AI agents differ from chatbots by pursuing autonomous goals through the ReACT loop rather than responding to turn-based prompts. While coding agents are currently the most reliable due to verifiable feedback loops, the market is expanding into desktop and browser automation via tools like Claude co-work and open claw.

Links

Notes and resources at ocdevel.com/mlg/mla-28
Try a walking desk - stay healthy & sharp while you learn & code
Generate a podcast - use my voice to listen to any AI generated content you want

Fundamental Definitions

Agent vs. Chatbot: Chatbots are turn-based and human-driven. Agents receive objectives and dynamically direct their own processes.
The ReACT Loop: Every modern agent uses the cycle: Thought -> Action -> Observation. This interleaved reasoning and tool usage allows agents to update plans and handle exceptions.
Performance: Models using agentic loops with self-correction outperform stronger zero-shot models. GPT-3.5 with an agent loop scored 95.1% on HumanEval, while zero-shot GPT-4 scored 67.0%.

The Agentic Spectrum

Chat: No tools or autonomy.
Chat + Tools: Human-driven web search or code execution.
Workflows: LLMs used in predefined code paths. The human designs the flow, the AI adds intelligence at specific nodes.
Agents: LLMs dynamically choose their own path and tools based on observations.

Tool Categories and Market Players

Developer Frameworks: Use LangGraph for complex, stateful graphs or CrewAI for role-based multi-agent delegation. OpenAI Agents SDK provides minimalist primitives (Handoffs, Sessions), while the Claude Agent SDK focuses on local computer interaction.
Workflow Automation: n8n and Zapier provide low-code interfaces. These are stable for repeatable business tasks but limited by fixed paths and a lack of persistent memory between runs.
Coding Agents: Claude Code, Cursor, and GitHub Copilot are the most advanced agents. They succeed because code provides an unambiguous feedback loop (pass/fail) for the ReACT cycle.
Desktop and Browser Agents: Claude Cowork( (released Jan 2026) operates in isolated VMs to produce documents. ChatGPT Atlas is a Chromium-based browser with integrated agent capabilities for web tasks.
Autonomous Agents: open claw is an open-source, local system with broad permissions across messaging, file systems, and hardware. While powerful, it carries high security risks, including 512 identified vulnerabilities and potential data exfiltration.

Infrastructure and Standards

MCP (Model Context Protocol): A universal standard for connecting agents to tools. It has 10,000+ servers and is used by Anthropic, OpenAI, and Google.
Future Outlook: By 2028, multi-agent coordination will be the default architecture. Gartner predicts 38% of organizations will utilize AI agents as formal team members, and the developer role will transition primarily to objective specification and output evaluation.

MLA 028 AI Agents

Machine Learning Guide