A multi-agent research system that uses OpenAI's o3-deep-research model to conduct comprehensive research with automatic extraction of key insights. The system uses markdown-based prompts with dynamic placeholder replacement and configurable extraction templates to generate structured research outputs.
Uses OpenAI o3-deep-research with web search and code interpreter tools Processes markdown prompts with full section integration (not just query snippets) Supports dynamic placeholder replacement (e.g., [TaskName] → actual task name) Automatic source extraction and metadata collection Uses gpt-4o for structured data extraction Template-based extraction with auto-template selection JSON output formatting with validation Support for multiple extraction templates
In this study, we systematically explore the phase behavior of Cacio e pepe sauce, focusing on its stability at increasing temperatures for various proportions of cheese, water, and starch. We identify starch concentration as the key factor influencing
I had planned, as the heading of this section, to claim that I had learned to avoid self-deception, but after reading more about it, I decided that I had learned only to guard against self-deception.
Kevin A. Bryan's meta-analysis on seven books regarding economic impact of AI:
All I would like you to keep in mind is that the bold claims are taken seriously by enough people on the AI research and AI policy side that social scientists risk being left out of important conversations
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