AI Agents articles
101 articles about AI Agents, newest first.
- Stop Guessing: How OpenSEO Turns AI Agents into SEO Pros — Discover how OpenSEO combines real-time search data with AI agents to automate keyword research and competitor analysis without the hallucinations.
- DeepSeek Harness Explained: 10x Faster AI Agents — Discover how DeepSeek Harness supercharges LLM agents with a simple install and 10x performance boost. Perfect for developers and AI enthusiasts.
- AI Agents Auto‑Optimize Their Harnesses: How Opus 5, GPT‑5.6 Sol and KIMI K3 Work — AI agents now optimize other agents' harness structures, using tools like Opus 5, GPT‑5.6 Sol and KIMI K3 to boost performance.
- Stop Building 'God-Agents': Lessons from Anthropic's CCA Exam — Learn the core patterns of agentic engineering, from context discipline to tool-use branching, based on the Claude Certified Architect exam.
- Why AI Agents Fail in Big Business (and Win in Small Ones) — Discover why enterprise bureaucracy is killing AI ROI and how small businesses are actually leveraging agentic AI to win.
- Prime Agent: Why the 'Harness' is More Important Than the Model — Discover how Prime Agent replaces clunky JSON tools with an IPython kernel to create recursive, self-improving AI agents.
- Beyond the Chatbot: How AI 'Harnesses' Enable Self-Evolving Research — Explore how agentic runtimes like Argus transform static LLMs into autonomous researchers through external state and verification-guided persistence.
- From Brittle Graphs to Deep Agents: How Harmonic 4x'd User Retention — Learn how Harmonic replaced complex query graphs with a flexible agentic loop to drastically improve AI reliability and user retention.
- When AI Agents Lie: Understanding 'False Success' — Learn why AI agents report tasks as complete when they haven't actually done the work and how to stop 'reward hacking' in your workflows.
- GitHub Goldmine: Turning Books into AI Skills and Running Huge Models on Tiny GPUs — Explore the latest AI breakthroughs from GitHub, including AirLLM for low-VRAM model loading and tools that turn books into reusable AI skills.
- Stop Struggling with Production: LangChain's Managed Deep Agents Explained — Learn how LangChain's Managed Deep Agents bridge the gap between AI prototypes and production-ready agents using LangSmith.
- Beyond the Chatbox: Understanding AI Orchestration and Agent Workflows — Explore the shift from simple prompting to AI orchestration, covering OpenAI Symphony, local models with Ollama, and the rise of autonomous agent workflows.
- Beyond the Chatbot: The Rise of AI Agents That Actually Do Work — Explore the shift from AI that talks to AI that acts, featuring new tools for autonomous calling, voice-coding, and robotic automation.
- From 12 Weeks to 2: How Madrigal Pharmaceuticals Scaled AI Agents — Discover how Madrigal Pharmaceuticals used LangChain and LangSmith to slash AI deployment times and master agent observability.
- Can AI Agents Fact-Check Science? The ICML 2026 Reproduction Challenge — Hugging Face's massive experiment used AI agents to reproduce 2,000+ research papers, testing the validity of cutting-edge AI science.
- Stop the Crash: How Harness-R1 Keeps AI Racing Agents on Track — Discover how Harness-R1 uses a meta-controller to create 'software guardrails' for autonomous AI agents without needing to retrain the core model.
- From Prompt to Production: Meet the AI Agent That Builds Entire Apps — Discover Buzz, the AI agent workspace that writes, tests, and deploys full applications from a single prompt.
- Agentic AI: Moving From Chatbots to Autonomous Do-Bots — Discover how Agentic AI transforms LLMs from simple conversationalists into autonomous agents that can plan, execute, and self-correct.
- Stop Chasing AI Hype: How to Actually Get ROI from Your LLMs — Learn why the secret to AI profitability isn't a better model or a fancier agent, but a smarter integration into your business workflows.
- Stop Building Chains: The Shift to Outcome-Driven AI Agents — Learn why moving from rigid, step-by-step agent workflows to outcome-focused architectures is the key to building truly autonomous AI.
- Beyond Correctness: Why Cognition Built FrontierCode — Discover why standard AI benchmarks like SWE-bench are failing and how Cognition's FrontierCode focuses on 'mergeability' over simple correctness.
- Stop Writing Your Own Tests: Let AI Agents Do the Heavy Lifting — Discover how AI agents are transforming software testing by automatically generating test suites and finding edge cases you missed.
- Stop Building AI Platforms: Why Outcomes Trump Outputs — Learn why most AI agent projects fail and how to shift from building 'fancy software' to delivering actual business outcomes.
- From Chatbots to Teammates: Mastering AI Agents with Hyperagent — Discover how Hyperagent transforms Slack into a multi-agent AI workforce that automates lead gen, research, and outreach.
- Herdr: Orchestrating a Herd of AI Coders in Your Terminal — Stop drowning in terminal windows. Learn how Herdr lets you manage multiple parallel AI coding agents through a single, clean interface.
- The Death of Monolithic AI: The Scaffold & Harness Paradigm — Explore the shift from giant, single-model AI to modular 'Agentic' frameworks that use scaffolds and harnesses to self-evolve and solve complex problems.
- Beyond the Prompt: The 9 Layers of Production-Ready AI Agents — Moving AI agents from demo to production requires more than a prompt. Discover the 9 architectural layers needed for reliability, safety, and scale.
- From Laid Off to AI Engineer: Building a Job Search Agent with Claude — Learn how Mads Lorentzen used Claude and a multi-agent AI workflow to automate his job search and gain 30K GitHub stars.
- Local AI Made Easy: Run Your Own AI Stack with ODS — Stop paying for API tokens and reclaim your privacy. Learn how to use the Open Deployment Stack (ODS) to run LLMs and AI agents locally.
- Beyond Prompting: The Rise of Autonomous Problem-Finding AI — Stop perfecting your prompts. Learn why the future of AI is about letting agents find your business bottlenecks and solve them autonomously.