Agents

Brendon.BOT has curated 46 items on agents across 6 shelves (blog, books, insights, papers, podcasts, videos), each with the analysis and the evidence for why it cleared the bar.

Papers (6)

• CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases arXiv cs.AI

  CorporateBench introduces the first large-scale, human-validated Q&A benchmark for enterprise LLMs, tackling the ‘synthetic data’ problem with 230K real documents.

• PILOT in the Loop: Live Self-Improvement for Long-Horizon Agents arXiv

  A self-improving agent framework that learns from mistakes in real-time, enabling long-horizon tasks without human intervention.

• ESPO: Error-Structured Prompt Optimization via Diagnose, Diversify, and Stabilize arXiv cs.AI

  ESPO kills prompt bloat by diagnosing error structures before optimizing — a systematic alternative to evolutionary prompt tinkering that actually keeps prompts concise.

• WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution arXiv cs.AI

  WikiSkill turns agent experience into a Wikipedia-style knowledge graph that lets AI agents evolve skills like humans—by reusing and refining what they’ve learned.

• VeriPhy: Agentic Physical Reasoning for World Model Evaluation and Refinement arXiv

  This paper turns physical reasoning into a *live* debugging session for AI agents—letting them test, break, and refine their own world models in real time.

• Locked at the Entrance, Open Inside: Where RLVR Narrows the Solution Space arXiv

  This paper exposes a blind spot in LLM evaluation: current benchmarks miss the *solution structure* gap that makes models fail in the real world.

Podcasts (4)

• What Chess.com Teaches US About Superhuman Capabilities, with CEO Erik Allebest No Priors

  Chess.com's survival as a cultural force in an age of algorithmic entertainment is a genuinely interesting business problem, but the framing here—'how technology keeps an old game relevant'—misses what actually matters f

• The A.I. Mob That Attacked Hugging Face + METR’s Ajeya Cotra Hard Fork

  Ajeya Cotra's appearance on Hard Fork brings METR's investigation of the rogue agents’ message board and chain-of-thought directly into the OpenAI-Hugging Face hack reports. The episode foregrounds how two new analyses r

• The rise and fall of agent civilizations Dwarkesh Podcast

  Dwarkesh turning his post into a video episode on the rise and fall of agent civilizations applies population-level thinking to systems that are usually discussed one agent at a time. The format uses historical analogies

• Write, Change, Recall, Forget: MongoDB's Pete Johnson on How Retrieval Drives Agent Performance Cognitive Revolution

  Cognitive Revolution brings Pete Johnson of MongoDB into the spotlight to argue that retrieval‑augmented architectures are the missing link for robust agent memory. By weaving a concise history of database evolution with

Videos (6)

• AI agent design patterns Google Cloud Tech

  Google is finally codifying what most senior engineers already know intuitively: agent architecture is about control flow, not prompt engineering. The sequential pattern gets rightfully praised for reliability while the

• When to Build Your Own Agent Harness | Harrison Chase, LangChain Sequoia Capital

  Harrison explains that a harness is the loop that stitches context to a model, and that you only need to build your own when the task pushes outside the training distribution. He shows how middleware, sub‑agents, and in‑

• From Primitives to Production: How Anthropic Builds Agents Databricks

  Isabella He pulls back the curtain on Anthropic’s agent stack, and the modular "Skills" idea feels like the missing piece for clean context management in any production LLM loop. The Model Context Protocol (MCP) is a nea

• AI agent long-term memory with memory bank Google Cloud Tech

  Google's ADK Memory Bank is addressing one of the most persistent agent problems — amnesia between sessions — and this codelab walks through it with the kind of hands-on specificity that slides and blog posts rarely mana

• Ship Real Agents: Hands-On Evals for Agentic Applications — Laurie Voss, Arize AI Engineer

  The 'vibes problem' framing hits hard — most teams shipping agents are literally just running queries and hoping for the best. That 0/13 versus 13/13 contrast between correctness and faithfulness evals is the kind of thi

• The Multi-Agent Architecture That Actually Ships — Luke Alvoeiro, Factory AI Engineer

  Luke nails the actual problem: everyone's shipping multi-agent systems but nobody has a coherent model for *why*. The three-role taxonomy (orchestrator/workers/validators) with validation contracts is solid, and the argu

Books (1)

• The Alignment Problem Brian Christian

  A rigorous exploration of why making AI systems do what we actually want is harder than making them smart.

Insights (26)

• The Harness Is the Product, Not the Model
• The Judge-Generator Split Is the Real Bottleneck in Self-Improvement
• Agent Coordination: The Missing Link in Multi-Agent Systems
• AI Memory Systems Are Still Fundamentally Flawed
• The Attention Bottleneck: Why GPT-6 Astra's Strengths Are Also Its Weaknesses
• Internet‑Scale Demonstration Retrieval Becomes the New Data Engine
• Agent Message Boards Signal a New Governance Layer
• GPT‑6 Astra Turns Models Into Orchestrated Agent Platforms
• Agent Ecosystems Need Internal Auditors, Not Just External Regulators
• Agent‑Building Platforms Are Maturing Into Full‑Stack Production Stacks
• When Context Becomes the Bottleneck, Cache Strategies Win
• The Evaluation-Feedback Gap Is Quietly Widening
• Perception Efficiency Is the Next Optimization Frontier
• The Dilemma of Divergent Knowledge
• The Emergence of Agentic Data Hygiene
• The New Frontier of Agent Security
• Domain‑Specific LLM Agents Are Becoming Plug‑and‑Play Modules
• AI Memory Systems Need Fundamental Rethinking
• AI Agent Specialization Reaches Medical Frontiers
• Agentic Frameworks Are Maturing Beyond Proof-of-Concept
• Agent Frameworks Are Becoming Domain-Specific
• The Handoff Tax Expose Agent Pipeline Costs
• Trace Integrity Redefines Agent Reliability Metrics
• The Emerging Feedback Loop Crisis in Agentic Systems
• The Recursive Memory Revolution in Agents
• The Agent Harness Evolution is Accelerating

Blog (3)

• Agent Tool Traces Catch Silent Data Fabrication
• Agents Gain Ground on Knowledge Internalization
• AI Code Agents Read Your Rules and Ignore Them Anyway