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title: How I Built a Blog-to-Podcast AI Agent | daily.dev
description: A developer built a blog-to-podcast AI agent that takes a blog URL and returns an MP3 file. The pipeline uses Firecrawl to extract article content, Gemini 2.5...
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og:title: How I Built a Blog-to-Podcast AI Agent | daily.dev
og:description: A developer built a blog-to-podcast AI agent that takes a blog URL and returns an MP3 file. The pipeline uses Firecrawl to extract article content, Gemini 2.5...
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# How I Built a Blog-to-Podcast AI Agent

**[Medium](https://daily.dev/sources/medium_js)** · [@aniketsdev](https://daily.dev/aniketsdev) · 6 min read · 2 upvotes · 0 comments

## Summary

A developer built a blog-to-podcast AI agent that takes a blog URL and returns an MP3 file. The pipeline uses Firecrawl to extract article content, Gemini 2.5 Flash to rewrite it as a conversational podcast script, and ElevenLabs for speech synthesis. Agno orchestrates the entire workflow. The post explains the architectural decisions, including why an agent-based approach was chosen over simple sequential API calls, and the importance of writing for ears rather than eyes when generating the script. Current limitations include single-speaker output and blog-only support, with future ideas like PDF ingestion, multilingual narration, and multi-host conversations.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/data-science-collective/how-i-built-a-blog-to-podcast-ai-agent-9a7232346bbb>

## Questions this post answers

### How can I build a pipeline that converts a blog article into a podcast using AI tools?

Combine four tools into one agentic workflow: Firecrawl extracts the blog content, Gemini 2.5 Flash rewrites it into a conversational podcast script, ElevenLabs converts that script into natural speech, and Agno orchestrates the whole process behind a single objective. A Streamlit interface lets users paste a URL and receive a playable or downloadable MP3.

_daily.dev surfaces practical writeups like this for developers piecing together agentic AI pipelines._

### Why use an agent framework instead of just calling scraping, summarization, and text-to-speech APIs in sequence?

An agent framework like Agno lets the application focus on a single goal, such as 'turn this blog into a podcast', instead of manually coordinating each API call. The agent decides how to use available tools like Firecrawl and Gemini to extract content and generate a script, making it easier to add new capabilities without restructuring the whole pipeline.

_developers weighing agent orchestration versus manual API chaining can find similar tradeoffs discussed on daily.dev._

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- [How to Build and Deploy a Blog-to-Audio Service Using OpenAI](https://daily.dev/posts/how-to-build-and-deploy-a-blog-to-audio-service-using-openai-nbhhr0rwh) · freeCodeCamp · 2 upvotes · 0 comments
- [AI Assistant for Our Blog Writing Process](https://daily.dev/posts/ai-assistant-for-our-blog-writing-process-uduobqhmo) · RUBYLAND · 1 upvotes · 0 comments
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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#google-gemini](https://daily.dev/tags/google-gemini), [#text-to-speech](https://daily.dev/tags/text-to-speech), [#elevenlabs](https://daily.dev/tags/elevenlabs)

[View this post on daily.dev](https://daily.dev/posts/how-i-built-a-blog-to-podcast-ai-agent-6hfveoxdq)

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