Software engineering is supposed to be the first job AI takes. But Dwarkesh bets there will be more demand for human software engineers in 2027 than today — because AI is acting as a complementary input that expands the overall market for software.
Where this was said
At 9:28 · chapter starts 8:46
Dwarkesh argues inefficiency doesn't block white-collar automation because AI's training costs amortize across billions of sessions. [1] — Dwarkesh Patel "AIs can be wildly data-inefficient and still automate white-collar work, because common tasks are common enough to bring into the training …" 07:48 He bets on more human software engineers in 2027, and previews a future post on the intelligence explosion. [2] — Dwarkesh Patel "Current discourse on intelligence explosions is stuck between two bad takes: it's impossible, or a god emerges at the end. Neither is right…" 10:17
Dwarkesh bets there will be overall more demand for human software engineers in 2027 than today, largely due to AI acting as a complementary input rather than a replacement.
Current discourse on intelligence explosions is stuck between two bad takes: it's impossible, or a god emerges at the end. Neither is right. The real question is what a period of faster-than-usual AI progress looks like when it's built atop the particular kind of intelligence LLMs represent.
Avnish grew his solo business to $25,000 per month in just 15 months without spending a dollar on ads. His entire growth engine was built on community posts in Reddit and Facebook groups.
One well-crafted post in the right community took Avnish from single thousands of users to tens of thousands. This wasn't luck — it was a repeatable part of his 5-step playbook.
Most founders chase paid ads and influencer deals, but Avnish's growth came entirely from knowing where his users already gathered online. Dominating Reddit and Facebook groups — for free — was his entire strategy.
Spend 80% of your landing page design time above the fold. The hero section is the only thing most visitors will ever truly read, so it needs to deliver your full message instantly.
The dominant mobile monetization flow is simple: free download, onboarding, then a hard paywall that blocks all features until the user pays or starts a trial. It's unskippable by design — and that's exactly the point.
Switching PuffCount to a hard paywall and requiring a free trial before any feature access sent conversion rates soaring to 20–25%. One structural change to the payment flow — no new features, no new users — transformed the business.
Vasco is so confident in YouTube that he'll personally PayPal $500 to anyone who posts for 45 days and doesn't make $5,000. This isn't hype — it's a distillation of his own experience growing an AI app to $70K/month using nothing but daily videos.
Vasco's AI app went from zero to $70,000 a month in just two years. The entire growth engine was YouTube — one video a day, nothing fancy, no expensive tools. Most of his users came directly from the channel.
People buy from people they know, like, and trust. YouTube is the only platform that builds all three at scale — and Vasco's $1M business is the proof of concept.
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