Tagged: agents

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Anthropic announced MCP

Berkeley AI Research group published a piece on compound AI systems

Google introduced the Agent-to-Agent (A2A) protocol

moved their coding agent from outside the top 30 to the top 5

named it in February 2026

offered a useful analogy

official MCP server registry

OpenAI's Agents SDK

Salesforce acquired it

writing on Martin Fowler's site

Beyond LLMs: Anatomy of Agentic Systems

From compound AI systems to the agentic loop, MCP, APIs, frameworks, and the rise of the Claws — a technical map of what it takes to build with AI agents in 2026.

Beyond LLMs: The Whole Product Framework for AI

What Maslow's hierarchy of needs, Levitt's whole product model, and Geoffrey Moore's crossing the chasm can teach us about building AI products that actually ship.

a PR against Liquid

autoimprove on GitHub

autoimprove presentation

Karpathy's autoresearch

Shopify Liquid PR #2056

From Autoresearch to Autoimprove: Generalizing the Agentic Experiment Loop

Two unrelated projects discovered the same pattern: point an AI agent at code, give it a score to chase, and let it run experiments until morning. I generalized it into a tool that works for any domain.

17% lower on comprehension tests

Anthropic published a study

highly-upvoted post on r/ClaudeAI

large-scale study with 234 students

Observing Without Doing: Pseudo-Apprenticeship Patterns in Student LLM Use

one post with 2,700+ upvotes

put it well on X

senior developer on r/learnprogramming

University of Saarland study on knowledge transfer in AI pair programming

Shadowing AI: What I Learned by Watching Agents Code

I've been learning new programming languages by watching AI coding agents work — like shadowing a colleague. The research says this should make me worse. Here's why I think it's more complicated than that.

1.7x more issues

Agentic Engineering Patterns

AI Agents and Code Review

As one practitioner put it

Making Coding Agents Reliable

State of AI vs Human Code Generation Report

The 80% Problem in Agentic Coding

The AI Coding Trust Gap

Using Linters to Direct Agents

Why Your AI Coding Assistant Keeps Doing It Wrong

Shrinking the Verification Gap: Practical Patterns for AI-Assisted Development

If AI scales execution and verification is the bottleneck, the winning move is to make verification cheaper. Here are the patterns that actually work.

Agent Skills (SKILL.md)

Galileo's research on multi-agent coordination

Jimmy Song wrote

OpenAI's September 2025 research

Tetrate wrote about securing the MCP supply chain

what CoSAI has been calling for

I Vibe-coded an open registry for AI agents

Container registries store bytes. They don't know what's inside. The Agent Registry is a governance layer for AI agents, skills, and MCP servers, built on A2A AgentCard, MCP server.json, and Agent Skills as native identity formats.

Claw Gateway Network Atlas

Six gateway architectures for AI agents, ranked from full control plane to no gateway at all. Interactive diagrams with animated data flows.

Coleman et al., 2022

— Coleman et al., 2022

10 Things Developers Want from Agentic IDEs

Agent Access Control on GitHub

Agent Access Control Presentation

Agent Access Control

Claude Code is the Inflection Point

Claude Code vs Cursor

Coleman et al. (2022)

CyberArk wrote about this

DevEx: What Actually Drives Productivity

Do Cloud Developers Prefer CLIs or Web Consoles?

GitHub Octoverse 2025

Gravitee surveyed 900+ practitioners

JetBrains Developer Ecosystem 2025

MCP Gateway on GitHub

Measuring AI Impact on Developer Productivity

most agents hold 10x more privileges than required

OWASP released their Agentic AI Top 10

OWASP Top 10 for Agentic Applications 2026

Securing Agentic Applications Guide 1.0

Stack Overflow Developer Survey 2025

State of AI Agent Security 2026

The Rise of AI Agents and the Reinvention of Kubernetes

Warp State of the CLI 2023

What's Shaping the AI Agent Security Market in 2026

Why CLIs Are Better for AI Coding Agents Than IDEs

Don't Teach Your Agents Karate

Every agent team rebuilds the same auth, rate limiting, and credential management. I built an agent gateway for Kubernetes that generates it all from two CRDs so the people building agents never touch security and the people running the platform never touch agent code.

Your terminal is an AI runtime now

AI coding agents pulled developers back to the terminal. But the data says the real split isn't CLI versus GUI. It's about what you're doing.

1,000+ servers in the community registry

10-15% of IT spending in 2026

Agent Registry in Copilot

Agent Registry on GitHub

AI 2026: Infra Agentic Runtime

AI Supply Chain Security Imperative

an MCP catalog

announced an enterprise MCP registry

Cloud API Registry integration

Deploying Agentic AI with Safety and Security

Gartner also predicts

Gartner analyst noted

MIT researcher posted in r/artificial

Multi-Agent Coordination Failure Mitigation

official MCP Registry

one r/kubernetes commenter put it

OpenAI Research on Training Procedures

realized LLMs are terrible at infra

Research measuring hallucination rates

Securing the MCP Supply Chain

Tray.ai coined the term "Shadow MCP"

Agent Access Control

The agent gateway for Kubernetes. Covers agent discovery, authentication, routing, credential injection, rate limiting, and MCP protocol support.

Agent Registry

A vendor-neutral registry for AI agents, skills, and MCP servers. Covers the problem of agent discovery, the registry architecture, and how agentctl works.