Roundtable on decision models, Jev, and predictive interfaces
Several heavy AI users compare DevDay releases, assistants, and coding tools, with one chapter focused on Jev decision models and predictive interaction.
🆕 show: HIGH TASTE TESTERS We convene top Al power users to compare what actually works-and what falls apart once you start using it.@davis7, @benhylak, @dexhorthy, @allisonology, @altryne and @swyx give you unfiltered takes on @OpenAl DevDay, Dots vs Muse vs GrokBot vs Instinct, who's winning coding, personal assistants, and the gap between impressive Al capabilities and useful products. From Pi-powered personal agents and decision models to subagents, context management, prompt injection, and assistants that can spend money: what should you actually use? CHAPTERS 00:00 Introducing High Taste Testers 01:26 OpenAl DevDay: Dots, Spaces, and product execution 10:28 Great models versus great products 14:39 Agents versus assistants 18:08 Building a personal assistant with Pi 21:07 Decision models, Jev, and predictive interfaces 32:46 Model speed, writing quality, and subagents 37:29 Agent loops, forks, and context management 43:19 Haiku, Muse Spark, and Grok 50:00 Local models and coding benchmarks 54:09 Prompt injection and assistants taking action 57:50 Tools, payments, and assistant overload 1:02:16 Delegation, computer use, and everyday workflows 1:10:48 Al hardware and closing thoughts THANKS TO THE TESTERS Ben Davis - @davis7 Ben Hylak - @benhylak Dex Horthy - @dexhorthy Allison Durham - @allisonology Alex Volkov - @altryne