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Like a Ragged Prayer

Artificial intelligence

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Like a Ragged Prayer

Like a Ragged Prayer

Some interesting stuff from Alexandra Alter on how AI is disrupting the romance novel industry.

Typing Code and Punching Cards

Typing Code and Punching Cards

If typing code for money goes the way of punch cards, how do we ensure that code is correct?

The Jevons Paradox and the Kindle Web Proxy

The Jevons Paradox and the Kindle Web Proxy

When solving problems becomes almost free, more problems get solved. I built a silly little app last night that nobody else would ever build, and that's sort of the point.


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The Decade of Agents: Swyx's AI Engineer Paris Keynote

The Decade of Agents: Swyx's AI Engineer Paris Keynote

Swyx argues for 2025-2035 as the decade of AI agents, backed by unprecedented infrastructure investment and converging technical definitions.

LLM Evals Course Lesson 4: Multi-turn and Collaborative Evaluation

LLM Evals Course Lesson 4: Multi-turn and Collaborative Evaluation

Notes from lesson 4 of Hamel and Shreya's LLM evaluation course - handling multi-turn conversations and building evaluation criteria through collaboration.

Building Domain-Specific Annotation Tools with FastHTML: Lessons from Isaac Flath

Building Domain-Specific Annotation Tools with FastHTML: Lessons from Isaac Flath

How Isaac Flath built a medical flashcard annotation tool for AnkiHub using FastHTML, and why custom annotation tools beat generic ones for complex domains.

Where to Host Your FastHTML Apps

Where to Host Your FastHTML Apps

Deployment options for FastHTML applications.

Connecting Chrome DevTools to FastHTML Apps for Rapid Style Iteration

Connecting Chrome DevTools to FastHTML Apps for Rapid Style Iteration

How to connect Chrome DevTools to your FastHTML applications for fast CSS and HTML debugging and iteration during development.

LLM Evals Course Lesson 3: Building Automated Evaluators

LLM Evals Course Lesson 3: Building Automated Evaluators

Notes from lesson 3 of Hamel and Shreya's LLM evaluation course - implementing automated evaluators, building reliable LLM-as-judge systems, and avoiding common pitfalls.