Jason Liu Portfolio
Creator of Instructor, a Python library for structured LLM outputs that OpenAI itself cited as inspiration for its structured-output API feature; now works as a developer experience engineer on OpenAI's Codex team while running his site as a hub for writing and consulting.
What makes it work
A breakdown of the choices that make this portfolio stand out.
A library whose impact is independently verifiable
OpenAI publicly crediting Instructor as inspiration for a shipped API feature is an external, checkable validation of the work's real-world impact — far stronger than a self-reported usage claim.
Consulting offerings built directly on top of the open-source work
The open-source library serves as a demonstrated-competence portfolio piece that directly supports his separate paid consulting practice, rather than the two being unrelated.
Willingness to publish both technical and personal reflection
Mixing technical writeups with more personal essays signals a real, specific person behind the work rather than a faceless open-source maintainer account.
What AI Engineers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
If your open-source work influences a larger platform or company, note that connection explicitly and specifically — it's stronger proof than describing your own impact.
Use a well-scoped open-source project as the credibility base for a paid consulting or training offer built directly on top of it.
Don't be afraid to publish some personal, reflective writing alongside technical content — it makes the work read as a real person's practice, not an anonymous feed.
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