Most websites fail before a single pixel gets designed. They fail in the brief. "Make it modern. Make it clean. Make it feel like... name any competitor" That's not a brief, it's a mood board pretending to be a strategy.. We just shipped a Framer site for an AI company. And we didn't open Framer for 3 weeks, just locked positioning, who's the buyer, what makes them stop scrolling, what objection hits first and what proof kills it. Then we wrote the site before we designed it, because every section needs a job. Built the whole thing in Framer in 10 days because the strategy was already done and there were no debates around copy, structure or style. just implementitaion. Then 2 more days on the final layer with scroll animations, micro interactions, page transitions. That's what turns a good site into one people actually remember. Fastest way to build a website is to not start with the website.

Love the colors 🎨

Looks like the contra community is liking stuff on machine learning, and I thought it would be interesting to share another article we put together about why machine learning models can underperform for... just no obvious reason.

Despite having clean data and tuned hyperparameters, the accuracy graph barely moves. The trick here is everything related to feature engineering. We wrote a piece titled “Feature engineering decides machine learning outcomes” to share our thoughts on this quasi-"mystic" exercise.

I call it quasi-"mystic" because it is part art and part science. You have to be able to see through the rubble of messy data and know what will really move the needle for you. Much like the jeweller in our cover. It breaks down the essentials, from understanding your data’s structure to choosing well-validated features. Read the full piece here: https://www.algorithmic.co/blogs/feature-engineering-decides-machine-learning-outcomes

Wow, this is sick. the cover as well as the article