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🪞AI Reveals Where Our Work Was Never Clear to Begin With
One of the most uncomfortable things about working with AI is that it does not just expose what the tool can or cannot do. It often exposes what we were never clear about ourselves. The friction we experience is not always a sign that AI is failing. Sometimes it is a sign that our instructions, decisions, and workflows were already costing us time long before AI entered the picture. That is why this matters so much for teams trying to save time. AI does not only accelerate work. It also acts like a mirror. And what it reflects back to us is often the hidden source of delay, vague thinking, unclear expectations, inconsistent handoffs, and avoidable rework that were already shaping our cycle times. ------------- The Tool Did Not Create the Confusion ------------- A common reaction to disappointing AI output is to blame the tool immediately. The answer was too generic. The draft missed the point. The summary left out something important. The recommendations felt disconnected from the real need. Sometimes that criticism is fair. But other times the real issue is more revealing. The output is weak because the input was never clear enough to produce strong work in the first place. This is not just an AI problem. It is a work design problem. Many teams operate with instructions that are functional enough for humans to patch together socially, but not clear enough to stand on their own. A manager says, “Put together something polished for leadership.” A teammate asks for “a quick update” without defining what matters. A project brief contains goals, but no decision criteria. A task gets assigned with urgency, but without enough context to reduce ambiguity. Humans often compensate for this through intuition, back-and-forth, and experience. AI cannot compensate in the same way. It reflects the ambiguity more directly. That is why AI can feel frustrating at first. It removes the illusion that the request was clear. It shows us, very plainly, how much of our normal workflow depends on people filling in blanks that were never explicitly addressed. When that happens, the tool is not introducing confusion. It is surfacing confusion that was already there.
🪞AI Reveals Where Our Work Was Never Clear to Begin With
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Audit Your Life ...
Going into the weekend, this might be a good time to slow down for a minute and really take a look at your life. Not in a judgment way. Not in a beat-yourself-up way. Just honest. Ask yourself… What in my life is actually helping me get where I want to go? And what in my life is pulling me off track? What habits should stay? What habits need to go? What relationships make me stronger? Which ones drain my energy? What am I giving my time to every day…and does it match the future I keep saying I want? Most people don’t get stuck because they aren’t capable. They get stuck because they never stop long enough to audit what they’re allowing into their life. This weekend might be a good time to do that. Not to be perfect. Just to get clear. Because when you get clear about what needs to go…it gets a lot easier to protect what matters. Stay on offense.
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OpenAI's Huge New Releases & More AI News You Can Use
This week, I cover the new model releases from OpenAI including GPT-5.3 and 5.4, plus I show off the new Project Sources update for ChatGPT. I also break down the many releases from Google as they condense their AI tools down into the products that work, talks briefly about OpenClaw competitors and Anthropic's latest releases, and more. Enjoy!
Excited to be here
In my 50s and have a lot to learn but I believe this group will be a great source for my education.
Update on disastrous ChatGPT business work migration. Cautionary tale for ChatGPT users
It’s been a while since I’ve posted here. Aside from the holidays, I have spent the last 30 days in full business recovery mode following a disastrous workspace migration in ChatGPT on November 30th. I didn’t want to come back until I had something positive to report. Over the summer, before joining the AI Advantage I launched my startup using a ChatGPT Plus account tied to my personal email. As a (now) professional founder, I eventually realized it was necessary to separate my personal data from my business for IP protection, liability, and future HIPAA compliance with the app I’m building. When I started my ChatGPT account I hadn’t even thought about starting a company yet. Everything was mixed up. All my personal topics and my business building topics were in one account. Which is not a good thing. I knew enough to upgrade to a ChatGPT plus account when I started iterating business ideas, because I did not want them being trained on any of open AI models. I did everything by the book. I followed the documentation and even used ChatGPT to build a migration checklist. What happened next took my business out at the knees. ChatGPT wiped out every last bit of my data. Their support was nonexistent—no apology, no refund, and no path to recovery. $632.00 spent for a two year Business Workspace and nothing to show for it, everything gone. While my "founder discipline" meant I had backed up my core IP and design docs locally, I lost months of context and chat logs that served as the backbone of my cognitive scaffolding system. It was a disaster of epic proportions. I’ll admit it: I cried. Sobbed actually. I’m normally not a crier, but I had worked so damn hard for several months building something that I know is going to help people. I refused to let it be the end. I have spent December reconstituting my operations from the ground up, but I didn't go back to what broke. After learning that this has happened to dozens, if not hundreds of other founders and businesses, I migrated my entire company to Google Business Workspace (Enterprise Standard) and Gemini. The difference in professional stability and support has been night and day. Because of this move, I’ve recovered enough momentum to stay on track for our first product launch this January.
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