Every day, a new AI money playbook and a real growth trick from a real company. Tools, tactics, and steps you can act on today.
Global AI market size — Grand View Research
Have adopted AI in at least one function — McKinsey
Annual value AI could add — McKinsey Global Institute
One real distribution or SEO trick per day. Stolen from products that grew without a marketing team.
Cognition had two kinds of numbers to lead SWE-2's launch with: accuracy percentages against public benchmarks, or efficiency numbers against its own predecessor. The efficiency numbers went largely uncontested in a 131-comment HN thread; the accuracy numbers got called 'benchmaxxing.'
Instead of writing a blog post complaining that coding agents over-engineer simple tasks, one builder made a page where you watch it happen live. The interactive version hit 921 points and 372 comments on Hacker News.
A post with no product to sell, no thesis to defend, and a real unanswered question — 'am I allowed to publish this?' — pulled 294 points and 160 comments because it gave a technical audience a genuine problem to solve, backed by exact, checkable detail.
Every day, one trending AI idea turned into a step-by-step money-making guide.
Cognition post-trained SWE-2 from Kimi K3, a 2.8-trillion-parameter base model, and led its launch with two kinds of numbers: accuracy against public benchmarks, and operational efficiency against its own predecessor SWE-1.7 — "58% fewer turns and costing 81% less on average," reaching its first real edit in "a median of 18 steps, compared with 48 for SWE-1.7." On Terminal-Bench 2.1 it scored 92.8% versus 81.5% for SWE-1.7. On the newer, harder Terminal-Bench 4 it scored 27.3% versus 7.6% for SWE-1.7 — a 65-point drop within the same benchmark family, and a number an HN commenter set directly against DeepSeek V4.1 Flash's 31.2% and Sol's 37.3% on that same suite. Every team about to standardize on a coding agent is choosing between vendor tables built to spotlight the number where that vendor wins.
opusfived.dev gives visitors one instruction — "Make the 'Add to Cart' button blue. Do not let Claude change anything else." — and turns the site's own description, "a short interactive comedy about agentic AI assistants that can never just do the thing," into the punchline. The HN thread it spawned pulled 921 points and 372 comments, and the top comments aren't jokes — they're specific, repeatable descriptions of coding agents over-scoping simple requests. That specificity is a service brief, not just a meme.
A hobbyist handed the AI model Fable a single purchased MP3 — no source code, no documentation, no reverse-engineering toolkit — and asked it to figure out how it worked. Fable decoded the proprietary MIDI channel, then wrote both an encoder and a decoder for the format, including a working reproduction of the vendor's deliberate obfuscation. If a curious end user can do that in an evening with a general-purpose model, any company relying on a proprietary format or 'security through obscurity' as a protection layer needs to know how long theirs actually survives.
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