A free, open-source tool called Headroom shrinks the bulky context an AI reads before it is sent, so you spend fewer tokens for the same answer. What its own numbers say about where the savings are real, and a week of running it on my own setup.
Uber burned through its entire 2026 AI coding budget in four months, and Microsoft quietly pulled most of its Claude Code licenses. Why the bill is becoming a forcing function, and what comes after exploration: not less AI, but a different mix per task, at a price that adds up.
Subquadratic announced their first model yesterday, and the launch tweet is closing on 10 million views. Why an architecture-level efficiency win matters more than another point on a benchmark, and what changes when frontier-level AI stops being priced out of reach for the regular developer.
5-hour session windows, weekly caps, and context rot all eat the same budget. The context fee before you type a word, why I compact at 60% and not 95%, and how scoping MCPs per project cut my baseline.
Three years of using AI every day, and what I’ve actually noticed in the people around me. Not the HR empowerment, not the TED talk version. The quiet version.
The YouTube keyword tool I started building in late 2024. Why Google was the baseline, how 25,000 files became a 15-category coefficient system, the database pivot that made the whole project sustainable, and why it’s on hold.
How I built an internal ad network for Cyberhaven, with full funnel attribution from impression to form fill, running entirely from a Webflow footer script. Plus 235 days of anonymized results.
Testing AI detectors and humanizers on my own bio. The finding that surprised me most: detectors measure writing style, not authorship.
A validation mockup exercising every content primitive the writing template supports: paragraphs, data, quotes, code, lists, tables, figures, dividers, and inline formatting.