User
Write something
Pinned
🧭 The Real AI Maturity Shift Is Operational: Why the Winning Teams Are Rebuilding the Operating Model, Not Just Adding Tools
A lot of organizations still approach AI like a layer they can add to the side of existing work. They test a few tools, launch a pilot, create some prompt libraries, maybe automate a small process, and hope that productivity improves. Sometimes it does. But the larger pattern is becoming clearer. The biggest gains do not come from simply adding AI into the old system. They come from rethinking how the system itself should work when intelligence is more available, more distributed, and more embedded in the flow of work. That is why the real AI maturity shift is operational. Winning teams are not only collecting new tools. They are rebuilding the operating model so that work moves with less friction, less redundancy, less waiting, and less rework. In time terms, this is one of the most important conversations happening right now because it changes AI from an occasional shortcut into a structural source of reclaimed capacity. ------------- Context ------------- Most organizations begin their AI journey at the task level. They ask where writing can be faster, where summaries can be generated, where research can be assisted, or where a repetitive process can be streamlined. That makes sense as a starting point. Small wins build trust. But over time, a deeper truth emerges. The biggest time leaks are often not isolated tasks. They are the patterns in how work is organized. The number of handoffs. The waiting between stages. The repeated restating of context. The dependence on specific people to manually connect steps that should already be connected by the system. If those structural issues remain in place, AI can still help, but the total value stays limited. The organization moves faster in spots while remaining slow in shape. That creates the illusion of progress without changing the underlying economics of the workflow. This is why operational maturity matters so much. The conversation shifts from ā€œWhere can we use AI?ā€ to ā€œHow should work be redesigned now that AI can carry more of the information movement, first-pass synthesis, and coordination burden?ā€ That is a very different question, and it creates much larger time gains.
🧭 The Real AI Maturity Shift Is Operational: Why the Winning Teams Are Rebuilding the Operating Model, Not Just Adding Tools
Pinned
New ChatGPT Model & Memory Features Explained (AI News You Can Use)
In this video, I break down the big updates from OpenAI including a new default model for all users in ChatGPT called GPT-5.5 Instant plus some important updates to how Memories function. I'll show off some live testing, benchmark results from the AI Advantage research team, and ends the video by covering some smaller stories that I feel should still be on your radar. Enjoy!
Pinned
The Reason I Refused To Quit
Everybody wants success until success starts testing them. Because eventually this journey asks a question most people aren’t prepared for: ā€œHow bad do you really want it?ā€ Not when things are easy. Not when the money starts coming in. Not when everyone is cheering you on. I mean when you’re doubting yourself. When nothing seems to be working. When you’re exhausted. When you feel embarrassed. When you fail publicly. When it would honestly be easier to quit. That’s the moment your WHY matters. For me, it was my mom. Mother’s Day always reminds me of this… I watched my mom work herself to exhaustion trying to provide for us. Multiple jobs. Constant stress. Doing the best she could with what she had. And as a kid, I remember the moments that stuck with me most weren’t the things we didn’t have…It was watching how hard she worked and realizing she still couldn’t buy back time. She missed games. Missed moments. Missed parts of life because survival demanded everything from her. I remember thinking very early on: ā€œOne day I’m going to change this.ā€ Not because I wanted fancy things. Not because I cared about looking successful. I just wanted freedom. Freedom for her. Choices for her. Relief for her. That became the thing I held onto anytime life punched me in the face. And trust me, there were a LOT of moments where quitting would’ve been easier. But when your reason is emotional enough, you find another gear. That’s the part people don’t talk about enough. Success is rarely about intelligence alone. It’s usually about emotional conviction. The people who make it have something that pulls them forward when motivation disappears. So, I’d love to ask you: What’s the reason behind your drive? Who are you fighting for when life gets hard? P.S. Happy Mother’s Day to all the moms out there doing their best, carrying more than anyone sees, and loving through it all. You’re appreciated more than you know. ā¤ļø
Short trailer
I started practicing creating videos using still images, looking for some feedback on this short trailer.
Short trailer
The ChatGPT ā€œpersonalisation settingsā€ mistake most people make
This post is a more advanced follow-up to https://www.skool.com/the-ai-advantage/illusion-of-control?p=7a73faa9, specifically designed for power users. ------------- The ChatGPT ā€œpersonalisation settingsā€ mistake most people make ------------- Most people assume ChatGPT settings are a control panel for privacy, personality, and behaviour. But that assumption breaks the system in their head. Here’s the truth. What looks like a unified ā€œcustomisation menuā€ is actually three completely different layers of control that do not operate with equal power. 1. ā€œData controls = full privacy protectionā€ This is the biggest misconception. Turning off training usage does not mean: - your data becomes invisible - your data stops being processed - your interactions stop being stored for operational purposes - What it actually does is narrow one specific use case: model improvement training. The mistake is thinking this is a global privacy switch when it is actually a scoped data usage preference. 2. ā€œVoice and colour = meaningful personalisationā€ These settings feel important because they are visible. But they only modify interface presentation, not intelligence, behaviour, or memory structure. This creates a false signal:ā€œIf I tweak enough UI settings, I’m shaping the system.ā€ In reality, you are only changing the surface layer of interaction. 3. ā€œParental controls = general safety layerā€ These are compliance tools, not behavioural reshapers. They are designed for account boundaries, not conversational intelligence or output quality. Treating them as part of ā€œpersonal optimisationā€ blends governance tools with UX tools, which are not the same system. ------------- The real model most people miss ------------- ChatGPT ā€œpersonalisationā€ is not a single system. It is three independent layers: - Governance layer: data usage, safety, compliance boundaries - Interface layer: voice, colour, accessibility, UX preferences - Interaction layer: how you prompt, structure, and iterate with the model
1-30 of 18,993
The AI Advantage
skool.com/the-ai-advantage
Founded by Tony Robbins, Dean Graziosi & Igor Pogany - AI Advantage is your go-to hub to simplify AI and confidently unlock real & repeatable results
Leaderboard (30-day)
Powered by