Raza Habib

Who is Raza Habib?

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Raza Habib is the co-founder and CEO of Humanloop, a prompt engineering and evaluation platform for enterprise teams. He is best known for helping build tooling that makes it easier to manage prompts, test LLM behavior, and ship AI features safely. (humanloop.com)

Background and career

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Raza Habib studied Physics at Cambridge and later earned an MSc and PhD in Machine Learning at UCL, according to Humanloop and his public company bio. Humanloop also describes him as a founder with experience across applied AI, including work at Google AI and Monolith AI. (humanloop.com)

That background helps explain Humanloop’s focus on practical LLM workflows. Rather than treating prompt writing as a one-off task, Habib’s work centers on iteration, measurement, and deployment, which is the same set of problems enterprise AI teams face when they move from prototypes to production. (humanloop.com)

Key facts about Raza Habib include:

1. Current role: Co-founder and CEO of Humanloop.
2. Academic background: Physics at Cambridge, then machine learning research at UCL.
3. Technical focus: Prompt engineering, evaluation, and enterprise LLM workflows.
4. Public presence: Appears on Humanloop podcast and related AI discussions.
5. Industry context: Works at the intersection of product, ML, and developer tooling.

Notable contributions

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1. Humanloop: Co-founded the company to help teams build, test, and operate LLM applications with more control and repeatability. (humanloop.com)
2. Enterprise prompt workflows: Helped popularize the idea that prompts should be versioned, reviewed, and evaluated like other production artifacts. (humanloop.com)
3. Applied ML background: Brought research and engineering experience into a product aimed at real-world AI deployment. (humanloop.com)
4. AI education and commentary: Shared practical guidance on LLM development through Humanloop’s podcast and public interviews. (humanloop.com)
5. Enterprise AI tooling: Contributed to making evaluation and monitoring first-class concerns for teams shipping LLM features. (humanloop.com)

Why they matter in AI today

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1. Operational thinking: His work reflects how modern AI teams need process, not just model access.
2. Evaluation-first mindset: He represents the shift from demo-driven AI to measurable production systems.
3. Prompt quality: He has helped frame prompts as assets that can be reviewed and improved over time.
4. Enterprise fit: His focus matches the needs of teams that must balance speed, reliability, and governance.
5. Builder relevance: Founders and ML teams can learn from his emphasis on iteration, feedback, and traceability.

Where to follow their work

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The most direct place to follow Raza Habib’s work is Humanloop itself, especially the company’s about page and podcast content. Humanloop also lists his role publicly and shares episodes where he discusses LLM building patterns and enterprise adoption. (humanloop.com)

His public X account is referenced on the Humanloop podcast page as RazRazcle, which gives another way to see his commentary on AI tooling and product thinking. (humanloop.com)

How PromptLayer connects with Raza Habib's work

Raza Habib’s work at Humanloop centers on the same core problems PromptLayer helps teams solve, prompt iteration, evaluation, and operational visibility for LLM apps. For teams building production AI, PromptLayer offers a practical way to manage prompt versions, compare outputs, and keep engineering workflows moving.

Ready to try it yourself? Sign up for PromptLayer and start managing your prompts in minutes.