The U.S. monthly jobs report does not break out the tech industry as its own category; tech jobs are spread across information, professional services, and manufacturing sectors established decades ago.
Where this was said
At 4:19 · chapter starts 3:35
Castleman delivers a quietly devastating diagnosis of America's economic measurement problem. The monthly jobs report — the gold standard of labor market data — doesn't even have a tech industry line item. Tech employment is scattered across the information sector (which also includes newspapers), professional services, and manufacturing. The categories were established decades ago and haven't kept pace with the economy. Want to know what's happening to recent college graduates month-to-month? That data doesn't exist reliably either. Castleman is careful not to call it an 'oversight' — economies move faster than data infrastructure, and you can't spin up new measures every time something changes — but the practical effect is the same: we are flying blind precisely when we most need to see clearly. [1] — Ben Castleman "The U.S. monthly jobs report doesn't even have a tech industry category — that classification was set up decades ago. The result: we cannot…" 03:35
The U.S. monthly jobs report doesn't even have a tech industry category — that classification was set up decades ago. The result: we cannot isolate what AI is doing to the labor market in real time, leaving policymakers and workers essentially flying blind.
Credible economists using private-sector data from ADP, LinkedIn, and Indeed are reaching polar-opposite conclusions about AI's job impact. One serious report shows entry-level workers in AI-exposed roles losing jobs. Another equally credible report shows AI-adopting companies hiring faster than others.
Credible reports from serious economists using private-sector data (ADP, LinkedIn, Indeed) reach polar-opposite conclusions — some showing job losses in AI-exposed occupations, others showing AI-adopting companies adding jobs faster.
Sam's initial MVP was coded in approximately one week using ChatGPT voice mode and copy-pasting code, with no prior technical experience.
Sam argues Discord is 10x better than email for building relationships with younger users who rarely check their inbox.
Sam's monthly operating costs include Cursor ($200), AI image generation ($100), AI video generation ($200), hosting ($100), email marketing ($80), and AI compute ($300–$500).
Sam recommends copying days of Discord chat history into ChatGPT and prompting it to list recurring pain points as a fast, free market research technique.
Bhanu and his team built approximately 50 free tools to attract search traffic, each linked back to SiteGPT.
With AI coding tools like Cursor, Bhanu can now create a new free marketing tool in less than 5 minutes by referencing existing tools.
Bhanu filters Ahrefs keyword results to show only those with a keyword difficulty below 10, making them realistic ranking targets for any decent website.
Bhanu sets a minimum search volume of 1,000 monthly searches when selecting keywords to target with free tools.
PropGPT averaged 20 downloads per day right after launching on the App Store through influencer marketing.
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