Snapshot · The Prof G Pod with Scott Galloway
John Burn-Murdoch observed that when the full pipeline from AI-assisted code to actual product usage is tracked, there has been very little measurable uplift in real value delivered, despite higher activity levels.
Where this was said
At 45:40 · chapter starts 43:19
Scott introduces the counter-narrative John has been developing: the collapse in junior hiring that everyone attributes to AI actually started well before ChatGPT, aligning with the rise of fully remote work in 2020. John Burn-Murdoch explains that an enormous amount of research energy has been spent examining AI's impact on employment while very little has been devoted to the radical transformation in working conditions brought about by remote work — despite the fact that it fundamentally changed the worker-employer relationship, the hiring process, and the nature of daily tasks [1] — John Burn-Murdoch "Everyone blamed AI for the collapse in junior hiring. But the data says the pullback started in 2020 when remote work took off — three year…" 43:19 . Emerging studies are starting to show that fully remote working was a major driver of reduced junior hiring: once work became a series of digital tasks done over Slack, it became natural to ask whether those tasks could be done by someone far away — or by agentic AI. The solution, Burn-Murdoch argues, is not a return to five-day mandates (which create their own problems) but a hybrid model of three to four days in the office, which the evidence shows benefits both juniors and managers [2] — Scott Galloway "Remote work pre-dates AI in junior hiring decline: The pullback in junior hiring began when remote work took off in 2020, well before ChatG…" 43:19 . The discussion segues into the noisy AI productivity research landscape, where John notes that headline metrics of activity don't necessarily translate to real delivered value.
The pullback in junior hiring began when remote work took off in 2020, well before ChatGPT arrived, suggesting remote work — not AI — may be the primary culprit for young workers' labour market struggles.
Everyone blamed AI for the collapse in junior hiring. But the data says the pullback started in 2020 when remote work took off — three years before ChatGPT. When work became a string of digital tasks done over Slack, it was natural for managers to wonder why they needed anyone in the room.
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.
Eyal and Yali shut down all marketing and spent 4 months completely rebuilding PropGPT from scratch.
PropGPT has accumulated over 40,000 total downloads since launch.
PropGPT's large language model (AI) operating costs are just $20 per month, and the cost is continually falling.
Ad-based monetization works well for game apps where users spend extended time in-session, as seen with Grid and Wordle.
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