There’s a documented arc here, not vibes: launching a tech startup cost about $5M in 2000 (servers, Oracle licenses, salaried engineers), about $500K by 2005 after open source, about $50K by 2010 after AWS. That last shift has real evidence behind it. An NBER/Journal of Financial Economics study found that after AWS launched in 2006, the number of first-round-funded software startups roughly doubled, while industries that couldn’t use the cloud grew only about 30%: https://www.nber.org/papers/w24523 Then AI compressed the part that was left, which was the humans. Columbia’s Mattan Griffel now puts the cost of starting a software business around $500 ( https://www.forbes.com/sites/christinedare-bryan/2026/05/22/from-5-million-to-500-the-secret-behind-shrinking-startup-costs/ ), and Y Combinator reported that for a quarter of its Winter 2025 batch, 95% of the code was written by AI, with companies hitting $10M revenue at under ten people: https://www.nbcphiladelphia.com/news/business/money-report/y-combinator-startups-are-fastest-growing-most-profitable-in-fund-history-because-of-ai/4135508/ Here’s the discussion I actually want. Every piece of startup methodology still in circulation (validate before you build, MVP-in-months, graduate from search into execution) was arithmetic for a world where a wrong build could kill you. Search was expensive, so you interviewed before you built. The reality is that building the thing is now often cheaper and faster than scheduling the interviews about the thing. So what advice that was correct in 2010 do you think is actively harmful in 2026? I’ll go first: “don’t build until you’ve validated.” When a build costs a weekend, validation-by-shipping beats validation-by-asking, because people are bad at describing what they’d use and good at reacting to what’s in front of them. submitted by /u/popcornjebus
Originally posted by u/popcornjebus on r/ArtificialInteligence