Interactive Web Playground for Building and Testing AI Agents

Added Jun 2025 3 design docs

Teams adopting agentic AI face a practical bottleneck: configuring an agent means editing code, redeploying, and rerunning, which makes experimentation slow and discourages the rapid iteration that good agent design requires. Students and developers learning the technology hit the same wall, because there is rarely a safe place to try out roles, tools, and orchestration patterns and see the consequences immediately. The intern builds a web-based playground that removes that friction. The backend is a Python FastAPI service that lets users define agents from configurable building blocks: CrewAI supplies the role-based orchestration layer for assembling crews of cooperating agents, while LangChain provides the tools, prompts, and model integrations each agent can use. Through the interface a user can adjust an agent's role, goals, tools, and model parameters, launch a task, and watch the execution unfold in real time, then tweak the configuration and run it again. The intern implements the configuration schema, the execution engine, and the live result streaming that makes the loop feel immediate. Completing the project demonstrates a deep working knowledge of agent architecture, multi-framework integration, API design for long-running tasks, and the craft of building developer tools that make a complex technology approachable.

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