ai engineering / system design / ai agents / tool calling
AI Systems Design Interview: Build an Agent Loop in 3 Steps
How do you design an AI agent in a systems design interview? Austin walks through three steps: a minimal chat interface, tool calling, and a ReAct loop that executes actions and adds results to the conversation.
This is part 1 of the series. It covers the MVP and stopping conditions before the more complex architecture needed for senior AI engineering roles.
Transcript
0:00I'm an AI engineer and here's how you pass the AI Systems Design Round And this interview is
0:06extremely important for AI engineering positions that have you building AI agents So step one you want to
0:14define like the minimal product I mean the most minimal requirement of an AI agent which is literally
0:20you going on to a website like ChatGPT you type in something in the bar and it gives
0:27you a response Then step two you want to make it implement tool calling So instead of the
0:34response being a traditional response maybe the response is in JSON or maybe the response is a CLI
0:41command Step 3 you'll make it a loop and we call this ReAct Essentially you want to tell
0:50the LLM to respond with two things a thought process of things is done right now and the
0:56action of what it should do next The action is the tool call from step two You take
1:02the action you execute it so you execute the CLI command or you execute some sort of function
1:08that uses the JSON but you execute the tool and that gives you a result which you append
1:14to the conversation log and you do this over and over again until a certain number of iterations
1:21or until you have a tool call that says you're done This is just the MVP approach and
1:28a AI engineer that is hitting the senior level is building something that's much more complicated but this
1:34video is getting too long so like and follow for part two
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