Podbit · Planet Money
A third or more of American workers sign non-compete agreements — and not just for sensitive roles. Arin Dube cites sandwich chains and summer camps as examples, arguing these agreements are really about suppressing worker mobility and keeping wages low.
Where this was said
At 18:56 · chapter starts 15:20
Dube walks the hosts through the multiple channels through which employers acquire monopsony power even without literally owning an entire town. First, there is market concentration: Vermont's ski industry went from dozens of family-owned hills to a handful of large owners in 25 years, meaning a ski instructor may find that every nearby mountain has the same boss. [1] — Arin Dube "Vermont's ski industry went from dozens of family-owned hills to a handful of consolidated owners in 25 years. Now a ski instructor in Verm…" 16:50 Second, there are search frictions: even in large cities with many options, people don't switch jobs the way theory predicts because changing jobs is slow, exhausting, and risky. [2] — Arin Dube "Even in cities with many employers, people don't switch jobs the way economic theory predicts. Arin Dube says search frictions — the real c…" 17:43 Third, employers actively manufacture monopsony through 'monopsony by artifice': non-compete agreements signed by a third or more of American workers, including at sandwich chains and summer camps. Dube's conclusion is stark — we are all, in smaller but real ways, not so different from the trapped crew of the Nostromo.
Vermont's ski industry went from dozens of family-owned hills to a handful of consolidated owners in 25 years. Now a ski instructor in Vermont may find that every nearby mountain has the same boss — textbook monopsony, no sci-fi required.
Arin Dube points to Vermont's ski industry as a classic example of monopsony: what were once many family-owned hills have consolidated under single owners, leaving workers with fewer employers to choose from.
One study found that typical American workers only have about three equal-sized employers within driving distance for their particular employment field.
Even in cities with many employers, people don't switch jobs the way economic theory predicts. Arin Dube says search frictions — the real cost and effort of finding, applying for, and transitioning to new jobs — hand employers quiet power to underpay workers who stay.
Arin Dube says 'search frictions' — the difficulty of finding, applying for, and transitioning to new jobs — give employers monopsony-like power even in cities with many employers, because workers don't switch jobs as freely as theory predicts.
Arin Dube argues that sectoral bargaining agreements — strong unions that set conditions across a whole industry rather than just one firm — are one of the most effective tools to counter monopsony power.
Arin Dube identifies minimum wage laws, antitrust enforcement, and labor unions as the three main counterforces against monopsony power, whose erosion has caused wage stagnation and rising inequality.
SiteGPT attracted over 1 million visitors and $500K in total revenue without spending a cent on paid marketing. The secret: engineering as marketing — building free tools that rank on Google.
Bhanu quit his first job after just 8 months, moved back to his parents' house to cut costs, and started building. One product sold for $250K; the next hit $10K MRR in its first month.
90% of SiteGPT's Google search traffic comes not from the main product but from ~50 free tools Bhanu built. Each tool targets a low-competition keyword and funnels users back to the paid product.
50,000 monthly visitors become 200 leads, 60 trials, and roughly 15–24 new customers per month at ~$100 average revenue each. Add a $1,700–$1,800 LTV and you have a very healthy SaaS.
Start with a blank Ahrefs search, layer in keyword filters (include term, KD < 10, volume > 1,000), list candidates in Notion, design a CTA linking to your main product, then score by volume, difficulty, build effort, and product relevance. That's the whole playbook.
Marketing feels painful for most builders. Engineering as marketing flips the script: instead of writing cold emails or blog posts, you build things — and those things rank on Google forever.
Don't spend months perfecting before launch. Ship the core feature, get real users, and let their feedback dictate the product roadmap. Premature polish is a trap.
SiteGPT launched and hit $10,000 MRR within its first month. That momentum was so overwhelming that Bhanu sold his existing SaaS, Feather, for $250,000 to free up all his time.
PropGPT launched with 20 downloads a day and strong influencer marketing but hit a ceiling at $1,000–$2,000 MRR. High download numbers masked a critical flaw: almost nobody stuck around after the free trial ended.
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