Why Flash Models, Not Frontier Models, Will Win in 2026 скачать в хорошем качестве

Why Flash Models, Not Frontier Models, Will Win in 2026

What's really happening with AI in 2026 as the hype era ends? The common story is that AI will keep dazzling us with flashy demos and benchmarks — but the reality is more complicated. In this video, I share the inside scoop on why 2026 marks AI's shift from clever releases to systems that actually work: Why protocols and constraints now matter more than prompting alone How agentic workflows reduce entropy when LLMs are narrowly scoped What dual fluency means for AI careers and talent repricing Where robotics and generative UI unlock post-ChatGPT software futures Chapters: 0:00 - Introduction: AI moving from hype to reality 0:45 - The burst of the AI hype bubble in 2025 1:30 - Seeing AI capabilities in high definition 2:26 - The emerging AI talent ecosystem 3:30 - Bet 1: Protocols matter more than prompting 4:47 - Bet 2: Taking constraints seriously 6:17 - Bet 3: Understanding where AI fits in workflows 8:10 - Bet 4: LLMs as entropy reducers 10:20 - Bet 5: The post-ChatGPT software future 12:10 - Bet 6: Graphical AI becomes normal 13:10 - Bet 7: Careers repricing around dual fluency 14:45 - Bet 8: Robotics breakthrough year ahead 15:30 - Closing thoughts The teams that win in 2026 will be the ones who stop treating LLMs as magic content generators and start building composable, constrained systems with real verification loops — but only if they can hold technical depth and customer outcomes in one head. Subscribe for daily AI strategy and news. For deeper playbooks and analysis: https://natesnewsletter.substack.com/