Quality went up alongside output. Even with more PRs shipping, total incidents dropped 5%. They built security guardrails and quality standards into the agentic workflow itself. Productivity vs quality is sometimes framed as a tradeoff. They're not seeing it.
AUTOMATION
-
AI Agents Transform Workflows and Organizational Structure
By
–
The teams seeing the biggest wins from AI are completely changing how they work, not speeding up what they already do. What steps can you delete, what handoffs go away, what can an agent just own end to end. Great to see Salesforce go this deep. Shoutout to Srini, @Benioff &
-
AI Agent Memory Management and Data Structure Integration
By
–
好问题，这两个点很关键，安装本身不会改写原有 agent 的本地记忆文件；如果发现可导入的历史记忆，会先扫描并征得确认，再进入 EverMe 的结构化抽取/归类流程。 验证上，可以用一条已知历史事实跨 agent/session recall，并在 Memory Hub 里反查 source。如果未来停用，影响的是 EverMe
-
Open-Source Voice Agents Replace Proprietary Paid Platforms
By
–
You can now run unlimited voice agents for $0.
— AlphaSignal AI (@AlphaSignalAI) 29 mai 2026
Building a voice agent today usually means renting one.
You pay per minute. You hand over call data.
You hope the closed platform you depend on does not change terms.
A team of YC alumni just shipped the open source way out.… pic.twitter.com/AiNBJWULbgYou can now run unlimited voice agents for $0. Building a voice agent today usually means renting one. You pay per minute. You hand over call data. You hope the closed platform you depend on does not change terms. A team of YC alumni just shipped the open source way out.
-
Agentic layer enables autonomous fact-based optimization
By
–
The agentic layer closes the loop entirely, pushing fact-based optimizations without waiting for human intervention.
-
Four Layers of Industrial AI: From Prediction to Automation
By
–
Industrial AI operates across four layers: predictive forecasts what's coming, prescriptive recommends actions, generative exposes insights in natural language, agentic pushes optimizations directly to control systems. #industrialai #manufacturing
-
Teaching Robots Complex Tasks Without Extensive Training
By
–
Teaching #Robots to do complex tasks WITHOUT spending hours training them
— Ronald van Loon (@Ronald_vanLoon) 29 mai 2026
via @IlirAliu_
#Robotics #AI #ArtificialIntelligence #MachineLearning #MI #Tech pic.twitter.com/QsA3VhFyOITeaching #Robots to do complex tasks WITHOUT spending hours training them
via @IlirAliu_ #Robotics #AI #ArtificialIntelligence #MachineLearning #MI #Tech -
Claude Dynamic Workflows: Parallel Subagents for Task Automation
By
–
Claude's new Dynamic Workflows is amazing!
— AlphaSignal AI (@AlphaSignalAI) 29 mai 2026
1. Set model to Opus 4.8
2. Reasoning effort to /ultracode
It can spawn hundreds of subagents working in parallel to take on massive tasks. https://t.co/xa3mA4ewqF pic.twitter.com/frh9lov5wfClaude's new Dynamic Workflows is amazing! 1. Set model to Opus 4.8
2. Reasoning effort to /ultracode It can spawn hundreds of subagents working in parallel to take on massive tasks. -
20-minute intro to Managed Deep Agents by Runkle and Moreira16
By
–
.@sydneyrunkle + @VictorMoreira16 with a 20 minute intro to Managed Deep Agents.
— LangChain (@LangChain) 29 mai 2026
Watch the full Interrupt keynote: https://t.co/jDvoDG6wek pic.twitter.com/hcBAIcUHpL.
@sydneyrunkle + @VictorMoreira16 with a 20 minute intro to Managed Deep Agents. Watch the full Interrupt keynote: https://
youtu.be/LdQpoK2TzSo