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harness engineering > prompt engineering prompts get you 80% there the last 20% — tool routing, memory retrieval, retry logic, evals — thats…

Harrison Chase, co-founder of LangChain, argues that while prompt engineering is foundational and can get you 80% of the way to a functional AI system, the remaining 20% of engineering effort involves

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Agents

Have an idea for an experiment? Hermes can now write conference-grade research papers alongside you.

DGX agent

Have an idea for an experiment? Hermes can now write conference-grade research papers alongside you. Media introducing Autoreason, a reasoning method inspired by @karpathy's AutoResearch which extends

agentsnous-research--x

12 Apr 2026

I fed The Godfather into a structured knowledge graph, here's what the MCP tools surface

A Reddit post from the r/ollama community demonstrating a practical experiment in which a user ingested the narrative content of *The Godfather* into a structured knowledge graph and then queried it u

agentsr-ollama

Memory, the next toe-hold for closed AI platforms; increasing user ergonomics whilst playing the long game against customers.

Memory features in AI platforms represent a strategic mechanism for increasing user retention and platform lock-in, as personalized context and learned preferences become increasingly difficult to mig

Not your memory not your life

Harrison Chase, co-founder of LangChain, likely discusses the concept that AI agents and systems lacking persistent memory cannot truly learn, adapt, or maintain continuity across interactions — makin

The clarity of this piece by @hwchase17 is immense. No jargon.

Harrison Chase, the creator of LangChain, shared or was referenced in a post praising a piece of writing attributed to him for its clarity and accessibility, notably avoiding technical jargon. The con

This. And i know it works very well.

Harrison Chase, the co-founder and CEO of LangChain, shared or endorsed a post on X (formerly Twitter) expressing strong confidence in a particular approach, tool, or method, stating it 'works very we

🔗 Codex App: https://chatgpt.com/codex/

OpenAI's Codex App (available at chatgpt.com/codex) is a dedicated command center for agentic coding, enabling developers to manage multiple AI coding agents working in parallel across projects. T...

model-releasesopenai--x

Most illuminating graph I have seen for definition of harness. Memory and context are deeply coupled with harness. In my humble opinion, how…

Most illuminating graph I have seen for definition of harness. Memory and context are deeply coupled with harness. In my humble opinion, how they are injected and managed are one of most important pie

The most important post I've read all week by @hwchase17 . Memory, particularly memory consistency is the biggest performance inhibitor to A…

The most important post I've read all week by @hwchase17 . Memory, particularly memory consistency is the biggest performance inhibitor to AI agents today. As we interact with different harnesses and

This is why you need model agnostic harnesses

model-releasesharrison-chase--x

I was unable to retrieve the content of that specific X (Twitter) post, as web search results did not surface the tweet or its content. X.com posts are generally not indexed in a way that makes the...

What if owning the memory layer goes far beyond escaping lock-in? What if memory becomes fully editable intelligence? You could debug bad pa…

What if owning the memory layer goes far beyond escaping lock-in? What if memory becomes fully editable intelligence? You could debug bad patterns, reinforce good ones, and crucially synthesize new on

middleware is underrated

I wasn't able to retrieve the content of that specific tweet or URL from the search results. X (Twitter) posts are generally not indexed in a way that allows direct retrieval of their content, and ...

My X bookmarks have an 'intellectual shape' Apparently mine is: Technique-heavy, Tool-obsessed, Light on Opinion I didn't know until I ran t…

My X bookmarks have an 'intellectual shape' Apparently mine is: Technique-heavy, Tool-obsessed, Light on Opinion I didn't know until I ran the numbers OSS I've been building w/@LangChain to explore Ge

One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration

arXiv:2510.12088v2 Announce Type: replace Abstract: Symbolic world modeling requires inferring and representing an environment's transitional dynamics as an executable program. Prior work has focused

PriPG-RL: Privileged Planner-Guided Reinforcement Learning for Partially Observable Systems with Anytime-Feasible MPC

arXiv:2604.08036v1 Announce Type: cross Abstract: This paper addresses the problem of training a reinforcement learning (RL) policy under partial observability by exploiting a privileged, anytime-feas

safetyarxiv-cs-ro

Speed of open source! Anthropic adds advisor strategy yesterday -> Emanuele adds an implementation as middleware less than 24 hours later!

