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George pulls three current academic studies to make his case. A 2026 NBER working paper found that AI adoption "has not yet led to meaningful changes in total employment," though it is reshaping how tasks are divided within companies. A Federal Reserve Bank of Atlanta study found that more than 90% of firms report no net headcount impact from AI over the past three years. Census research shows that of the small minority of firms that did see headcount changes, reductions and increases were split nearly equally.

The historical pattern holds across every analogous shift. Farm employment fell from one-third of U.S. jobs to roughly 2%, yet agricultural output tripled and the labor freed up built entirely new industries. When spreadsheet software arrived, it didn't eliminate bookkeeping; it shifted roughly 1 million bookkeepers into 1.5 million financial analysts. Travel agent employment halved, but wages for those who stayed nearly caught up to the broader private sector average.

Goldman Sachs research George cites shows AI augmentation effects outpace substitution mentions in earnings calls by roughly 8 to 1. Software development headcount has continued growing since early 2025, and roles with higher AI exposure are seeing above-trend wage growth, particularly in systems design.

George does note that some entry-level roles are getting harder to find, and that transitions create real hardship worth investing in. The macro direction is his actual argument: cheaper intelligence tends to expand markets rather than contract them.

The framing used is the AI hyperscaler model. Microsoft Azure plus OpenAI, Google Cloud plus Gemini, Amazon plus Anthropic as tenant. For most of the AI era, the assumption was that big tech owns the infrastructure and frontier labs are tenants above it. This deal adds a new player to that list, and this one is building more layers of the stack than any of the others.

@farzyness counts six layers SpaceX now controls: launch economics via Falcon 9 and Starship, chip manufacturing via the Terafab project in Austin (a planned $25 billion facility reportedly scaling toward $200 billion), Colossus 1 and 2 data centers in Memphis with a third site under construction in Mississippi, Starlink's 10,000-plus satellite constellation, Grok and now Anthropic as co-tenants on the same infrastructure, and a reported option to acquire Cursor by end of 2026. For comparison, the author argues other major AI infrastructure players max out at four of those layers.

The strategic read: SpaceX may not need to win the model race to win the AI economy. If the moat has moved below the model layer to compute, chips, power, and developer surfaces, owning those layers means collecting rent from whoever does win the benchmark race. The thread closes by noting that Anthropic's reported $30 billion ARR run rate by April 2026 makes SpaceX's compute revenue economics compelling regardless of how the Grok vs. Claude competition plays out.

The Naples chapter held its sixth event last week, this time in workshop format for the first time. Organizer Chris Young led the session around a practical theme: setting up personal AI environments. Attendance doubled from the previous gathering, and the session surfaced a recurring gap that chapter organizers plan to revisit.

Many attendees weren't aware that AI tools default to using conversation data for model training, and didn't know how to change those settings. That kind of configuration literacy, knowing not just how to use the tools but how to set them up safely, is becoming a recurring conversation at chapter events across the network. The chapter has been rotating across formats including agent builds, demo days, and panel discussions. More at https://www.aicollective.com/chapters/naples-fl

The AI Collective Miami crossed 2,000 members this week, with five active chapters, more than 20 events hosted, and a dozen partner organizations on board. The Miami community has been building toward a specific goal: putting the right people in the same room across the full builder stack, researchers, developers, operators, and business leads, and creating real momentum around practical AI applications rather than just conversation about them.

The chapter has been working with local universities and companies to extend that reach, with The LAB Miami as a core partner. Aman Sharma, who co-leads the chapter alongside Charles Whiteman, Ather Husain, Tomas Canova, Jay Rodriguez, Blas Giffuni, and others, framed the milestone as a foundation for the next phase of expansion across South Florida. More at aicollective.com/chapters/miami.

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