Good morning, AI enthusiast.

OpenAI is undertaking a massive expansion of its physical infrastructure, announcing plans with partners Oracle and SoftBank to construct five new Stargate AI data centers. The expansion is a core part of its monumental project to secure the raw computing power needed for the next wave of AI.

This huge investment signals that the primary roadblock to more capable AI is shifting from algorithms to hardware and energy. As the industry races to build these AI megastructures, the key question is: how quickly can this new infrastructure overcome current limitations and deliver on the promise of truly advanced AI?

In today’s AI recap:

• OpenAI’s five new Stargate data centers

• The AI industry’s $800B shortfall

• The growing trust gap for AI coders

• Microsoft’s agentic browser vision

• 8 trending AI Tools

OpenAI's AI Megastructures

The Recap: OpenAI, along with partners Oracle and SoftBank, announced plans to build five new massive Stargate AI data centers across the U.S. This expansion is a core part of its $500 billion project to build the physical infrastructure needed to power the future of AI.

Unpacked:

• The new sites bring Stargate's planned capacity to nearly seven gigawatts, which is enough energy to power more than five million homes.

• These facilities will house hundreds of thousands of Nvidia's most powerful AI chips, starting with the GB200 series and laying the groundwork for the next-generation Vera Rubin chips.

• The push for more compute is driven by current limitations, with CEO Sam Altman noting that services like ChatGPT are still "slow" and not as capable as the company wants them to be.

Bottom line: This massive buildout signals that the primary constraint on AI progress is shifting from algorithms to physical hardware and energy. Securing this level of computing power prepares OpenAI to train and deploy significantly more capable AI models for widespread use.

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AI's $800B Reality Check

The Recap: A new analysis from Bain & Company projects the AI industry could face an $800 billion annual revenue shortfall by 2030. The report warns that the immense cost of compute power and data center infrastructure is scaling faster than the productivity gains can pay for it.

Unpacked:

• Bain’s analysis estimates that meeting AI's compute demand will require about $500 billion in capital investment each year, a sum that would need $2 trillion in annual revenue to support.

• Despite this warning, industry giants are moving full steam ahead with massive spending on their Stargate infrastructure platform, signaling a massive bet on future growth.

• While breakthroughs in algorithms and hardware could ease the financial strain, progress is currently throttled by real-world constraints like power grid limitations and supply chain shortages.

Bottom line: The AI sector is navigating a high-stakes period where investment is far outpacing current monetization models. This gap highlights a critical race to develop more efficient technologies before the costs become unsustainable.

AI Training

How to Automate Your Web Scraping in LLM-Ready Format (n8n + Firecrawl + rss.app)

The Recap: We just posted our very first (of many!) AI automation training videos on YouTube. In this video, we walk through how to use n8n, firecrawl, and rss.app to scrape virtually any piece of web content and transform it into LLM-ready output.

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The Coder's Trust Paradox

The Recap: A new Google DORA report reveals a major gap between AI adoption and confidence. While 90% of tech professionals now use AI at work, only 24% say they trust its output "a lot."

Unpacked:

• Despite the trust gap, over 80% of respondents report that AI has enhanced their productivity, and a majority (59%) say it positively impacts code quality.

• Developers treat AI-generated code with the same healthy skepticism they apply to resources like Stack Overflow—it's a useful starting point but requires human review and validation.

• The shift suggests the software engineer's role is evolving from writing lines of code to architecting systems and breaking down complex problems for AI to help solve.

Bottom line: AI is rapidly becoming a standard developer tool, but its output is still viewed as a draft rather than a final product. True success comes from thoughtfully integrating AI into workflows with human oversight, not from blind adoption.

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The Rise of the Agentic Browser

The Recap: Microsoft AI CEO Mustafa Suleyman laid out a future where AI assistants transform your browser into an active partner. Instead of building a new app, Microsoft wants Copilot to manage tabs, conduct research, and perform tasks for you.

Unpacked:

• The core idea is for your AI to use the same browser tools you do, like opening tabs, navigating pages, and synthesizing information from multiple sources at once.

• Suleyman describes the experience as having an "angel on your shoulder" that handles tedious work like reading reviews, comparing prices, or summarizing research in real-time.

• Unlike competitors creating dedicated AI browsers, Microsoft's strategy is to evolve the current experience, turning tools like Edge and Copilot into a true agentic browser.

Bottom line: This approach aims to change the browser from a passive window for information into an active assistant that accomplishes tasks for you. The vision reflects a larger industry trend toward creating AI agents capable of automating complex workflows across the web.

The Shortlist

Google integrated Gemini into the Play Store, allowing the AI to act as an in-game "Sidekick" that can see your screen and offer real-time tips and guidance.

Cloudflare launched Application Confidence Scorecards, a new tool to automatically evaluate and rate AI and SaaS apps on security, privacy, and compliance to combat "Shadow AI."

Microsoft unveiled Windows AI Labs, a new pilot program for testing experimental AI features within core Windows applications, starting with new capabilities in Microsoft Paint.

New research revealed that major LLMs from OpenAI, Anthropic, and Meta struggle with cultural nuances, correctly navigating the complex Persian social etiquette of "taarof" only 34-42% of the time.

Signing off,

David, Lucas, Mitchell — The Recap editorial team