Agent, take the wheel.
Agents are here to manage generic workflows from beginning to end. The more specialised the workflow is, the more expertise the agent can get.
The 3 Core Parts of an AI Agent
1. Brain (LLM) 2. Tools (APIs, browser, database) 3. Memory (context over time)
How it works
You give a goal
It breaks goal into steps
It chooses tools
It checks results
It repeats until done
Real World Example
- Searches web - Extracts data - Structures comparison - Outputs summary table - ...
What's the Catch?
Agents aren't perfect, their autonomy usually means you will have to double check the results. - Can make wrong decisions - Can misuse tools - Expensive (multiple model calls) - Hard to debug
Why Everyone Talks About Agents
We are shifting from having a “Software you use” to having a “Software that works for you.” Having the speed of a machine and the brain of a human would allow workflows to be exponentially faster.
What Should You Learn Next?
Beginner path: 1. Prompting basics 2. APIs 3. Simple automation flows 4. Agent frameworks Start small. Automate one workflow.