The Archive

MASS-RAG: multi-agent synthesis for RAG with role-specialized agents for summarization, extraction, and reasoning over noisy/incomplete contexts.

AI tools are significantly accelerating software development and changing how developers work with code. These tools serve as real-time copilots, automating... AI tools are significantly accelerating software development and changing how developers work with code. These tools serve as real-time copilots, automating repetitive tasks, executing tasks, writing documentation, and more. OpenAI Codex, for example, is a coding agent designed to assist developers through tasks like code generation, debugging, and automated pull request (PR) creation. Source

Tech workers in China are being instructed by their bosses to train AI agents to replace them—and it’s prompting a wave of soul-searching among otherwise enthusiastic early adopters. Earlier this month a GitHub project called Colleague Skill, which claimed workers could use it to “distill” their colleagues’ skills and personality traits and replicate them with…

Analysis of headless API-first architecture replacing GUI interaction for personal AI agents, citing Salesforce Agentforce.

MACE multi-agent framework verifies claims from tabular data using specialized Planner, Executor, Verifier agents with zero-shot CoT.

Benchmark of 10 frontier LLM agents on NYU CTF Bench offensive cybersecurity tasks across 7 providers, 200 challenges.

Graph-of-Agents proposes graph-based multi-agent LLM orchestration with node sampling and decoupled communication to improve task performance over Mixture-of-Agents.

SeekerGym benchmark evaluates completeness and trustworthiness of information retrieved by deep research AI agents, addressing information gaps and bias.

HIVEMIND applies OS scheduling primitives (admission control, AIMD backpressure, circuit breaking) to coordinate concurrent LLM coding agents sharing rate-limited API endpoints.

Coding agents are starting to write production code at scale. Stripe’s agents generate 1,300+ PRs per week. Ramp attributes 30% of merged PRs to agents.... Coding agents are starting to write production code at scale. Stripe’s agents generate 1,300+ PRs per week. Ramp attributes 30% of merged PRs to agents. Spotify reports 650+ agent-generated PRs per month. Tools like Claude Code and Codex make hundreds of API calls per coding session, each carrying the full conversation history. Behind every one of these workflows is an inference stack under… Source

Agents are evolving from question-and-answer systems into long-running autonomous assistants that read files, call APIs, and drive multi-step workflows.... Source

Developing real-time vision AI applications presents a significant challenge for developers, often demanding intricate data pipelines, countless lines of code,... Developing real-time vision AI applications presents a significant challenge for developers, often demanding intricate data pipelines, countless lines of code, and lengthy development cycles. NVIDIA DeepStream 9 removes these development barriers using coding agents, such as Claude Code or Cursor, to help you easily create deployable, optimized code that brings your vision AI applications to… Source

Anthropic releases Claude Opus 4.7 with improved coding, agents, vision, and multi-step reasoning capabilities.

OpenAI updates Agents SDK with native sandbox execution and model-native harness for secure, long-running agent development.

Notion ships knowledge work AI agents via 5 rebuilds, 100+ tools, and MCP integration after internal infrastructure overhaul.

Import AI 453 examines agent vulnerabilities, MirrorCode tool, and disempowerment strategies for AI systems.

We cap out our World Models coverage with one of the most exciting new approaches - long running, multiplayer, interactive world models built with agents bootstrapped from game engines!

Gradient Labs deploys GPT-4.1 and GPT-5.4 mini/nano agents for automated banking support with low-latency agentic workflows.

Mistral releases Spaces, a CLI tool designed for both human developers and autonomous agents.

Mistral AI shares design philosophy for CLI tools supporting both human users and AI agents, emphasizing unified tooling that improves developer experience.

Agentic AI is an ecosystem where specialized models work together to handle planning, reasoning, retrieval, and safety guardrailing. As these systems scale,... Agentic AI is an ecosystem where specialized models work together to handle planning, reasoning, retrieval, and safety guardrailing. As these systems scale, developers need models that can understand real-world multimodal data, converse naturally with users globally, and operate safely across languages and modalities. At GTC 2026, NVIDIA introduced a new generation of NVIDIA Nemotron models… Source

Mistral open-sources Voxtral, a fast, adaptable TTS model for voice agents with real-time synthesis.

OpenAI uses chain-of-thought monitoring to detect misalignment risks in internal coding agents via real-world deployment analysis.

While consumer AI offers powerful capabilities, workplace tools often suffer from disjointed data and limited context. Built with LangChain, the NVIDIA AI-Q... While consumer AI offers powerful capabilities, workplace tools often suffer from disjointed data and limited context. Built with LangChain, the NVIDIA AI-Q blueprint is an open source template that bridges this gap. LangChain recently introduced an enterprise agent platform built with NVIDIA AI to support scalable, production-ready agent development. This tutorial, available as an NVIDIA… Source

AI-native services are exposing a new bottleneck in AI infrastructure: As millions of users, agents, and devices demand access to intelligence, the challenge is... AI-native services are exposing a new bottleneck in AI infrastructure: As millions of users, agents, and devices demand access to intelligence, the challenge is shifting from peak training throughput to delivering deterministic inference at scale—predictable latency, jitter, and sustainable token economics. NVIDIA announced at GTC 2026 that telcos and distributed cloud providers are… Source

AI‑native organizations increasingly face scaling challenges as agentic AI workflows drive context windows to millions of tokens and models scale toward... AI‑native organizations increasingly face scaling challenges as agentic AI workflows drive context windows to millions of tokens and models scale toward trillions of parameters. These systems rely on agentic long‑term memory for context that persists across turns, tools, and sessions so agents can build on prior reasoning instead of starting from scratch on every request. Source

Autonomous AI agents are driving the next wave of AI innovation. These agents must often manage long-running tasks that use multiple communication channels and... Autonomous AI agents are driving the next wave of AI innovation. These agents must often manage long-running tasks that use multiple communication channels and background subprocesses simultaneously to explore options, test solutions, and generate optimal results. This places extreme demands on local compute. NVIDIA DGX Spark provides the performance necessary for autonomous agents to execute… Source