AI Engineer

Harrison Chase Portfolio

Creator of LangChain; his GitHub profile (10,000+ followers, 68 repositories) shows the early, individually-shipped projects — including a Q&A-over-Notion tool and a "chat with your data" app — that preceded and fed into LangChain becoming the most widely adopted LLM application framework.

LangChainRAGOpen SourceAgent Frameworks

What makes it work

A breakdown of the choices that make this portfolio stand out.

1

Small, individually shipped projects visible before the big one

Repos like notion-qa and chat-your-data are complete, scoped applications in their own right — the public history shows the pattern-finding that led to a framework, not just the framework appearing fully formed.

2

Star counts as an honest, third-party signal

Visible star counts on individual repos (2.2k, 972, and more) give a visitor a real, unmanipulated read on which specific ideas resonated, rather than a self-reported claim of impact.

3

GitHub itself as the portfolio, with no separate personal site needed

For an open-source-first engineer, a well-maintained GitHub profile is a complete portfolio on its own — proof that the platform where the work lives can double as where it's showcased.

What AI Engineers can take from this

Specific, actionable tips to apply to your own portfolio — no generic advice.

  • Ship small, complete, narrowly scoped projects publicly before attempting something ambitious — the pattern across those projects is often what the bigger idea comes from.

  • Let star counts and forks speak for themselves as an honest, third-party signal rather than only self-describing your project's impact.

  • If your work is open source, treat your GitHub profile itself as your primary portfolio rather than building a separate site to describe the same repos.

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