
Developed a Podcast Transcript Generation Agent for the google/adk-samples repository, delivering an automated pipeline that converts PDF, Markdown, and text documents into podcast-ready transcripts. The solution leveraged Python, FastAPI, and Google ADK to orchestrate a sequence of specialized sub-agents responsible for topic extraction, episode planning, and transcript writing. By integrating natural language processing and sequential agent design, the agent enabled automated content repurposing and supported customizable personas for conversational scripts. This approach streamlined the process of generating podcast content, reduced manual authoring time, and facilitated easier distribution across platforms, enhancing the scalability and reusability of existing materials.
October 2025: Delivered a new Podcast Transcript Generation ADK Sample Agent in google/adk-samples that orchestrates a multi-step pipeline to generate transcripts from PDF, Markdown, and text documents. The agent delegates topic extraction, episode planning, and transcript writing to specialized sub-agents, enabling automated content repurposing, customizable personas for conversational scripts, and easier cross-platform distribution. This work enhances scalability, reduces manual authoring time, and improves reuse of existing materials across formats.
October 2025: Delivered a new Podcast Transcript Generation ADK Sample Agent in google/adk-samples that orchestrates a multi-step pipeline to generate transcripts from PDF, Markdown, and text documents. The agent delegates topic extraction, episode planning, and transcript writing to specialized sub-agents, enabling automated content repurposing, customizable personas for conversational scripts, and easier cross-platform distribution. This work enhances scalability, reduces manual authoring time, and improves reuse of existing materials across formats.

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