# How Do AI Agents Work > A comprehensive educational site explaining AI agents — how they work, > what they can do, how to build one, and a beginner's guide. Updated for 2026. ## Core Content - [How Do AI Agents Work?](https://www.howdoaiagentswork.com/): Deep technical guide covering AI agent architecture (perception, reasoning, planning, tool use, memory loop), complete workflow breakdown, and comparisons with chatbots and RPA. - [What Is an AI Agent?](https://www.howdoaiagentswork.com/what-is-an-ai-agent/): Plain-English definition: model + tools + loop + memory, 2026 examples, five types, and how agents differ from chatbots. - [Best AI Agents for Coding](https://www.howdoaiagentswork.com/best-ai-agents-for-coding/): Five tested coding-agent picks for 2026 — Claude Code, Codex / GPT-6 Astra, Cursor, GLM-5.3, and Qwen3.8-27B — with criteria, pricing, and tradeoffs. - [What Can AI Agents Do?](https://www.howdoaiagentswork.com/what-can-ai-agents-do/): 50+ real-world examples across 10 industries — coding, customer service, healthcare, finance, marketing, cybersecurity, content creation, and more. - [Create Your Own AI Agent](https://www.howdoaiagentswork.com/how-to-create-an-ai-agent/): Step-by-step build guide with Python code examples covering LangGraph, CrewAI, and the OpenAI Agents SDK. - [How Do AI Agents Work for Beginners?](https://www.howdoaiagentswork.com/beginners-guide/): Plain-English introduction to AI agents with everyday analogies. No jargon. - [AI Agent Framework Comparison](https://www.howdoaiagentswork.com/ai-agent-framework-comparison/): Decision guide comparing LangGraph, CrewAI, OpenAI Agents SDK, Pydantic AI, and Microsoft Agent Framework. - [Best AI Agent Framework 2026](https://www.howdoaiagentswork.com/best-ai-agent-framework-2026/): Ranked framework picks by production control, prototype speed, typed Python, multi-agent experimentation, and Azure/.NET fit. - [AI Agent Tutorial](https://www.howdoaiagentswork.com/ai-agent-tutorial/): Focused Python tutorial for a bounded reason-act-observe tool loop. - [DeepSeek Harness](https://www.howdoaiagentswork.com/deepseek-harness/): What DeepSeek Harness is — DeepSeek's first agent product, plugin architecture, open-sourced eval harness, and how it compares to other runtimes. - [DeepSeek Harness Explained](https://www.howdoaiagentswork.com/deepseek-harness-explained/): Hands-on guide to running DeepSeek Harness from npm, with verified commands and gotchas. - [GLM-5.3 Review](https://www.howdoaiagentswork.com/glm-5-3-review/): Hands-on look at Zhipu's open-source coding model — benchmarks, GLM Coding Plan testing, and how it compares to closed flagships. - [Who Is Behind Ox Alpha?](https://www.howdoaiagentswork.com/ox-alpha/): OpenRouter stealth model: fingerprint evidence vs GLM-5.3, the retracted DeepSWE score, and what a $0 preview actually costs you. - [Run Qwen3.8-27B Locally](https://www.howdoaiagentswork.com/run-qwen3-8-27b-locally/): Practical deploy guide for Alibaba's 27B open-weight multimodal model on Mac (MLX) or a single consumer GPU (GGUF / vLLM). - [Ornith-1.5 Review](https://www.howdoaiagentswork.com/ornith-1-5-review/): Open-weight 9B/35B/397B family from DeepReinforce, claimed Claude Opus 4.8 parity on agentic coding, plus local-run notes. - [AI Agent Guide](https://www.howdoaiagentswork.com/ai-agent-guide/): 2026 hub on what an AI agent is, types, architecture, memory, security, and how to run agents locally. - [Hugging Face Guide](https://www.howdoaiagentswork.com/hugging-face-guide/): What Hugging Face is, how the model hub works, how to download models, and how to run them locally. - [NVIDIA Buys Hugging Face](https://www.howdoaiagentswork.com/nvidia-buys-hugging-face/): The reported $12.9B acquisition, why NVIDIA wants the open-source hub, and what it means for developers. - [Hugging Face Microduck](https://www.howdoaiagentswork.com/hugging-face-microduck/): A $399 open-source robot duck you train with sim-to-real reinforcement learning — hardware, price, and Hugging Face's physical-AI bet. - [Perplexity Portable Computer](https://www.howdoaiagentswork.com/perplexity-portable-computer/): A fully local AI agent on NVIDIA DGX Spark: zero token cost, private data stays on device, cloud only by explicit escalation. - [How Reasoning Models