DeepCode is an agentic coding platform built around a multi-agent architecture that turns high-level inputs, including research papers, documents, and natural-language requirements, into working software artifacts. It positions itself as an “open agentic coding” system that can handle tasks like paper-to-code reproduction, frontend generation, and backend implementation by decomposing problems into structured steps and coordinating specialized agents. The system description highlights an orchestration layer that plans, assigns subtasks, and adapts strategies as complexity changes, rather than relying on a single monolithic prompt. It also describes document parsing capabilities aimed at extracting algorithmic and mathematical details from technical materials, translating them into implementable specifications and code.
Features
- Multi-agent orchestration for planning, decomposition, and execution
- Document and paper parsing for extracting implementable technical details
- Research-to-code workflows designed for reproducing algorithms and systems
- Retrieval-augmented coding with dependency-aware reference mining
- Automated prototyping for generating application structure and components
- Integrated quality steps like testing, debugging, and documentation synthesis
Project Samples
