Hamel Husain and Shreya Shankar, drawing on work with over 50 AI companies, published an advanced follow-up on building eval systems for AI products, arguing that most teams skip the critical step bef…
Hamel Husain and Shreya Shankar published an AI Evals FAQ distilling the most common questions from teaching 700+ engineers and product managers about AI evaluation. The guide distinguishes model benc…
Hamel Husain, a software engineer, published a blog post arguing that developers should inspect the final prompts that LLM abstraction tools like DSPy, guidance, and instructor send to language models…
A developer at nugalaxy advises teams to build their first AI agent eval set from twenty real conversations and agreed-upon answers, arguing that this small, thoughtful set is more valuable than thous…
An engineer who previously created a 29-question exam for an LLM and made five errors in the process tested whether an AI could write a better exam. The AI author (Sonnet 5) generated 50 questions wit…
Hamel Husain, a prominent AI engineer, argues that most AI evaluations fail because teams treat weak outputs as model failures when the real problem is product design, not the model itself. In the sec…
A viral joke by Peter Steinberger, creator of OpenClaw, and Hamel Husain, known for AI evals, sparked debate over whether 'loop engineering' is dead and 'graph engineering' is the new discipline. The …
Machine learning engineer Hamel Husain argues that automated evaluations (evals) for AI systems are flawed and often misleading, based on his 20+ years of experience and work at Airbnb and GitHub. He …
A developer reviewed six 'operator-ready' checklists for AI agents and found that none define the problem correctly. The frameworks, including Anthropic's 'Building Effective Agents' and Hamel Husain'…
Hamel Husain argued at Arize Observe 2026 that AI evaluation is fundamentally a data science problem, urging teams to return to rigorous data analysis and metric design rather than relying on vague 'v…
A Forward Deployed Engineer working on AI adoption reports that TDD cannot guarantee design correctness, especially when AI generates tests. The engineer describes an incident where a function signatu…
BenchFlow released a curated, annotated library of over 443 resources for building and evaluating AI agents, including papers, blog posts, talks, and tools. The list is verified, pruned of dead links,…
A developer found that while AI accelerates generation, it does not reduce the cognitive load of judgment. They now delegate tasks only when a machine-checkable gate exists to verify output, as the hi…