Hamel Husain
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12 October
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18 September
From one piece AI Evals: Everything You Need to Know 2 beliefs, in the piece's order there
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korrents.com
People cannot fully specify what they want from an AI system without first observing how it behaves.Their words
Additionally, a LLM cannot read your mind, and research shows that people need to observe the LLM's behavior in order to properly externalize their requirements.
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korrents.com
Evaluation and error analysis will remain necessary practices even if AI models become near-perfect.Their words
Even with perfect models, you still need to verify they're solving the right problem. The need for systematic error analysis, domain-specific testing, and monitoring will still be important.
16 August
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29 June
From one piece “It’s Hard to Eval” Is a Product Smell 3 beliefs, in the piece's order there
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Their words
Before AI, verification often happened incidentally during the process of creating work product. With AI, verification is the bottleneck.
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korrents.com
Designing a product for ease of verification should happen before building evals for it.Their words
More importantly, designing your product for ease of verification should come before building evals.
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korrents.com
An artifact that is hard for its builder to verify is usually also hard for its users to verify.Their words
Artifacts that are hard for you to verify are often hard for users too.
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18 January
From one piece Why I Stopped Using nbdev 2 beliefs · hamel.dev
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korrents.com
Careful step-by-step thinking is a property of the developer, not something a tool or framework can enforceTheir words
Notebooks don't force you to write clean code. AI tools don't force you to think carefully. Discipline comes from the developer, not the environment.
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korrents.com
Good documentation is produced by effort, not by tooling that keeps code and docs togetherTheir words
This reinforced my belief that good documentation comes from effort, not tooling.
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Usesrcmnd.app
AmpTheir words
My daily drivers now include Amp, Cursor, and Claude Code. I still enjoy notebooks, but only for data analysis, machine learning, or other exploratory workflows where the iterative, visual nature of notebooks shines.
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Usesrcmnd.app
CursorTheir words
My daily drivers now include Amp, Cursor, and Claude Code. I still enjoy notebooks, but only for data analysis, machine learning, or other exploratory workflows where the iterative, visual nature of notebooks shines.
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Usesrcmnd.app
Claude CodeTheir words
My daily drivers now include Amp, Cursor, and Claude Code. I still enjoy notebooks, but only for data analysis, machine learning, or other exploratory workflows where the iterative, visual nature of notebooks shines.
+ 2 more
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Mixed ontheir ownrcmnd.app
nbdevTheir words
Because I have invested thousands of hours into nbdev, it's difficult to admit there are better tools for the outcomes I want.
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Likedrcmnd.app
Next.jsTheir words
I now use different languages for different tasks. For web development, I prefer the Next.js stack.
12 November 2025
31 October 2025
1 October 2025
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Mixed onrcmnd.app
LangsmithTheir words
The overall workflow is intuitive, especially for those new to formal evaluation processes. The UI guides you through creating datasets, running experiments, and annotating results.
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Mixed onrcmnd.app
BraintrustTheir words
The panel had a generally positive view of Braintrust, highlighting its clean UI and structured approach to evaluations. The tool’s emphasis on human-in-the-loop workflows was a significant strength.
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Likedrcmnd.app
Arize PhoenixTheir words
The panel had a generally positive view of Phoenix, with one panelist calling it one of his “favorite open source eval tools.” The tool is positioned as a developer-first, notebook-centric platform.
+ 1 more
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Usesrcmnd.app
Jupyter notebooksTheir words
As for me personally, I tend to use these tools as a backend data store and use Jupyter notebooks as well as my own custom built annotation interfaces for most of my needs.
24 March 2025
30 November 2024
29 October 2024
29 July 2024
12 April 2024
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