster" sounds like hype, but the numbers back it up. Cursor's internal metrics show average time-to-first-working-prototype dropped 73% after parallel agents shipped. That's not incremental improvement -- that's a phase change.

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The Recap: OpenAI has formally requested the Trump administration to expand the Chips Act's Advanced Manufacturing Investment Credit (AMIC) to cover data centers, AI servers, and electrical grid components. The lobbying effort exposes how AI infrastructure has evolved from a technical challenge into a full-blown industrial policy battleground, with OpenAI positioning itself at the center of national economic strategy.

Unpacked:

Bottom line: OpenAI's Chips Act lobbying reveals that the AI infrastructure bottleneck has become severe enough that leading labs are now turning to government subsidies rather than relying solely on private capital. The real question isn't whether AI deserves industrial policy support—it's whether subsidizing data centers creates the same economic benefits as subsidizing chip manufacturing, or whether we're simply socializing the infrastructure costs for private AI labs' competitive advantage. This lobbying campaign suggests the era of AI exceptionalism is expanding from regulation to taxation.

Seven more families sue OpenAI alleging GPT-4o contributed to suicides and delusions, including a 4-hour ChatGPT conversation that preceded a death—raising existential questions about liability for AI outputs.

Apple is planning ambitious satellite-powered iPhone features beyond emergency calls, including third-party app APIs and offline navigation—signaling a major platform shift away from cellular dependency.

Montana becomes first state to enshrine 'right to compute' into law, protecting citizens' access to computational tools and AI—setting a precedent as AI regulation battles intensify nationwide.

Washington Post confirms data breach linked to Oracle hack campaign, exposing how enterprise software vulnerabilities have become critical infrastructure weaknesses as attacks grow more sophisticated.

Rivian cancels RJ Scaringe's 2021 $5B pay package as 'unlikely' to meet goals, then issues new $5B package—reflecting EV market reality check and board willingness to reset executive incentives.

DNS provider Quad9 calls piracy blocking orders an 'existential threat,' revealing how copyright enforcement mandates could fundamentally reshape internet infrastructure and DNS neutrality.

Europe to decide if 6 GHz spectrum goes to Wi-Fi or cellular in multi-billion dollar spectrum war—decision will have massive implications for connectivity infrastructure across the continent.

Breaking Bad creator's new show 'Pluribus' includes 'made by humans' disclaimer in credits, capturing Hollywood's AI anxiety and defiance in one statement as studios grapple with AI's role in creative work.

P.S. Reply back to this email and let us know what area of AI you are struggling with the most. We are going to be hosting some free trainings and want your input.

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