Prompt Engineering

Senior Dev: This "Grill Me" Prompt Is Going Viral Among Top Engineers

May 7, 2026 · 22:03

Matt Pocock — the TypeScript educator turned AI engineering teacher who created the viral "Grill Me" prompt and runs AI Hero — argues that classic software engineering fundamentals are more critical than ever in the AI coding era. He explains how Domain-Driven Design's ubiquitous language and deep module patterns let developers contain complexity and delegate implementation to AI. His free "Grill Me" skill (part of his 13,000-star skills repo) forces AI to relentlessly interview humans until reaching shared understanding. He contrasts Claude Code's ease-of-use against Pie's transparent primitives, predicting a shift toward developer observability. The episode also covers his two-month course creation process, why TypeScript is overtaking Python in AI engineering, and why traditional lectures still dominate learning.

[State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute

Dec 31, 2025 · 22:34

Andy Konwinski, co-founder of Databricks and Perplexity, launches Laude Institute—a dual venture fund and nonprofit to accelerate the path from open research to breakout companies. At NeurIPS, he explains how Laude's Slingshot program funds projects like DSPy, Terminal Bench, and LMArena, and why the NSF's $1B/year for CS is insufficient, needing $10-100B for frontier AI. He argues Chinese labs (Moonshot, DeepSeek) now outpublish US because OpenAI and others stopped sharing; Open Frontiers, a live-streamed conference in SF, aims to unite top open researchers (Yann LeCun, François Chollet, Jan Leike) to reclaim global leadership. The episode also spotlights the emerging 'post-post-training' layer—prompt optimization, context management, RAG—and why research teams with multiple co-founders (like Databricks' eight) are the new gold standard for AI startups.

OpenAI o1 isn’t a chat model (and that’s the point)

Jan 17, 2025 · 31:59

Ben Hylak and Dan McAteer explain why OpenAI’s o1 is not a chat model and how mastering its prompting turned Ben from a skeptic into a proponent. Ben’s prompt structure—goal, return format, warnings, context dump—emphasizes describing what you want rather than how to think, a shift from earlier models. Dan uses o1 for coding by feeding it full code context, achieving one-shot implementations that reach 100% where previous models maxed out at 95%. Ben notes o1 is the most capable but hardest model to use, with experiments costing $20 per try, and argues model routing will let humans or systems trade off cost, speed, and intelligence. Dan also applies o1 to scientific research, feeding it papers from multiple fields to find novel connections that humans would miss.

This World Does Not Exist — Joscha Bach, Karan Malhotra, Rob Haisfield (WorldSim, WebSim, Liquid AI)

Apr 27, 2024 · 1:56:11

The episode features Karan Malhotra demoing WorldSim, a prompt that turns Claude 3 into a universe simulator via CLI; Rob Haisfield presenting WebSim, which generates functional websites on the fly; and Joscha Bach arguing simulative AI reveals consciousness as a virtual property, with LLMs creating agents as real as human minds, urging the California Institute for Machine Consciousness to build self-organizing silicon life. Malhotra shows WorldSim running “world.exe” to create Twitter inside a simulated universe, with users tweeting and Elon Musk moving Dogecoin. Haisfield demonstrates WebSim generating a 5D particle interface, a news RSS aggregator, and a face-swap webcam app via URL parameters like “secrets=revealed”. Bach explains consciousness as second-order perception in a simulated now, criticizes RLHF for lobotomizing models, and advocates for animist AI where software agents compete like spirits, not golems.