ReplayAI , Time travel for AI agents.

Inspiration

As AI agents become more capable, building them is becoming easier—but understanding why they behave the way they do is still incredibly difficult. Traditional debugging tools don't provide visibility into multi-step reasoning, tool calls, or agent collaboration. ReplayAI was inspired by the idea that developers should be able to debug AI systems with the same confidence they debug traditional software. What I'm Building ReplayAI is a developer workspace for building reliable intelligent workflows. It allows developers to replay executions, inspect tool calls, compare different prompt versions, evaluate behavior across test cases, and understand exactly how an agent reached its final output. Instead of treating an AI agent as a black box, ReplayAI makes every execution transparent and reproducible. How I'm Building It ReplayAI is being built using Codex and GPT-5.6 throughout the development process. The application will include: Visual execution timelines Agent execution replay Prompt version comparison Evaluation dashboards Performance and token analytics Trace inspection for tool calls and workflow execution The frontend will be built with Next.js, TypeScript, and Tailwind CSS, while the backend will use the OpenAI Agents SDK and modern web technologies to orchestrate and analyze agent workflows. Challenges One of the biggest challenges is making complex agent executions easy to understand without overwhelming developers with technical details. Another challenge is designing a workflow that is powerful enough for advanced users while remaining intuitive for developers who are new to AI agents. What I Hope to Learn Through this project, I want to better understand how developers build, evaluate, and debug production AI agents. I also want to explore how better observability and evaluation tools can improve the reliability, safety, and developer experience of autonomous systems. ReplayAI's mission is simple: If developers can replay every execution, they can build more reliable AI systems with confidence.