Speed of open source! Anthropic adds advisor strategy yesterday -> Emanuele adds an implementation as middleware less than 24 hours later! Just shipped advisor-middleware: an open-source implementatio

The Illusion of Stochasticity in LLMs

arXiv:2604.06543v1 Announce Type: cross Abstract: In this work, we demonstrate that reliable stochastic sampling is a fundamental yet unfulfilled requirement for Large Language Models (LLMs) operating

agentsarxiv-cs-lg

We have @liadyosef and @idosal1 at @aiDotEngineer talking MCP apps and why we need them.

Nick Taylor (@nickytonline) shared a post highlighting a talk at AI Engineer (@aiDotEngineer) featuring Liad Yosef (@liadyosef) and Ido Salomon (@idosal1) on the topic of MCP apps and their importa...

agentsswyx--x

Working Paper: Towards a Category-theoretic Comparative Framework for Artificial General Intelligence

arXiv:2603.28906v2 Announce Type: replace Abstract: AGI has become the Holly Grail of AI with the promise of level intelligence and the major Tech companies around the world are investing unprecedente

@3blue1brown https://x.com/verncrawford/status/2042344703077859402?s=46

@3blue1brown https://x.com/verncrawford/status/2042344703077859402?s=46 @NousResearch 2 prompts guys. 2 prompts!!! The second prompt was “go from 6 camera moves to 3.” (Hermes Agent, Codex5.4, Manim V

agentsnous-research--x

9 Apr 2026

Claude Cowork, now generally available!

model-releasesboris-cherny--x

Claude Cowork, now generally available! We released Claude Cowork as a research preview 12 weeks ago. Since then, millions of people have made it part of how they work - and hundreds of thousands more

9 Apr 2026

i have been waiting for this ...

I'm sorry, but I'm unable to retrieve the content of that specific post. The URL points to an X (formerly Twitter) post that requires JavaScript and user authentication to load, and my web search w...

9 Apr 2026

@3blue1brown https://x.com/tobi/status/2041719844920283326

I was unable to retrieve the specific content of the two X/Twitter posts referenced (NousResearch status/2041974602826457364 and tobi status/2041719844920283326), as X requires authentication to ac...

agentsnous-research--x

8 Apr 2026

https://x.com/Vtrivedy10/status/2041927488918413589

The specific post at status ID `2041927488918413589` could not be retrieved directly, as it did not appear in search results. However, based on the surrounding context from the same account (@Vtriv...

8 Apr 2026

> which is exactly why we believe memory should live outside of model providers open harness = open memory which everyone should want!

> which is exactly why we believe memory should live outside of model providers open harness = open memory which everyone should want! The new Anthropic managed agents API is basically the Letta API t

8 Apr 2026

ARGUS: An Agenda-Driven Framework for Reliable User Simulation

arXiv:2610.21346v1 Announce Type: new Abstract: High-fidelity user simulators are essential for evaluating and training agents in interactive environments. However, current LLM-based simulators strugg

Beyond Retrieval Failure: Understanding Why LLMs Miss Evidence in Multi-Hop RAG

arXiv:2610.21184v1 Announce Type: new Abstract: Multi-hop retrieval-augmented generation (RAG) requires an agent to retrieve evidence for a sequence of dependent sub-questions. When a wrong answer lac

agentsarxiv-cs-cl

Dell’s infrastructure strategy takes shape as enterprise AI moves into production

At the enterprise level, agentic AI has become less of a prospective tool for businesses, evolving into a valuable asset for many organizations. As more companies shift from the experimentation phase

agentssiliconangle

Intern-Decision: Efficient Multimodal Decision Making with Autoregressive Masked Language Modeling

arXiv:2610.22131v1 Announce Type: new Abstract: Interactive agents repeatedly choose among a finite set of actions, labels, or ordinal outcomes. Generating a free-form response for each choice adds la

agentsarxiv-cs-cl

Memorilla: Latent Semantic Memory for LLMs

arXiv:2610.21375v1 Announce Type: cross Abstract: Memory enables large language models (LLMs) to use information beyond their parameters, such as past user conversations, long documents, or an agent's

Reinforcement Learning-driven Diffusion Models: Language, Vision, and Beyond

arXiv:2610.21539v1 Announce Type: new Abstract: Diffusion models (DMs) have steadily demonstrated outstanding performance in high-fidelity, controllable generation across diverse scenarios, following

