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@AdamRLucek on how we use traces to build evals for production agents.
AUTOMATION
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Using Traces to Build Production Agent Evaluations
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Multi-Agent Retention Patterns in Graph-Based AI Systems
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Multi-agent retention is a great extension of this. The execution agent needs a tight working set, the audit agent needs full provenance. Context templates in Graphiti help here. Same underlying graph, but each agent gets a different view scoped by edge types, entity types, and
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SkillOS: Agents Learn Once, All Level Up
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AI agents shouldn’t start from zero every time. SkillOS captures what works from each job, turns it into a tested Skill, and shares it with every approved Agent. One Agent learns.
All Agents level up. That’s how AI work becomes compounding intelligence. -
MagicPath Introduces Figma Export with AI Agent Integration
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Introducing Figma export in MagicPath.
— Pietro Schirano (@skirano) 26 mai 2026
Design and build with our native agent, or your favorite external one (Codex, Claude Code, etc.).
Explore tons of different directions, then bring your work into Figma as fully editable designs.
As simple as a copy-paste. pic.twitter.com/ON9h0UCXpuIntroducing Figma export in MagicPath. Design and build with our native agent, or your favorite external one (Codex, Claude Code, etc.). Explore tons of different directions, then bring your work into Figma as fully editable designs. As simple as a copy-paste.
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AI Copilot for Industrial Telemetry Analysis and Documentation
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The system feeds live and historical telemetry into the same copilot connected to ABB's documentation library for analysis.
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Long-Horizon Agents: Attention Scaling and Sleep Mechanisms
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// Language Models Need Sleep // Let your agents "sleep", folks. On a serious note, this is a fascinating paper on getting the most from long-horizon agents. Here is the problem with agents today: Attention scales badly with context length, so long-horizon agents keep paying a
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Coding Agents as Tool-Using Systems with API Support
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Coding agents are no longer chatbots, they’re tool-using systems that read files, run tests, patch code, and iterate until it works. That’s why we’re adding /v1/responses support across SambaCloud, SambaStack, and SambaManaged for faster agent workflows.
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LangChain Academy: Build AI Agents with LangSmith Fleet Essentials
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LangChain Academy Course: LangSmith Fleet Essentials Learn how to build your own agents with LangSmith Fleet. Anyone can now build, use, and manage an agent fleet for complex daily tasks, without writing code. In this quickstart course, you'll learn how to build and improve
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LangSmith Engine Accelerates Self-Optimizing AI Loops
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LangSmith Engine makes your self-optimizing loops spin faster and faster
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Helio Public Beta: Describe Goals, Get AI Team in 60s
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Helio moved to public beta, allowing anyone to describe a goal in plain language and get a working AI team up and running in under 60 seconds. > We set up an HR Manager, a Content Editor, and a Content Writer as AI teammates for TestingCatalog News. > Created a task and