The Hidden AI Cost of JavaScript Frameworks
The agent spent eleven minutes reading a migration guide before it wrote a single line of code. Not your agent — the one a colleague pointed at a SvelteKit...
AI & Data 20 articles
Sarah Chen
Sarah spent years shipping machine-learning systems before she started writing about them, which is why her pieces care less about leaderboard scores and more about what happens after deployment: drift, evaluation, cost, and the boring pipelines that make models useful.
She covers AI, machine learning and data science, and has a soft spot for small models, honest benchmarks and anyone willing to publish a negative result.
More from Sarah
Recommendation-Free Feeds: Curation Over Algorithms
It's 11pm on a Friday. You're tired, you open YouTube, and the homepage greets you with a wall of screaming thumbnails, shocked faces, and the same three...
Why LLM Voice Is Instantly Recognizable — and How to Fix It
Spend ten minutes reading blog posts written since late 2023 and you'll feel it: a creeping sense that everything was written by the same slightly overeager...
Stack Overflow Is Dying: 5 Myths About What Replaces It
Stack Overflow now gets fewer than 1,000 new questions a month — a lower volume than its second month of existence, back in 2008. If you learned to program any...
World Models vs Video Prediction: What I Got Wrong
When Genie 4's demos landed, my first reaction was the same one I've had since Sora: this is a very good video generator, why are we calling it a world model?...
Reasoning Models Are Trained, Not Prompted
Here's an opinion I defended badly at a team lunch last year and have since come to believe even more strongly: if your mental model of a reasoning model is "a...
Specialist CNNs vs Frontier LLMs for Image Classification
A dermatologist recently put 200 biopsy-proven skin lesions in front of two frontier LLMs and a fine-tuned copy of Inception v3, a convolutional network Google...
Full-Duplex Speech Models: 5 Voice AI Myths, Tested
I spent two years building voice assistants on the classic stack: speech-to-text in, language model in the middle, text-to-speech out. Every latency...
DeepSeek's Inference Engine: 5 Myths, Tested
When DeepSeek pushed its production LLM inference engine to GitHub under an Apache 2.0 license, the repo hit thousands of stars in hours. That's not surprising...
Hybrid Reasoning Agents: Latent Thinking, Text Acting
Here's an uncomfortable truth about LLM agents: most of the tokens they produce are expensive filler. A reasoning agent solving a math problem will happily...
AI Code Comprehension Checks vs Tests: When Each Wins
Here's a scenario that's becoming common: your coding agent writes 600 lines across four files, the tests pass, the linter is happy, and you merge it. Two...
Why AI Benchmarks Miss 90% of Real Work
A friend of mine runs operations at a mid-sized logistics company, and last spring her team spent three weeks evaluating whether an LLM could take over their...
Inside an Agentic Coding CLI: Loops, Context, Permissions
The model is the easy part. That's the claim, anyway — and after watching a dozen agentic coding CLIs rise, fork, and stumble over the past couple of years, I...
Machine Translation's Low-Resource Language Problem
There are roughly 7,000 languages spoken on Earth. Google Translate supports about 130 of them. Most commercial MT systems handle fewer than 30 well. If you...
K-Means at Scale: Why It Falls Apart and What's Next
K-means is the algorithm everyone learns in their intro ML course and then uses incorrectly for the rest of their career. It's deceptively simple: pick K...
State Space Models vs Transformers: A Practical Guide
Transformers won't be the only game in town for much longer. I know that sounds like a bold claim — we've all watched the transformer architecture dominate...
How AI Tools Are Quietly Changing the Way Developers Think
I noticed it about six months into using Copilot regularly. I was debugging a Python script and reached for the AI assistant before I'd actually read the error...
LLM Agents Are Just Distributed Systems
The AI community is building multi-agent systems — teams of LLMs that divide work, communicate, and collaborate to solve problems no single model can handle. A...
Beyond Self-Attention: What Comes After Transformers
The transformer architecture has been running AI for eight years now. Every major language model, most image generation systems, and an increasing number of...
Running Large Language Models on Your Own Hardware
Last year I spent $4,200 building a local inference rig that could run a 70B parameter model at reasonable speed. A colleague looked at my setup and asked the...