This week's the frontier labs have quietly stopped pricing their best work as a luxury.

Anthropic's Claude Opus 5 puts near-frontier intelligence at half the price of its flagship. Launched July 24, it tops the Artificial Analysis Intelligence Index at 61 points, ahead of Fable 5, while costing $5 and $25 per million tokens, half Fable 5's rate. A new effort dial trades cost for capability per request. The model you reach for daily just got a lot cheaper.

OpenAI cut GPT-5.6 prices and had the model optimise itself. This week Luna dropped 80% and Terra 20%, funded by a 15% efficiency gain OpenAI got by tasking GPT-5.6 with improving its own runtime. Passed straight to API, Codex and ChatGPT users. When a lab uses its model to cut its own costs, the savings reach you fast.

Google shipped three Gemini models and still not the one everyone wants. July 21 brought 3.6 Flash, 3.5 Flash-Lite and a cyber-tuned Flash, but Pro is now on its third slip after missing internal quality targets. Flash keeps carrying Google's production load. If you are waiting on Pro to commit, stop waiting and build on what shipped.

Anthropic rewired the plumbing that connects AI to your tools. The new MCP spec, released July 28, moves connectors to standard web infrastructure with hardened login, and the directory now lists over 950 servers used by millions daily. Boring, and the most consequential item here. The tools your AI can reach are becoming standard infrastructure, not custom builds.

Sources: Anthropic · Releasebot · TechCrunch · Anthropic

B2B landing pages have a harder job than B2C. The decision is made by committee. Nobody buys on the page, they request a demo. Your main contact then has to defend the choice to a CFO who never saw your site.

And when these pages underperform, it's rarely the copy. It's three competing calls to action, a nav bar full of exits, and a headline with nothing to do with the ad someone just clicked.

That's a structural problem. So I built something structural to solve it.

A Skill is a set of instructions you give Claude once, that it then follows every time, a repeatable method rather than a prompt you rewrite from scratch. Think of it as encoding an expert's checklist so the AI applies it consistently, instead of improvising.

I took three conversion principles most marketers half-remember; Oli Gardner's attention ratio, CXL's work on message match, Eugene Schwartz's stages of awareness and turned them into rules Claude has to follow, not suggestions it might.

The difference matters. A prompt asking for a "high-converting landing page" gets you a generic one. A Skill that enforces one conversion action, no nav, message match to the traffic source, objections answered on the page gets you a page built to actual principles, the same way every time.

It runs in two phases. It asks a few questions, your product, your goal, where the traffic comes from, then drafts the strategy and hands it back for you to correct. You're editing, not filling in blanks. Then it builds the page in Claude Design.

The rule I'm proudest of: it won't invent your proof. No fabricated stats, no fictional logos, no testimonial from "a happy customer." Where you don't have the evidence, it leaves a marked gap telling you what to go and get. An AI that makes up your customer results isn't saving you time, it's handing you a problem you'll find out about later.

A hands-on AI intensive for marketing leaders who know AI matters, but have a marketing function to run. One-to-one, with your team, or both, we work out the right fit on the discovery call.

Every week there's a new tool, a new model, and another post telling you you're behind. You're a marketing leader, not a prompt engineer, and you don't have weeks to sit and work it all out.

Feeling like you can't keep up is the normal, sane reaction to a space moving this fast. The answer isn't more reading. It's a guide who has already done the work and get you feeling confident about using AI fast.

AI is moving fast and most people are falling behind. 

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