AI Odyssey

Grounding Agent Memory: When AI Must Check What It Remembers An AI assistant that remembers yesterday can repeat yesterday’s mistakes. This episode explores research from Microsoft on checking an agent’s memories...

Recursive Self-Improvement: AI Must Learn to Improve Its Own Learning An AI that fixes one answer has not necessarily learned anything for tomorrow. Recursive self-improvement asks for something harder: changes that...

When an AI agent fails after dozens of steps, the final error rarely reveals where the problem began. AGENTSCOPE turns long execution traces into structured reasoning-action graphs, then checks them against ten neural...

WikiSkill: Why Agent Experience Needs a Memory Layer Google Research's WikiSkill separates raw execution traces, persistent knowledge, and executable skills. The authors report that this architecture improves skill...

AI agents can regress even when their foundation model never changes. The culprit may be the harness around the model: prompts, memories, tools, skills, and routing rules that evolve after every task. This episode...

The next frontier in AI is not better prompts. It is systems that trigger, act, observe, judge, and stop on their own. This episode explores loop engineering: the shift from manual chat with an AI to autonomous...

<p>What if today’s “AI agents” are mostly automation pipelines wearing a more ambitious label?</p><p>This episode explores Critique of Agent Model, a paper that draws a sharp line between agentic systems, which look...

What if the best way for AI agents to learn together is to stop forcing them to share the same memory? This paper introduces DecentMem, a framework where each agent keeps its own adaptive memory instead of relying on...

<p>What if the best way for AI agents to learn together is to stop forcing them to share the same memory?</p><p>This paper introduces DecentMem, a framework where each agent keeps its own adaptive memory instead of...

<p>What if an AI agent could preserve a colleague’s judgment without pretending to become that person?</p><p><br></p><p>COLLEAGUE.SKILL turns chats, documents, emails, screenshots, and other traces into inspectable...

<p>What if the next leap in AI agents is not a bigger model, but a skill document that learns from failure? SkillOpt treats agent skills as trainable external memory: a separate optimizer edits a compact procedure, then...

<p>What happens when AI agents are asked to build the spreadsheets finance teams actually use?</p><p>WorkstreamBench, a benchmark for end-to-end financial spreadsheet work, exposes the gap between impressive demos and...

<p>Every forty years, the way we touch a computer changes shape. The command line gave way to the mouse. The mouse gave way to the touchscreen. And now, quietly, the screen itself is starting to disappear. In this...

<p>Most people assume an AI agent should ask for clarification as early as possible. This paper shows that the truth is more subtle.</p><p>For long-horizon agents — AI systems that execute many steps over time — the...

<p>What if multi-agent AI systems fail less because the models are weak, and more because the agents are badly coordinated? This paper treats coordination as an architectural layer : who talks to whom, who decides, how...