YouTube Shorts / Page 3
YouTube Shorts from Skillion AI Labs with quick takes on practical AI, workflow design, and venture building.
Shorts
Arthur Ketchel explains why an AI tool working over years of personal notes needs to know which ones still matter. He wants answers about today drawn from current notes, not from records made ten years ago.
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Pete Cooper explains where vibe coding fits in a Scrum or Agile development cycle and where it stops being enough. He argues that quick demos still need a planning step before they can become a product.
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Pete Cooper lists the problems he keeps seeing in code produced quickly with today's AI tools. He explains why he treats those tools like a junior developer and brings in experienced help before production.
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A speaker explains how an AI agent can pull client information from different apps into one place. The example is a business owner who wants the full context before calling a client, prospect or lead.
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Marcos Lima describes how much of his work now depends on AI and why he expects that dependence to spread. He says that without it he could not keep up with the newsletters and other projects he runs.
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Two speakers look at where AI voice agents and automation can take pressure off service businesses. The examples are a massage therapist who has to stop work to answer the phone and a busy reception desk.
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Pete Cooper explains what vibe coding is good for and which parts of software development it leaves untouched. He sets out why a quick AI-built prototype is still a long way from a production product.
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Marcos Lima explains why he thinks today's cheap AI prices will not last. He points to AI companies spending money they do not have and says customers will end up paying the real bill.
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Pete Cooper explains why he believes voice-driven AI chat is coming to cars and how it could change a drive. He walks through an example trip where the car finds an address, suggests a stop for a gift and re-routes on request.
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Pete Cooper answers a question he gets asked often: are consumer AI chatbots like ChatGPT and Claude going to get more expensive? He argues retail prices will stay roughly where they are, and explains who he thinks will end up paying the real cost instead.
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Alice Bull describes a lead-generation dashboard she built for a UK construction company that pulled six separate data sources into a single ranked view. It is a concrete look at AI-assisted prospecting built on public data rather than a bought list.
AI for Lead Generation: Construction Company Success Story #shorts
Pete Cooper explains Jevons' paradox, the 1865 observation that more efficient steam engines burned more coal rather than less, and applies it to AI. It is a short, clear answer to why falling AI costs are pushing resource use up instead of down.
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