What Are AI Agents?
AI agents are AI systems that can take actions autonomously to accomplish goals. Unlike chatbots that just respond, agents can browse the web, write code, use tools, and interact with other software.
The Next Frontier
Agents represent the shift from AI that talks to AI that acts. They're expected to transform how we work and interact with computers.
How Agents Differ from Assistants
- Assistants: Answer questions, generate text → Human takes action
- Agents: Understand goal → Plan steps → Take actions → Verify results
How Agents Work
- Goal — Receive a high-level objective
- Plan — Break into subtasks
- Act — Execute using tools (browse, code, APIs)
- Observe — Check results
- Iterate — Adjust approach if needed
Types of Agents
Coding Agents
Write, test, and debug code automatically. Examples: Devin, GitHub Copilot Workspace.
Research Agents
Browse the web, gather information, summarize findings. Examples: Perplexity, OpenAI's browsing mode.
Task Automation Agents
Complete workflows across applications—scheduling, data entry, email processing.
Computer Use Agents
Control your computer like a human would—clicking, typing, navigating applications.
Current Capabilities
- Web browsing and research
- Code writing and execution
- File management and creation
- Using APIs and web services
- Multi-step problem solving
Limitations
- Reliability — Still make errors on complex tasks
- Guardrails needed — Can take unintended actions
- Cost — Multiple LLM calls add up
- Speed — Multi-step tasks take time
- Trust — How much autonomy to grant?
Risks and Concerns
- Unintended actions — Agents might do something you didn't want
- Security — Accessing sensitive systems
- Job displacement — Automating significant work
- Runaway behavior — Agents pursuing goals incorrectly
The Future
- Personal AI assistants that manage your digital life
- Autonomous coding that writes entire applications
- Business process automation at scale
- Scientific research agents making discoveries
Summary
- • AI agents can take autonomous actions to accomplish goals
- • They plan, execute, and iterate like a human worker would
- • Current uses: coding, research, automation
- • Reliability and trust are key challenges