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AgentForge — Multi-Agent Software Engineering Assistant
Built a locally runnable multi-agent assistant that coordinates specialized agents to analyze tasks, propose software architecture, critique solutions, plan implementation, and synthesize a final response.
PythonOllamaLLMsMulti-Agent SystemsCode Generation
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SYSTEM ARCHITECTURE
Specialized agents collaborate locally with validation, caching, and code-generation workflows.
Problem
Software engineering tasks often require separate stages of analysis, design, review, and planning, which can be difficult to coordinate in a single prompt.
Architecture
User task → Analyst → Architect → Critic → Planner → Consensus → consolidated response, using locally hosted Ollama models.
Challenges
- Defined responsibilities for specialized agents
- Coordinated outputs across sequential stages
- Used a local model runtime to support development workflows
- Structured the final response around review and consensus
Benchmarks
This is a local prototype focused on agent orchestration and workflow design; no quantitative productivity or code-quality improvement is claimed.
Lessons Learned
- Explicit agent responsibilities make multi-step workflows easier to inspect
- Critique and planning stages can expose gaps before implementation
- Local inference introduces practical model-size and hardware constraints