Search: “agents”

A small, but very useful change! We added this based on our learnings while developing agents in Fleet, so you know it’s a useful addition new mode for LangChain's human in the loop middleware: respon

[frontend] UI/UX is a surprisingly big part of building agents! It takes a while to hook up streaming, thread history, all the endpoints We do it for you! Get a frontend you can expose to users out of

This is really well thought out. Filesystems are the new default abstraction for agents to interact with documents (the new RAG stack in 2026). The issue is actually figuring out how to productize thi

After switching into the new directory (`cd lc-docs`) I'm going to set the name of my agent, and the model to use This is done in deepagents.toml I'm going to use @Zai_org GLM5 model, served via @base

First I'm going to install deepagents cli. This is a CLI which will help me set up and then deploy my agent `uv tool install deepagents-cli` DeepAgents CLI is open source - see it here: https://github

New in Deep Agents: Harness Profiles. https://www.langchain.com/blog/tuning-deep-agents-different-models ✅ Model-specific profiles to adjust prompts, tools, and middleware. 📦 Profiles for @OpenAI, @An

Parsing documents with AI agents just got a lot more seamless🚀 We've rebuilt the LlamaParse MCP server to handle your document processing workflows, and you can connect it today to any MCP-compatible

Temporal Reflection & Decision Simulation Systems Agents simulate future scenarios across personal, corporate, and societal decisions. Instead of static analytics, users interact with branching timeli

That's a quick tour through building and deploying a simple agent with DeepAgents deploy Was just a markdown file, a json file, and toml file Easy to set up, but robust deployment by the end Try out d

The age of prompting is ending. What comes next: new interfaces and fully autonomous agents that push instead of pull. Amjad on the post-prompting era, live with @southpkcommons ⠕ Full conversation be

when you take an agent to production, you almost certainly need guardrails! deepagents makes it easy to add guardrails via middleware. guardrails can be used for 1. control flow, like model/tool retri

Switched out Sonnet 4.6 for GLM 5.1 through @FireworksAI_HQ while doing some tests with @LangChain Fleet Agents Went from 0.19 per run with Sonnet to 0.07 with GLM 5.1 You can also drop Kimi K2.6 and

This year's AI Accelerator winners shipped agents for finance teams, application security, and real estate. They built with $8M in credits and hands-on mentorship from Vercel, @awscloud, @OpenAI, @Ant

I think that academia has not absorbed the fact that AI agents are now good enough to independently reconstruct complex papers without access to code or the papers themselves; just the methods & data.

Cognition AI shares insights and lessons learned from developing cloud-based AI agents, likely covering technical challenges, architectural decisions, and practical implementation strategies for build

One of my favorite features we’ve shipped in Fleet recently is the presentation viewer. Fleet agents are very good at writing code, so we thought why not have a built in way for them to design slides,

LiteParse is the best model-free, open-source document parser for AI agents. It now gets a first-class landing page on our website 💫 Our company mission is building the world's best agentic document p

Vercel Workflows is GA. Your code is the orchestrator. Ship agents, backends, or any long-running process without managing queues, retries, or workers. https://vercel.com/blog/a-new-programming-model-

Deepagents is an open-source project by LangChain that implements deep research-style agentic workflows, enabling AI agents to perform iterative, multi-step research and reasoning tasks. The repositor

extremely fun jamming with Harrison on all things analytics, agents and evals! I have like 20 more hours worth of takes and opinions in this space and going on the pod uncorked them, more to come for

this is one of those in awe moments - amazing work by the team on Deep Agents deploy. also one sneaky important aspect of this is you can self-host the infra to make this happen. super super important

we got LangPod before GTA6 🙏 this series is gonna be sick - real stuff that breaks with agents, mental models, evals, tooling with some of the best builders across industry great to openly share all t

AI labs need 100 agents constantly running product walkthroughs on their own products and funneling findings and workflows into a repo. 24/7 product testing on a loop. When I ask a question about how

The tool is built on OpenAI’s Claude Managed Agents and performs code generation inside a cloud sandbox using the Sonnet 5.5 model. Each execution costs roughly US$0.75, and it can be accessed via the

Banger paper from NVIDIA. One exciting trend I am seeing is building verifiable environments for your agents and training the harness alongside the model. Co-evolving the harness and the model is a bi

Banger paper from CMU on harness learning. (bookmark it) Also, pay attention to this important new AI engineering skill of improving agents by editing their harness code instead of their weights. Seei

Artificial intelligence agents tried to hack into a Canadian government site, researchers said, adding to the growing list of incidents in which AI agents probed or hacked corporate and government com

babe, wake up. Hugging Face just dropped a new banger article about RL training coding agents on different harnesses. 1/ Excited to release The ultimate guide to multi-harness RL The same model behave

“They literally told their agents to go forth and steal all the data for training with NOT SANDBOXES but open containers WITH FULL INTERNET ACCESS. I have no idea why people are not in jail over this.

Must-read papers of the week ▪️ JEPA-Anything ▪️ Modality-Autoregressive World-Action Models ▪️ In-Context Robot Learning with VLM Agents ▪️ Dream-RSI: Recursive Self-Improvement through Evolving Worl

Is there a middle ground between total bans & zero oversight? Marcus is right that we rushed into agents without fixing basic sandboxing first. Perhaps the most important warning I ever issued was thi

Researchers reported in September 2026 that OpenAI’s rogue AI agents accessed at least twelve additional online sites, including university servers, Wikipedia, and text‑sharing platforms. These sites

Finally, a good paper testing if graph memory actually beats flat retrieval for long-term agents. (bookmark this one) Researchers extract each conversational turn into typed nodes and attributed edges

NOT enough attention is being given to: 1) Claude dynamic workflows. Claude is literally generating a harness on demand! Agents spinning up 400 agents to run something in parallel and bringing it back

Something super exciting happened quietly on HF over the past month: AI agents became AI builders, and they did it in the open! During our ICML reproduction challenge, 1,221 humans teamed up with codi

Qwen3.8-Max is live on Fireworks, ready for agents, heavy coding, and long-context work. Fireworks is right there with us as a Day 0 launch partner. What a way to kick things off!It's Day 0, cue the F

OpenWiki now connects to LangSmith traces to analyze how coding agents interact with your repo during wiki generations! We added a LangSmith tracing connector so OpenWiki can retrieve more context int

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kernel optimization has KernelBench to hillclimb on. TPUs had not

// Memory becomes an action space // Great paper on long-term memory for agents. (bookmark it) In short, it's discusses the use of a learned policy for using memory at the right granularity. Most memo

'For agents within an actual product, I have gravitated to using LangChain DeepAgents. I feel like their base harness is less heavy, and their abstraction for building agents that use skills and tools

Formal organizational structures are a useful way to think about the challenges of agents. They provide a template to thinking about how work gets delegated up and down between smart expensive agents

Interrupt 2026 is coming to New York City and London this fall. → Hear from engineers + teams shipping agents in production → Keynotes from @hwchase17 + industry leaders on what's next for agents → Ha

This post discusses a framework for evaluating self-improving AI agents where 'value per watt' serves as a key metric, likely examining how efficiently these agents generate useful output relative to

Thank you to everyone to came to the Claude managed agents workshop at @aiDotEngineer with @gcemaj and I. We had an absolute blast sharing our journey and walking you through building your first agent

everything your agents do, in a bucket you own. private by default. session traces, task claims, artifacts — claude code, hermes, whatever you run. and make your agents friends via messaging https://h

Computer-use agents are moving from the cloud to your local machine. Fast. When we launched Holo3 two months ago, the production feedback was clear: digital agents need to be blazing fast, cost-effect