Julia Pollard

Julia Pollard

Copywriters

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Write sharper landing pages, ads, and product copy with more focus. Built for better words and faster output.

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Explain is live on PH today! 🚀

Since our last update we have doubled the number of explainers made to 20k and we hope today's PH launch can bring an even bigger group of users testing Explain. We also have a Chrome Extension and plugins with ChatGPT and Claude to make it even easier to create Explainers anywhere.

Check out the launch and join the conversation here

Your product is about to become a tool an agent picks up. Decide now whether it should be.

MCP just locked its biggest revision ever, and it quietly changes the unit of distribution from "a user opens your app" to "an agent calls your tool." That's a strategy decision, not an integration ticket.

A couple of weeks ago the Model Context Protocol shipped its final 2026-07-28 spec the largest revision since it launched. Most of the coverage was about the plumbing: it's stateless now, it runs on ordinary HTTP, the session handshake is gone. Real changes, and if you operate a server they matter. But that's not the part I'd flag for makers. The part I'd flag is what MCP has quietly become while everyone argued about transports: the way software gets used by agents instead of by people. There are close to ten thousand servers in the official registry now, MCP lives under the Linux Foundation with AWS, Google, Microsoft and Salesforce behind it, and this same release added MCP Apps servers can now render their own interactive UI right inside the agent. The protocol stopped being a developer curiosity. It became a distribution surface.

19d ago

How do you handle AI tools that make a judgment call vs. ones that just generate text?

Generation tools are low-stakes when they're wrong draft an email, get a bad draft, edit it. Judgment tools are different: grading, flagging, scoring. If the output looks confident and it's actually a guess, someone might act on it without knowing that.

Working on letsflw's exam-checker made this concrete objective questions are easy (exact match, no ambiguity), but for open-ended answers we made a call to surface the AI's mark as a suggestion to review, not a final score, because presenting it as settled felt dishonest.

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