Agentic Explainability at Scale: Corporate Fears and 'Agent Sprawl'
What happened
As companies rapidly adopt agentic AI, concerns are rising about agent autonomy and associated risks, particularly with "Agent Sprawl" due to low-code applications outpacing governance. Current observability tools often lack insight into agent configurations, settings, or decision-making during interactions.
Why it matters
CTOs and VPs of Engineering deploying agentic AI must prioritize scaling governance alongside low-code agent adoption to mitigate "Agent Sprawl" risks, implementing robust explainability techniques at both design and runtime.
Topics
- Agentic AI
- AI Governance
- Agent Sprawl
- Explainable AI
Articles in this trend
- Agentic Explainability at Scale: Between Corporate Fears and XAI Needs — Takara TLDR - Daily AI Papers
- Dario Amodei, hype, AI safety, and the explosion of vibe-coded AI disasters — Marcus on AI
- Why AI Systems Struggle With Truth, Trust, and Reliability — Artificial Intelligence on Medium
- When Correct Systems Produce the Wrong Outcomes — AI & ML – Radar
- Why Should I Trust You? (and Can I?) — Deep Learning on Medium
- Dispatches from O'Reilly: Fast paths and slow paths — Stack Overflow Blog
- Building an AI Agent That Distrusts Itself: Starting With the Jail, Not the Brain — AI Advances - Medium
- Red-teaming a network of agents: Understanding what breaks when AI agents interact at scale — Microsoft Research
- The Sequence Opinion #864: Every AI Agent Needs a Computer — TheSequence
- The Production Gap: 5 Patterns for Building Long-Running AI Agents* — Turing Post
- Frontier model collapse is near — Machine Learning ML & Generative AI News
- AI agents don’t just need better reasoning. They need better stopping rules. — Artificial Intelligence