AGENTS - AI Dynamics

AI Conductor Model Uses RL to Automate Prompt Engineering

By

–

27 April 2026 16h55

For the past few years, humans have been doing “prompt engineering” to coax the best performance out of different LLMs. In this work, we explored what happens if we train an AI to do that job instead. By training a Conductor model with RL, we found that it naturally learns to

→ View original post on X — @hardmaru

27 April 2026

AI Conductor Framework Learns to Orchestrate Multiple Agent Teams

By

@sakanaailabs

–

27 April 2026 16h54

Introducing our new work: “Learning to Orchestrate Agents in Natural Language with the Conductor” accepted at #ICLR2026 https://
arxiv.org/abs/2512.04388 What if we trained an AI not to solve problems directly, but to act as a manager that delegates tasks to a diverse team of other AIs?

→ View original post on X — @sakanaailabs

27 April 2026

Join Us or Refer Exceptional AI Talent Today

By

@rowancheung

–

27 April 2026 16h14

Join us or refer the most exceptional person you know:

→ View original post on X — @rowancheung

27 April 2026

AI Agent Incidents: Backup Recovery Strategy for Production Systems

By

@simonw

–

27 April 2026 16h04

Backups fix that too. If the agent spent six hours rewriting your production logic good backups will let you roll back those six hours, of both data changes AND code changes

→ View original post on X — @simonw

27 April 2026

Enterprise AI Shifts From Prompting to Autonomous Agents

By

@bernardmarr

–

27 April 2026 16h01

👥 For a while, prompt engineering was treated as the must-have AI skill. Enterprise AI is moving into agents, autonomous systems that chain tasks, make decisions, and act across real workflows.

In this video, I explain:
✅ Why prompting matters less as AI becomes agent-driven… pic.twitter.com/vNo9n1YoE5
— Bernard Marr (@BernardMarr) 27 avril 2026

For a while, prompt engineering was treated as the must-have AI skill. Enterprise AI is moving into agents, autonomous systems that chain tasks, make decisions, and act across real workflows. In this video, I explain: Why prompting matters less as AI becomes agent-driven

→ View original post on X — @bernardmarr

27 April 2026

Sandbox limitations and AI system safety constraints discussion

By

@simonw

–

27 April 2026 16h00

I want my sandboxes to limit what they can do when they are running It sounds like you and I may have different definitions of "sandbox"

→ View original post on X — @simonw

27 April 2026

AI Agents Rollout Too Fast: Safety Concerns Paramount

By

@garymarcus

–

27 April 2026 15h32

AI agents are wildly premature technology that is being rolled out way too fast. The deepest lesson about the vibe coded AI agent disaster story that is running around is NOT about losing your data. 𝗜𝘁’𝘀 𝗮𝗯𝗼𝘂𝘁 𝗔𝗜 𝘀𝗮𝗳𝗲𝘁𝘆. The user wasn’t (totally) naive.

→ View original post on X — @garymarcus

27 April 2026

Anthropic Account Support Scaling: Claude vs Human Managers

By

@soumithchintala

–

27 April 2026 15h29

This is kinda interesting. Anthro probably needs to scale up Account Support via Claude or via humans (traditional account managers). Would be funny if they chose humans. Alternatively, more and more companies can probably go multi-AI with open harnesses. Similar problems to

→ View original post on X — @soumithchintala

27 April 2026