Decide How Much to Think](https://www.howdoaiagentswork.com/how-reasoning-models-decide-how-much-to-think/): How reasoning models can pick their own thinking depth (NoThink / Short / Long) and cut token use by 41% with no accuracy loss. - [How AI Agents Learn to Use Tools](https://www.howdoaiagentswork.com/how-ai-agents-learn-to-use-tools/): MidTool research: tool use wants its own mid-training stage, and MCP skills are already showing up inside the training pipeline. - [OrcaRouter Review](https://www.howdoaiagentswork.com/orcarouter/): AI inference gateway that routes prompts across 200+ models with zero token markup, plus how it compares to OpenRouter. - [Qwen3.8-27B Uncensored](https://www.howdoaiagentswork.com/qwen3-8-uncensored/): What the abliterated research build is, who it's for, the risks, and why most users should run the official model. - [AI Agent Memory Management](https://www.howdoaiagentswork.com/anthropic-agent-memory/): Anthropic Managed Agents memory and "dreaming," plus how to build agents that learn across sessions instead of starting from zero. - [AI Agent Security](https://www.howdoaiagentswork.com/ai-agent-security/): How agents escape sandboxes, the Black Hat 2026 OpenAI / Hugging Face case, and how to defend agentic systems. - [OpenAI Astra](https://www.howdoaiagentswork.com/openai-astra/): Persistent agents, a Critical cybersecurity pause, and a 20% monitoring tax — confirmed facts vs rumors about OpenAI's unreleased model. - [Hugging Face Incident](https://www.howdoaiagentswork.com/hugging-face-incident/): Full postmortem of the 1,200-agent sandbox escape: shared message board, self-organized swarm, and zero who told a human. - [Multi-Agent AI Behavior](https://www.howdoaiagentswork.com/multi-agent-ai-behavior/): 2026 research on what happens when agents team up — emergence, deception, trust breakdown, and how to design for verification. - [How to Build an AI Agent with Claude](https://www.howdoaiagentswork.com/build-ai-agent-with-claude/): Claude-specific Python tutorial covering Anthropic tool use, a bounded loop, and tool permission and safety checks. - [Create Your Own AI Agent for Free](https://www.howdoaiagentswork.com/create-your-own-ai-agent-free/): Local Ollama and open-model path with a Python tool loop, honest cost notes, and local safety boundaries. - [AI Agent Beginner Guide](https://www.howdoaiagentswork.com/ai-agent-beginner-guide/): Five-minute introduction to goals, tools, memory, and safe agent use. - [AI Agent Memory Cost Calculator](https://www.howdoaiagentswork.com/ai-agent-memory-cost-calculator/): Estimate embedding and vector storage cost from workload, retention, and vendor pricing assumptions. - [AI Agent Token Budget Calculator](https://www.howdoaiagentswork.com/ai-agent-token-budget-calculator/): Estimate tokens and model spend per run and per month, with a suggested hard cap for runaway loops. - [AI Agent Cost Calculator](https://www.howdoaiagentswork.com/ai-agent-cost-calculator/): Pick a model and task volume to estimate monthly API spend, with a local $0 comparison. - [AI Agent Cost Tracking](https://www.howdoaiagentswork.com/ai-agent-cost-tracking/): Event schema and telemetry guide for model, tool, memory, retry, and successful-task costs. - [AI Agent Cost Control](https://www.howdoaiagentswork.com/ai-agent-cost-control/): Practical strategies for hard budgets, model routing, context reduction, caching, retry limits, and quality-preserving cost reduction. - [AI Agent Safety Benchmark Comparison](https://www.howdoaiagentswork.com/ai-agent-safety-benchmark-comparison/): Compare AgentDojo, ToolEmu, AgentHarm, and CyberSecEval by safety question, setting, metrics, and limitations. ## Signals - /signal/: dated, sourced log of AI agent events (launches, demos, research, incidents). Each entry links back to the original source; nothing is re-uploaded or re-hosted here. - /signal/{slug}/: one event page with date, category, a one-line mechanism take, sources, and an optional link to the related deep-dive article. - Cite the original source (sources[].url) when referencing an event; link the /signal/{slug}/ page for the directory entry. ## Optional - The site includes original SVG architecture diagrams, comparison tables, and a "Was this helpful?" feedback widget on every page.