hour

Attention over time

7-day rolling share of analyzed posts/comments mentioning this entity · 90 daily points ending 2026-10-14

Final complete day: 2026-10-14. Attention was 1.1% — this entity appeared in 10 of 883 analyzed posts/comments in the seven days ending that day (11 mentions).

Each point is a seven-day rolling window of complete UTC days; a point is comparable only when at least 100 analyzed posts or comments fall inside it. A day with no analyzed records counts as zero; missing coverage is marked and never shown as zero. The series ends at the latest complete analyzed day — it never extends into the current incomplete day. How attention is measured.

Recent mentions

1. 2026-10-13 19:56 UTCComment

   You can now spin up a VPS by asking Claude (we added spend caps so it can't bankrupt you) Small VPS host here (Vozora, London). Connected our whole API to Claude over MCP. "give me a 2GB ubuntu server" works, costs about 1.1p an hour metered, delete it the same way. The hard part: an agent that can order one server can order a hundred. So the agent has to repeat the exact price it quoted before we accept the order, destructive stuff needs a confirmation, and every key has caps it can't raise itself. New provider, one location, that's the honest state of it. If you've hooked an agent up to anything with a card attached, what broke first?

2. 2026-10-13 18:45 UTCComment

   I’d push back a little on treating “AI velocity” and “deep fundamentals” as two separate skills to test. The thing that connects them is validation: can the person tell when what the AI produced is wrong, and say why. That’s where the fundamentals actually show up now, much more than in writing the code themselves. If I were designing the screen, I’d drop the LeetCode and the take-home and use one short session with AI explicitly allowed. Give the candidate a realistic task, or an AI-generated PR with a subtle flaw in it, and have them work through it out loud. What you’re watching for is whether they plan before they prompt, whether they catch the flaw or accept it, and how they react when you push back on a decision. A copy-paster can’t narrate their reasoning on code they didn’t understand, and it costs one interviewer an hour instead of a pile of take-home reviews. I wouldn’t look for a platform for this. The signal comes from the conversation, not from a tool. Curious if anyone here has seen the review-an-AI-PR format hold up once you’re running it across a lot of candidates.

3. 2026-10-13 05:31 UTCComment

   I’m in a similar position and i am not an expert. The AI agent describes your technology, not a problem someone has today. Nobody want agent, they need for example laptop under €800 that won’t die in a year. The distribution is hard, because the pitch is too broad for anyone to recognise themselves in it. Think of things people research for hours and fear getting wrong, or continue to wonder what to buy. Don’t try to cover everything. Pick one problem. Which category do your users/testers ask about most?

4. 2026-10-11 18:05 UTCComment

   For laptops and tvs I would test the "can I trust these reviews" part first. That is where people lose an hour. If they come back for an honest summery of what real owners complain about. That is a solid signal to build on.

5. 2026-10-11 16:23 UTCComment

   As an equal partner you shouldn't have to ask for financial visibility. Set up read-only access to the business bank account and accounting software today, so nobody has to spend hours reporting numbers that should already be transparent.