Search: “deployment”

Replit has introduced a built-in file conversion tool that allows users to convert files directly within the Replit platform. This feature is designed as an alternative to third-party file conversion

deepagents subagents are just tools. when you call a subagent, thats conceptually a function call. this is the simplest mental model for building multiagent systems. https://docs.langchain.com/oss/pyt

deepagents is a harness / planning tool, filesystem backend, subagent spawning, memory management / thats the stack that matters / models are the cpu, the harness is the os / anyways, check it out htt

Harness, Memory, Context Fragments, & the Bitter Lesson this is a work in progress mental dump on interesting intersections between how we use and design a harness, implications for memory being accum

I taught AI agents to 20,000 people for free, and for the next 12 hours, you can watch that exact same workshop replay. It’s 2026. You need to know how to build AI agents. I got you. If you’re a mom r

Most people building AI agents don't realize this until it's too late. Your agent's memory isn't a feature. It's your moat. 1. Closed harness = they own your memory 2. Switch models → lose all context

GBrain is my attempt to be in control of my own personal AI that could become my intentionally designed cognitive armor Open source open prompts means you aren’t under the API line It’s more important

Hot take: I can't see any startup building their critical core operations on Claude Managed Agents or any proprietary harness as investable. The past weeks have shown why it's critical to build on top

the fact that http://pi.dev agent is so good, with virtually no sophisticated harness whatsoever, is a testament to the fact token vendor (codex/claude) agents are overrated. highly. today's moat of c

time to help builders own their intelligence, open everything 🤝 the data produced and Experiential Memory gained from every agent interaction is the one of the most valuable things you can own to impr

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Best part? The spontaneous booth conversations with builders focused on turning AI ambition into production systems that scale. Open models are moving fast. The infrastructure around them is too. Grea

New Guide: Incorporating human judgment in the agent improvement loop Building agents is hard. Everyone talks about the code. What gets less attention is how to capture domain expert knowledge and act

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Wrapped up the 3-day AI Engineer conference in London. Key takeaways: Planning & verification > implementation. Humans define what to build and validate it works. AI handles the coding. The harness ma

Anthropic's new hosted service for long-running AI agents, designed to solve the challenge of creating systems that support 'programs as yet unthought of.' It abstracts infrastructure management to en

And that is what Thoth uses for its agents in the backend. Thanks for your contributions to oss @LangChain @hwchase17 https://github.com/siddsachar/Thoth AI that doesn't just work for you, it knows yo

You want a strong opensource and fully customisable harness?! None other than langchain’s deepagents. Try it yourself if in doubt. most of the agents we see being built do this the main cases where we

'Claude Code isn't magic. The harness layer is just software, and software is something any dev can shape to fit how they want to work.' Check out @Hacubu’s practical guide to building a custom agent

LangChain's 'Better Harness' tutorial, authored by Product Manager Vivek Trivedy and shared by Harrison Chase (@hwchase17), presents a hands-on, code-driven guide for using evaluations (evals) as a...

Highlights: 👉 28% coding improvement over GLM-5 with refined RL post-training 👉 Better long-horizon execution across hundreds of rounds and thousands of tool calls 👉 Thinking mode, tool calling, and s

If you're an AI/agent builder, it's so important that you don't overbuild and overcommit on a specific toolset and infrastructure. Frontier labs are shipping not just the models, but the harnesses and

David Silver is one of the all-time greats. He was the creator of AlphaGo, which changed the course of history by showing that neural nets could achieve superhuman performance for the first time. He a

Robots That Predict the Future: Dyna-2, Million-Hour World Models, & the Bitter Lesson of Robotics @DynaRobotics’s @JasonMa2020 explains how world-action models predict the future to guide physical ro

Today, we’re open sourcing the full NVIDIA Run:ai platform as part of the NVIDIA DSX AI Factory Platform. Developers, platform teams, and partners can build on production-grade AI workloads and GPU or

Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal custom models, driven by 10 years of experience training top mo

With only ~$1,000 of training compute, we trained 𝗳𝗿𝗼𝗺 𝘀𝗰𝗿𝗮𝘁𝗰𝗵 a 1.7B coding agent that beats Claude 3 Opus and GPT-4o on SWE-bench Verified 🤯 At 25.5% pass@1, it sets a new record for nanoswe, our op

Another great paper from Salesforce AI Research. The finding is that a 31B open Gemma-4 web agent scores 74.6% on the 9-app WebArena Infinity set, above Gemini 3 Flash with browser use at 70.1%. They

🟡 Semafor has announced the expanded co-chairs of Silicon Valley & The World, a first-of-its-kind, multi-year initiative connecting the leaders building transformative technologies with the policymake

On October 7, 2026, Clement Delangue noted that Microsoft’s Windows launch—highlighted by Satya Nadella and others—demonstrated the growing excitement around local AI solutions such as llamacpp. The e

Today I’m excited to introduce OpenDocRouter - a unified API for document parsing with the latest frontier and open-weight models. There are a lot of VLMs and OCR models that can be used for document

AI is driving the biggest infrastructure build-out in history, with @Google alone forecasting $200B of capex in 2026E. What are the real constraints on a system at this scale? Amin Vahdat is the chief

Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workl

Without a doubt evals are the biggest blocker in most agent development pipelines. We’re going to be changing that for everyone in LangSmith in a few short weeks… Hot take: evals are the #1 thing keep

Hot take: evals are the #1 thing keeping companies from becoming AI-native. If you want to understand evals, read this post & then the accompanying guide. Tweaking prompts and trying a few inputs by h

HuggingFace just closed a major gap in harness engineering! (the ultimate guide to multi-harness RL) the same open-weight model can perform well inside one harness, then lose accuracy or produce inval

AI researchers Zainhas and Parthsareen from Ollama delivered a breakout presentation on October 2, 2026, focusing on evaluating open-source models under real‑world production traffic rather than just

A thing to know about the AI business is labs that have frontier models can release half-built products and they work surprisingly well because the AI can just figure stuff out and improvise. Its like

Announcing our first open-weights world-action model, Praxis-1. It turns out that, unsurprisingly, you can get predictably better robotics policy performance by scaling third-person video. It’s been f

Your agent got the right answer. How much work did it take to get there? We worked with @NousResearch/@Teknium on a hands-on walkthrough of NVIDIA NeMo Relay to collect traces for Hermes Agent. Run tw

OpenAI’s “How we think about securing frontier RL training runs” (released September 29 2026) explains the company’s approach to safeguarding large‑scale reinforcement learning experiments. It details

“connect[ing] AI to the internet … safely with current technology is not a realistic goal...” Regardless of how well you think OpenAI security did their job, the thing people should take from this is

Today, with over 100 industry partners, we introduced the NVIDIA Open Agent Safety Platform, bringing together OpenShell and Sentry. Artificial intelligence is extraordinary technology that will advan

We are proud to be launch partners for NVIDIA Open Agent Safety Platform. We believe safe and responsible AI development is critical as the use of agents scale and they get more prevalent. Together AI

After the Hugging Face incident, we committed to conducting a much broader review of actions taken by our models during training and evaluation and to being transparent about our findings. This is an

Banger report on building faster memory for AI Agents. If your agent's memory layer is slow, this design is worth a look. Great weekend read. It proposes a new agentic memory architecture, Jev-Mem, in