12 hours ago
- A platform shift occurs roughly every 10 years, similar to AWS's cloud-native shift in 2006, with AI (especially LLMs) potentially causing another fundamental change.
- AI provides immediate value like cloud did, with easy-to-use HTTP APIs and solutions for formerly hard problems (e.g., sentiment analysis, code generation), but this value may be mistaken for durable value.
- Early AI is impractical for many contexts due to missing tooling and reliability issues, reminiscent of early cloud's limitations that shrank over time as capabilities expanded.
- Platform shifts force an evolution in software properties (e.g., from static to dynamic in cloud), and AI may require new properties like natural language interfaces, offering opportunities for new startups.
- Successful platform shifts bring along old technologies via migration paths (e.g., 'lift and shift' in cloud), whereas AI improves existing software, contrasting with the all-or-nothing approach of web3.
- If AI is a platform shift, we are in early stages; maturity may take years, but broader social hype could shorten timelines, and ignoring this trend is unwise.