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Explores whether analytics agents should incorporate contextual data from tools like Linear, Sentry, and Notion, or remain purely metrics-driven.
A tweet shares a prompt to use X MCP with Grok Build to create draft X articles via agents, emphasizing manual approval before publishing.
GPT-5.6 has been released, representing a significant model jump toward powerful agents, serious coding, better reasoning, and creative work.
Introduces Hierarchical Experimentalist Agents (HExA), an in-context, experiment-centric self-improvement framework that enables LLM agents to design experiments, learn reusable skills, and answer queries in novel domains, achieving significant improvements over baselines on the Interphyre physics simulation benchmark.
Philipp Schmid announces his attendance at the aiDotEngineer conference, where he will discuss agents and evals, and can be found at the GoogleDeepMind booth or talks.
Google released Agents CLI, a unified command-line tool that integrates scaffolding, evaluation, and deployment of agents on Google Cloud, enabling coding assistants to practice agentic engineering without context switching.
A discussion on techniques for keeping LLM agents consistently in character, highlighting an often overlooked aspect of steering.
A hackathon for building AI agents that can handle business operations, sponsored by NVIDIA, Stripe, and Nous Research, with prizes including cash, DGX Spark, and Stripe credits.
Anton Osika shares that Lovable designer Niklas's personal mission is to create the best interface for agents, emphasizing the importance of extreme ownership in teams.
Jerry Liu agrees that both agents and software have value, but notes that their interfaces are different—agents use simple communication interfaces like chat, while software tools need tailored interfaces for specific tasks.
The article compares two patterns for deploying AI agents in the cloud: directly in sandboxes vs decoupling components. It explains the limitations of the sandbox approach due to cloud failures, and highlights Anthropic's Claude Managed Agent as a solution that decouples session store, agent runtime, and sandbox for resilience.
A detailed article introducing Loop Prompt Engineering, a method to automate prompt optimization by iteratively rewriting prompts based on evaluation against a dataset, with emphasis on avoiding recursive traps.
The LangChain team has open-sourced the tutorial 'Deep Agents from Scratch', which deconstructs the core design patterns of mainstream agents from scratch, covering task planning, context offloading to a file system, and sub-agent isolation. It includes 5 progressive notebooks, allowing you to build a complete deep research agent hands-on.
Vercel launched Eve, an agent framework with built-in observability, debugging, durable execution, and sandboxed compute, aiming to simplify production agent development.
LangChain shares a discussion between Brace Sproul and Jake Broekhuizen comparing the use of MCPs versus CLIs when building agents.
BlitzOS is a free and open-source Mac app that allows users to run multiple AI agents (like Claude and Codex) in one place, connect them to any browser app, and manage their progress via a live kanban board.
OpenAI's Codex saw over 5x growth in active users in the first half of 2026, with non-developer teams like Legal and Finance driving the fastest adoption. Usage shifted towards longer tasks, and Codex now generates 99.8% of OpenAI's weekly output tokens.
A curated list of 93 free projects for AI engineers covering MCP, Agents, and RAG, shared by Matt Dancho.
The article explores the problem of AI agents trusting and selecting among over 1,300 paid services on Coinbase's Base blockchain via the x402 standard, and asks the community for ideas on how to evaluate service reliability.
A staff engineer describes how LLM agents have evolved by 2026 to become reliable collaborators for coding, debugging, and codebase research, while humans retain responsibility for judgment and review.