This is a submission for the Agent.ai Challenge: Productivity-Pro Agent (See Details)
What I Built
ResearchByte empowers users to conduct deep, comprehensive research on any topic or company in minutes by instantly scraping and synthesizing data from across the internet into a concise 5-minute video. I built this Agent to eliminate the hours spent manually gathering and digesting information, making it ideal for busy professionals, students, and curious minds who need fast, reliable insights. Envision it as a personal research assistant: users input a topic, and ResearchByte delivers a visually engaging video summary with key facts, trends, and analysis. Whether preparing for a meeting, studying, or exploring new interests, it turns overwhelming research into a streamlined, efficient process—democratizing knowledge with speed and clarity.
Demo
https://agent.ai/agent/research-byte
Here’s a sample video generated by ResearchByte with just the prompt: “Deepseek”
Agent.ai Experience
While the agent builder offers an intuitive interface for basic tasks, I have encountered several challenges when developing more complex workflows. Specifically, AWS Lambda deployments have consistently failed without clear error messages, necessitating deployment to a personal server and invocation via POST requests. Additionally, I have experienced issues with FOR loops within the agent builder, and the debugging tools have not provided sufficient diagnostic information. Furthermore, the handling and formatting of JSON data requires further clarification. I have seen others using GPT-4 to parse JSON outputs, which should be done actually via code, but as there was no option to debug properly I understand that.
Despite these challenges, I recognize the platform’s potential. With further development and resolution of these issues, the agent builder could empower users of all skill levels to rapidly create AI applications. It has the potential to become a central hub for AI agent orchestration, similar to Zapier, enabling agents to trigger external integrations based on their internal logic.
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