Translating the AI hype Ep 1: LOOPS

@digitalsamaritan

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Loopsloops.so

Loops is email marketing software for SaaS teams to send marketing, lifecycle, and transactional email from one product. Free to start.

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Why it worked

The video breaks down a complex AI concept ('loops') into easily digestible steps with clear visual aids, making it educational and engaging for viewers interested in AI. The creator's direct and slightly provocative tone ('I'm gonna piss off some of you') also helps capture attention.

Summary

This video explains the concept of 'loops' in AI prompting, differentiating them from standard prompts. It illustrates how loops involve an iterative process where the AI revises its output based on a defined check until a satisfactory result is achieved.

Structure

1Introduction to AI loops
2Explaining a normal prompt vs. a loop
3Visualizing the loop process with a diagram

Original caption

Translating the AI hype (episode 1: LOOPS) #learnai #digitalsamaritan

More from @digitalsamaritan

Product placement

The video discusses and visually represents the concept of 'loops' in AI prompting, showing a diagram of how an AI agentic loop works. The product name 'Loops' is mentioned as the subject of the episode.

On-screen text

Translating the AI hype Ep 1: LOOPS EVERYONE WILL START STOP WRITING PROMPTS AND START BUILDING LOOPS WHAT THE HECK IS A LOOP? THIS IS EPISODE 1 OF TRANSLATING THE AI HYPE SO WE CAN GROW TOGETHER. OFF SOME OF BUT A LOOP IS BASICALLY A FEW EXTRA STEPS. A normal prompt YOUR TEXT the prompt CLAUDE reads it once ANSWER whatever comes out STOPS HERE - NO RETURN PATH GET THE ANSWER. RETURN PATH. IF THE RESPONSE, I HEY DUDE, THIS IS GARBAGE. PLEASE DO THIS AGAIN. A LOOP, A WORK FOR US. An agentic loop draft = check = good enough = repeat / stop DRAFT + DATA CLAUDE ATTEMPT a rewrite CHECK 4/10 FINAL Pass 1: The check scores each attempt. If score > threshold OR max_iterations hit (e.g. 3): RETURN final script + the score trace EMAIL THE SAME WAY. HERE WRITES THE IT CHECKS IF THE RESPONSE IS ACTUALLY GOOD NOT, IT GOES AI, IT TRIES AGAIN IS ACTUALLY GOOD AND THEN WE GET THE FINAL ANSWER. Part is to KEEP ON WORKING IN A LOOP UNTIL WE GET THE SATISFACTORY ANSWER Part is to CLEARLY DEFINE WHAT'S OR ELSE IT'S GONNA KEEP GOING CIRCLES AND CIRCLES AND BURN ALL SO IN A TO CHECK AND WHAT IS THE THRESHOLD FOR GOOD ENOUGH LOOKS LIKE. KEEP ON REFINING THE RESULTS WITHOUT US BEING INVOLVED THAT CONDITION.

Transcript

Everyone will start telling you to stop writing prompts and start building loops. What the heck is a loop? This is episode 1 of translating the AI hype so we can grow together. I'm gonna piss off some of you for saying this, but a loop is basically a prompt with a few extra steps. This is a normal prompt and this is an example of a loop. See what I mean? So here's a diagram to really help you understand it. Let's say you prompt an AI to write a better email. To AI, you write a prompt, it writes a response and you get the answer. There is no return path. If you don't like the response, I hey dude, this is garbage. Please do this again. So in a loop, AI does work for us. In the same example, we ask here to rewrite an email the same way. Here writes the response, but then it checks if the response is actually good. If not, it goes back to the AI, it tries again until the result is actually good. And then we get the final answer. So basically it keeps on working in a loop until we get the satisfactory answer. But the tricky part is to clearly define what's good enough or else it's gonna keep going in circles and circles and burn all your credit. So in a loop, you're instructing it clearly define what to check and what is the threshold for good enough looks like. So why can keep on refining the results without us being involved that condition.