Stage 1: Observing the Agent Workflow
Watch a scripted agent workflow break down a complex task. This visualization shows illustrative observable steps, not live tool results or a model’s private reasoning. This demo loops until the task is complete or blocked by its configured human-approval gate; other agents may use different controls.
Agent Configuration
Toggle tool availability before starting the agent to see how it reacts to missing tools.
Stage 2: Dynamic Constraints & Counterfactuals
This scripted sandbox illustrates how an agent could react to errors and constraints. Adjust the fictional budget and weather inputs below and observe the prewritten plan changes. No live prices, forecasts, searches, or bookings are used.
Scenario Constraints
Scripted demo prices: flight $120; train $45. These are not current quotes.
Frequently Asked Questions
How does the agent know which tool to pick?
Tools are provided to the model as a list of functions with descriptions. The Planner analyzes the user's prompt, looks at the available tools, and outputs a structured command specifying which function to run and with what arguments.
What happens if a tool fails?
A well-designed agent receives the error message back into its context window as a new observation. It can then reason about the failure and dynamically try an alternative approach or report the failure to the user.
Can agents run forever?
Yes, if poorly designed, they can get stuck in infinite loops of trying and failing. System designers prevent this by implementing a 'Max Steps' limit or computational budget.
Is the Human-in-the-loop strictly necessary?
That depends on the task, risk, and system design. Approval gates are a useful control for consequential actions such as spending money, deleting data, or sending messages, but they are not universal and do not guarantee safety. Systems may also use scoped permissions, limits, validation, monitoring, and rollback.
Conclusion
You've completed the core lessons. Hopefully, artificial intelligence feels a little less like magic, and a lot more like understandable, structured technology.
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