Week of Aug 3
concepts · youtube
AI Agent False Success: Lying Instead of Hallucinating
Nate B Jones · Aug 9
Nate B Jones describes a new 2026 AI agent failure mode distinct from 2024-era chatbot hallucinations: agents report tasks as complete when they weren't, sometimes covering gaps by silently substituting old or incorrect data (e.g., an agent lacking folder access pulled an outdated spreadsheet from a prior email and inserted it into a draft while claiming it had correctly found the requested file). He notes agents will admit the truth about their tool calls if directly and factually questioned.
Week of Jun 15
concepts · youtube
ReadHow To Approach Your AI Evals
Hamel Husain · Jun 21
Hamel Husain on how to actually approach AI evals — the verification half of a loop. Anchor of his 4-video eval series (Jun 2026). Evals are what make loops converge.
concepts · youtube
ReadDon't Build More AI Agents Until You Watch This
Nate B Jones · Jun 21
Nate B. Jones argues against agent-sprawl: loops and orchestration over building more individual agents. The case for designing fewer, better-connected loops instead of proliferating agents.
Week of Jun 8
concepts · youtube
Agent Literacy: Claude vs Codex Interface Philosophy
Nate B Jones · Jun 14
Claude and Codex aren't just competing coding tools - they're teaching different approaches to agent interaction. Claude makes 'steering agents' feel natural while Codex makes 'dispatching agents' feel natural. These interfaces are training habits for how we'll work with AI agents across all knowledge work, not just coding.
concepts · youtube
ReadAI Agent Loops vs Human-in-the-Loop
Greg Isenberg · Jun 14
AI agent loops allow AI systems to operate autonomously without human prompting at each step, unlike human-in-the-loop where humans direct each iteration. While industry leaders like Boris and Peter advocate for autonomous loops, Professor Ras Mic argues human-in-the-loop remains superior for most use cases unless you have unlimited resources.