In reference to the AI world, we heard about Prompt Engineering, which of course it is important, because you need to know what questions/prompts to ask ChatGPT. This morning I read a post about something new (at least to me, the newbie) Context Engineering. Has anybody some thoughts to share about this? Many thanks!

Hi everyone! I’m currently in the middle of a massive ecosystem shift: I’ve decided to move from my personal ChatGPT account to Google Workspace Gemini (with a business account). I exported my GPT history—a 60MB file of every conversation I’ve had over the last few years—and realized I didn't want to just move the "noise." I wanted to distill it. --> The Vision: From Data Dump to 10 Focused Workbooks in Notebook LM that keep track of the conversations as they were nested under projects in chatGPT. For reference the nature of the 10 projects is: 1. New Ventures: The startups and side-hustles I'm building 2. Personal strategies: e.g. investing 3. Thematic Knowledge: Deep-dive research bases --> The Underlying logic: moving that "clean" history inside 10 dedicated notebooks in NotebookLM, Instead of one giant chat history, would allow me to: - Generate instant mind maps and project refreshers. - Ask questions across only the context of that specific project. - Feed that curated knowledge into Google Gems to create specialized experts on those matters. Has anyone else gone through the process of "de-noising" their GPT history before a migration? I read that one possible approach would be to write and run a script on the .json file, but that goes beyond my technical capabilities, especially because I wouldn't know how to identify the right meta data that nest conversations under one project. Another option would be to download as PDF each conversation nested under the project. Half a day worth of work, so a possible last resort... but quite a defeating one on my path of trying to get smarter and more effective with AI 😅 I’d love to hear how you handled the data sorting and/or if you might have a smarter approach to offer.

I ran into an issue with the certificate. The file was very blurry and essentially unreadable. My name also didn’t appear on the correct line and was pushed onto a second page. Rather than adding another ticket to an already busy support queue, I fixed it myself using Banano. If you’re having trouble getting a clean, professional-looking certificate, Banano is a solid solution. PS—ChatGPT was a little uptight and wouldn’t do it.

Imagine your closest competitor installs AI properly, not just ChatGPT for captions. Where do they beat you first • Faster response to enquiries • Better follow up and higher close rate • Cleaner operations, fewer staff headaches • Better customer experience• Lower costs, higher margins Be honest, which one is the biggest threat for you Reply with one line. This will tell you exactly where to start.

Help.