I had shown how to create these pictures with 2 different prompts, but someone asked me to merge the 2, so here is how you can do it in less than 2 minutes with NanoBanana. 🤗

When people imagine the future of work, they often picture automation taking over tasks, new job titles emerging, and skills lists changing faster than job descriptions can keep up. But beneath all the technical shifts lies something more personal. The real transformation is not in what we do, but in how we define contribution, creativity, and value itself. The arrival of AI has made work more fluid, more interconnected, and more unpredictable. Many of us are being asked to move from doing work to designing how work happens. That transition can feel both liberating and destabilizing. It challenges our sense of expertise, purpose, and control. What is unfolding is not the end of human work, but the beginning of a new kind of craftsmanship — one built around intelligence as a shared partner rather than a private possession. ---- The Shape of Work is Changing ---- Work used to be defined by repetition and reliability. We learned a skill, refined it, and executed it consistently. Mastery meant stability. Now, mastery looks more like adaptability. The ability to learn quickly, connect ideas, and translate context has become as valuable as technical precision. AI has changed the texture of time and attention. Many of the hours once spent gathering, formatting, or synthesizing information are being reallocated to judgment and decision-making. That shift sounds simple, but it introduces a new kind of strain. It forces us to rethink what a productive day even looks like. Imagine a professional who once spent hours creating detailed reports. With AI summarization and drafting tools, those same outputs now take minutes. At first, that feels like freedom. Then a new question emerges: what do I do with the time I have reclaimed? The answer is not always obvious. This is the new challenge of the future of work. Efficiency is no longer the destination. It is the starting point for deeper human contribution. ---- Redefining Human Contribution ---- In an AI-augmented environment, our contribution becomes less about production and more about perspective. The tasks that remain uniquely human involve context, interpretation, empathy, and choice. These are not easily measured, yet they are the essence of judgment and leadership.

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.

DOES ANYONE USE COPILOT