Guide to Onboarding Existing AI/ML Projects: From Setup to Data Tracing
kmeanskaran · x · 2026-09-01
Karan shared a guide for developers joining ongoing AI/ML projects:
- Read Documentation: Start with README and project docs.
- Setup Environment: Clean-clone the repo, check dependencies, create a UV virtual environment (prefer WSL on Windows), and configure .env.
- Decompose System: Avoid jumping into the whole codebase; split it into components like data, agent layer, API/MCP, observability, and CI/CD.
- Trace Data: Follow data flow from sources through ingestion and cleaning into feature stores.
- Run Services: Start the API or MCP server to observe online inference and system behavior.
- Deep Dive: Move to the agent core or model logic after understanding the data layer.
- Collaborate: Check cloud permissions, adhere to CI/CD rules, and communicate frequently.
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