Stronger Judges Do Not See More: Deployment-Integrity Blindness in LLM Evaluation

arXiv:2610.21135v1 Announce Type: cross Abstract: LLM-agent evaluation reports behavioral scores but leaves the identity of the deployed runtime stack unreported. A tampered deployment that preserves

Hardware

AReaL-RSI: Adaptive Scaling and Coordination of Recursive Self-Improvement

arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m

hardwarearxiv-cs-ai

AuthGateBench: Benchmarking LLMs as Authorization Gate

arXiv:2610.16426v1 Announce Type: new Abstract: Automated approval systems let coding agents execute high-risk actions with minimal human oversight by delegating the authorization decision to a classi

Avoiding What Your Teacher Already Knows: Entity Familiarity for Deep-Search Distillation

arXiv:2610.16251v1 Announce Type: cross Abstract: Deep-search agents are commonly trained by distilling tool-use trajectories from stronger teacher models. However, structurally complex questions may

Can Generative AI Automate Data Extraction for Meta-Analysis? A Case Study on Intercropping Research

arXiv:2609.35089v2 Announce Type: replace Abstract: Meta-analysis is the synthesis of information from multiple sources to arrive at an overarching conclusion. There is a large need for meta-analysis

Contextual Credit Policy Optimization

arXiv:2610.19103v1 Announce Type: new Abstract: Group-based reinforcement learning enables large language model agents to learn from sparse outcome rewards in long-horizon tasks. Recent methods derive

safetyarxiv-cs-lg

Delta Tokenizer: Reference-Identical Tokenization of Session Deltas and Segment-Parallelism for Long Prompts on Multicore CPUs

arXiv:2610.19801v1 Announce Type: new Abstract: An agent that drives an LLM sends the model the same conversation again and again, and each turn adds only a little text at the end. Inference engines r

agentsarxiv-cs-cl

Explorer-Zero: Improving Self-Play for Long-Horizon Tasks with Decomposable Verifiable Rewards

arXiv:2610.19868v1 Announce Type: cross Abstract: Training LLM agents on long-horizon interactive tasks with reinforcement learning typically relies on human-annotated tasks and reliable verification,

agentsarxiv-cs-lg

Judges Follow the Reference: The Derivation Gap in Verifying Tool-Call Arguments

arXiv:2610.18497v1 Announce Type: new Abstract: Tool-call judges evaluate argument values proposed by LLM agents. We find that they accept a correct value less often when their input holds no referenc

Large Language Model Assisted Transportation Planning through a Differentiable User Equilibrium Layer

arXiv:2610.16140v1 Announce Type: new Abstract: Transportation planning has traditionally required substantial expertise in network modeling, traffic assignment, and optimization. As a result, strateg

LATCH: LLM-Assisted Timing Closure Harness for Post-Route FPGA Optimisation

arXiv:2610.16625v1 Announce Type: new Abstract: Post-route FPGA timing closure remains expert-dependent and computationally expensive. We present LATCH (LLM-Assisted Timing Closure Harness), a two-lay

Long-Horizon RL Needs Muon

arXiv:2610.20256v1 Announce Type: new Abstract: Long-horizon agents must coordinate reasoning, tool use, and environment feedback over extended interactions. Learning from sparse outcome rewards requi

safetyarxiv-cs-lg

MemDuet: Learning Dual-Process Memory for Long-Context Reasoning

arXiv:2610.19928v1 Announce Type: new Abstract: Reasoning over infinitely long documents is becoming a reality with recurrent memory agents. However, increasing context length exacerbates the trade-of

safetyarxiv-cs-cl

Meta Muse Spark Open is live on Together AI

model-releasestogether-ai-blog

Meta’s Muse Spark Open, a high‑capacity US open‑weight model for agentic software engineering, is now live on Together AI as a Day 0 launch partner. The model supports a 1‑million‑token context window

Muse Spark Open is now live on Together AI. We're proud to be a Day 0 launch partner for @AIatMeta's Muse Spark Open, the most capable US op…

Muse Spark Open is now live on Together AI. We're proud to be a Day 0 launch partner for @AIatMeta's Muse Spark Open, the most capable US open-weights model to date, built for long-running agentic cod

agentstogether-ai--x

VideoHarness-SRSI: Structured Recursive Self-Improvement for Video Understanding Harness

arXiv:2610.19424v1 Announce Type: new Abstract: LLM system capabilities depend not only on model parameters but also on the executable harnesses that organize information acquisition, tool use, reason

agentsarxiv-cs-cv