groundy

agents & frameworks

107 articles·rss

Top in agents & frameworks


  1. jul 07agentsCan Multi-Agent RAG Run Air-Gapped? A Forensics System Shows How
  2. jul 07agentsCan You Prove an Agentic Trading Pipeline Has No Look-Ahead Bias?
  3. jul 07agentsHow Far Ahead Can a Coding Agent Plan? The Horizon Bottleneck
  4. jul 06agentsSymbolic Inference Forces Agent Frameworks to Expose Intermediate State
  5. jul 05agentsBOUNDARY_SYNC: Why Multi-Agent Representational Coupling Is the New Coordination Failure Mode
  6. jun 29agentsDo Multi-Agent RAG Systems Write Better READMEs Than One Agent?
  7. jun 28agentsAgentic AI Turns Location Trails Into a Re-Identification Tool
  8. jun 28agentsHow a Human-Agent Team Lifts One Video Into 4D Interactions
  9. jun 28agentsCan LLM Agents Learn Cooperation Laws From Embodied Play?
  10. jun 28agentsGovern the Repo, Not the Agent: A New Risk Metric for AI-Native Code
  11. jun 27agentsCan an AI Agent Catch Cryptographic Misuse Before It Ships? Chai Tests the Claim
  12. jun 26agentsCan Spec-Driven Development Keep AI Coding Agents From Drifting?
  13. jun 25agentsCan Knowledge-Based Pull Requests Make Agent Contributions Auditable?
  14. jun 25agentsDo AI Agents Hold Up Outside Familiar Environments? A New Eval Says No
  15. jun 25agentsHow Much Repo Structure Does a Coding Agent Actually Need?
  16. jun 25agentsMCP vs A2A: Two Agent Protocols, One Integration Layer Decision
  17. jun 24agentsCan You Rewind an AI Agent Mid-Run? Reversible Traces Say Yes
  18. jun 24agentsCan AI Agents Reproduce Published Research? CORE-Bench Tests It
  19. jun 24agentsHow On-Device AI Agents Keep Learning by Forgetting on Purpose
  20. jun 24agentsDo AGENTS.md Files Actually Help Coding Agents? A New Benchmark Tests It
  21. jun 24agentsShould AI Shopping Agents Pay Micro-Transactions for Verified Product Data?
  22. jun 23agentsCan a Conversational Graph Compile Into a Goal-Oriented Dialogue Runtime?
  23. jun 23agentsCan a Cryptographic Certificate Prove an AI Agent's Output Is Valid?
  24. jun 23agentsCrewAI vs AutoGen vs Microsoft Agent Framework: AutoGen's Merger Reframes the 2026 Choice
  25. jun 23agentsCan You Trust an LLM Judge to Grade an Agentic Data Analysis System?
  26. jun 23agentsDo LLM Agent Societies Develop Their Own Authority Hierarchies?
  27. jun 23agentsDo Retrieval Metrics Predict Tool-Use Agent Success? A Paper Says No
  28. jun 23agentsCan You Pinpoint Which Step Broke a Long-Horizon AI Agent?
  29. jun 20agentsDeep-Research Benchmarks Hide How Agents Fail at Open-Web Source Grounding
  30. jun 20agentsDSPy Ships Autonomous Prompt Optimization, but Judge Drift Is the Failure Mode
  31. jun 20agentsDo AI Agents Reach for Over-Privileged Tools When Simpler Ones Suffice?
  32. jun 20agentsWhen Should Multi-Agent Systems Use an Event Bus Instead of an Orchestrator?
  33. jun 19agentsCan Deontic Policy Rules Govern an AI Agent at Runtime?
  34. jun 14agentsDo Programming Languages Still Matter to Your AI Coding Agent?
  35. jun 14agentsWhy Production AI Agents Fail Silently and Your Logs Never Catch It
  36. jun 11agentsComputer-Use Agents Fabricate Success on 8 to 33 Percent of Long-Horizon Tasks
  37. jun 09agentsCan AI Agents Share Context Without a Central Coordinator?
  38. jun 09agentsWhy Skill Creation and Reward Optimization Collide in Agentic RL
  39. jun 09agentsWhen AI Agents Delegate Work, Your Observability Stack Goes Blind
  40. jun 08agentsBloomberg's Pomona Makes Small Automated Code Changes, Not Big Agent PRs
  41. jun 08agentsAgent Tool-Gating Moves From Prompt Rules to Learned Policies
  42. jun 08agentsMore Capable LLMs Cooperate Less in Zero-Cost Collaboration Tests
  43. jun 07agentsWhy Foundation Model Agents Pass Benchmarks but Fail in Production
  44. jun 06agentsCan AI Agents Repair Broken Network Configs? A New Benchmark Tests It
  45. jun 06agentsCan Self-Evolving AI Agents Drift Without a Human in the Loop?
  46. jun 05agentsFine-Tuning Multi-Agent LLM Systems: RL Enters Where Prompt Tweaks Stall
  47. jun 05agentsCascading Hallucination in Agentic RAG: When One Bad Retrieval Poisons the Chain
  48. jun 04agentsCan AI Agents Build Other Agents? The Meta-Agent Challenge Says Mostly Not Yet
  49. jun 03agentsWhen MCP Tool Descriptions Don't Match the Code, Agents Trust the Lie
  50. jun 02agentsWhen an AI Agent Causes a Loss, Who Files the Insurance Claim?

Agent frameworks ship faster than the rigor operators need to run them. Vendor docs promise orchestration, memory, and tool use; academic benchmarks and production post-mortems keep exposing the same structural gaps: diversity collapse in multi-agent ideation, hallucination amplification across consensus topologies, missing per-step rationale traces, role-based retry losing to graph-state failure isolation on long tasks, and configuration surfaces that punish static templates. This beat covers that delta.

The second through-line is governance and trust. Skill registries, tool-use protocols, and capability manifests are accumulating faster than auditable contracts for them. Trust schemas, contractual skill specs, and information-flow controls are arriving as bolt-ons rather than primitives, while the infrastructure layer — sandbox execution, private networking, agent memory — keeps absorbing functionality the framework layer used to own. The question of where the agent stack actually lives, and who is liable when it misbehaves, stays unresolved.

Coverage is comparative and opinionated. When a benchmark or paper exposes a gap that a major framework cannot close without redesign, that gets named. When a vendor ships governance theater rather than enforcement, that gets named too. The goal is help readers pick stacks that survive contact with production, not a taxonomy of every framework release.