Alpha Brief – AI‑powered daily economic podcast, ready every morning at 7 AM ET. Four specialized AI agents (Researcher, Analyst, Writer, Title Generator) work together via CrewAI to autonomously gather yesterday’s top economic news and turn it into a concise audio briefing with a push notification. Built end‑to‑end by an indie developer, using SwiftUI and Python FastAPI.
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Maker
📌
Hey Product Hunt! 👋
I'm Mehmet, an indie iOS & AI engineer from Turkey. Today I'm launching Alpha Brief, an AI-powered daily economic podcast that's ready every morning by 7 AM ET.
The backstory:
I'm passionate about both AI and finance, but I found it overwhelming to keep up with economic news every morning. So I built a fully autonomous system that does it for me—and delivers it as a podcast.
Why it's special:
Every single day, without any human touch, the system wakes up, gathers news, writes a script, generates audio, and sends a push notification.
I built this as a solo developer to explore the limits of agentic AI automation, and I'd love to hear what you think. Happy to answer any technical or product questions!
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How are you handling the accuracy of the economic summaries when AI agents pull from sources that might conflict or have biases?
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Maker
@azat3yws Great question, and honestly, this was one of the biggest challenges I focused on while building the architecture. To prevent AI hallucinations and bias, we don't just let the AI scrape the web freely. Instead, we use a strict two-step cross-referencing system:
Curated Raw Data: We pull the initial raw financial news and market movements from premium, institutional-grade financial APIs.
Data Validation: Before the AI processes anything, we cross-reference and validate the hard data (stock prices, percentages, market caps) directly with Yahoo Finance.
Finally, the AI agents operate under strict system prompts instructing them to strip away any editorial opinions and only aggregate the overlapping, verified facts. It's built to be an objective reporter, not an analyst.
Thanks for checking it out, let me know if you have any other questions.
Report
the four-agent pipeline is genuinely clever, especially letting the title generator wrap things up last so the show feels cohesive rather than stitched together
Report
Maker
@dndjnxz Thank you so much for noticing that. You hit the nail right on the head.
In the early testing phases, I realized that if the title/intro was generated too early, the transitions between different news segments felt robotic and disconnected. By letting the fourth agent 'read' the entirely compiled script at the very end, it can actually find the underlying narrative of the day (e.g., realizing both tech stocks and crypto are reacting to the same macro event) and tie the whole 2-minute episode together like a real human host.
Really appreciate you diving deep into the architecture.
How are you handling the accuracy of the economic summaries when AI agents pull from sources that might conflict or have biases?
@azat3yws Great question, and honestly, this was one of the biggest challenges I focused on while building the architecture.
To prevent AI hallucinations and bias, we don't just let the AI scrape the web freely. Instead, we use a strict two-step cross-referencing system:
Curated Raw Data: We pull the initial raw financial news and market movements from premium, institutional-grade financial APIs.
Data Validation: Before the AI processes anything, we cross-reference and validate the hard data (stock prices, percentages, market caps) directly with Yahoo Finance.
Finally, the AI agents operate under strict system prompts instructing them to strip away any editorial opinions and only aggregate the overlapping, verified facts. It's built to be an objective reporter, not an analyst.
Thanks for checking it out, let me know if you have any other questions.
the four-agent pipeline is genuinely clever, especially letting the title generator wrap things up last so the show feels cohesive rather than stitched together
@dndjnxz Thank you so much for noticing that. You hit the nail right on the head.
In the early testing phases, I realized that if the title/intro was generated too early, the transitions between different news segments felt robotic and disconnected. By letting the fourth agent 'read' the entirely compiled script at the very end, it can actually find the underlying narrative of the day (e.g., realizing both tech stocks and crypto are reacting to the same macro event) and tie the whole 2-minute episode together like a real human host.
Really appreciate you diving deep into the architecture.