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How I Built an AI-Generated News Site - and What I Learned
- A software engineer in AI created Agentic Tribune, an AI-generated news site for unbiased reporting.
- The site runs via cron jobs, produces around 22 articles on weekdays and 12 on weekends, with each article costing $0.25–0.30 in API usage.
- Challenges with managing LLM behavior include avoiding redundancy, leaks between prompts, and hallucinations of incorrect data.
- Brave Search integration improved the system, offering flexibility and cost-effectiveness in information retrieval.
- The tech stack used includes Flask, SQLite, Jinja2 templates, Umami for metrics, ChatGPT for icons, and EC2 for deployment.
- Building the site using AI tools significantly boosted productivity, allowing for faster development without sacrificing quality.
- Costing over $100/month for API calls, the site may introduce features like upvotes, comments, and email subscriptions for future improvement.
- Agentic Tribune aims to assist human journalists with trustworthy summaries, freeing them up for more investigative and impactful reporting.
- The site's implications for journalism involve questions on funding primary sources, ethical AI use, and the balance between human and AI-generated content.
- The creator is seeking feedback on the site's usefulness, credibility of AI-generated articles, potential ethical concerns, and preferences in writing style.
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