Greg Kamradt Portfolio
Runs the Data Independent YouTube channel and created the widely used "Needle in a Haystack" long-context evaluation test for LLMs; currently president of the ARC Prize Foundation and builds applied AI products through Leverage, including agent access-management tooling.
What makes it work
A breakdown of the choices that make this portfolio stand out.
Created a benchmark that became an industry reference point
The "Needle in a Haystack" test is now cited across the industry when evaluating long-context model performance — designing a widely adopted evaluation method is a durable technical contribution beyond any single product.
A portfolio of small, shipped tools rather than one flagship product
Listing multiple distinct, named tools (InterAuth, agnts.sh, RunReq) shows range and shipping velocity across the agent-tooling space rather than betting everything on one product.
Speaking engagements tied to a specific technical contribution
Presenting at OpenAI DevDay and MIT specifically on agent evaluation methods ties his speaking history to the concrete technical work he's known for, not general AI commentary.
What AI Engineers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
If you design an evaluation method or benchmark, publish and name it clearly — a well-designed benchmark can become a lasting reference point others cite.
Ship several small, named tools rather than waiting for one big flagship product — a portfolio of shipped work demonstrates range.
Seek speaking opportunities tied to your specific technical contribution, not generic AI commentary — it reinforces exactly what you're known for.
More AI Engineer portfolios
Ready to build your portfolio?
Follow the AI Engineer roadmap — skills, projects, and timeline to get hired.