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1h •
🔍 AI Is Exposing How Much Work We Never Defined
AI is often described as disruptive because it is new. In reality, it feels disruptive because it refuses to operate inside ambiguity we have quietly relied on for years. When AI struggles, it is rarely because the task is too complex. It is because the work was never clearly defined in the first place. ------------- Context ------------- Most organizations run on a mix of formal processes and informal understanding. Some work is documented, standardized, and repeatable. Much more work lives in habits, conversations, and “the way we usually do things.” Humans are remarkably good at navigating this ambiguity. We fill in gaps without noticing. We infer intent. We compensate for missing steps. We rely on experience and social cues to keep things moving. AI does none of that naturally. It needs clarity. Inputs, rules, definitions, boundaries. When those are missing, AI does not quietly adapt. It fails visibly. That failure is uncomfortable, but it is also diagnostic. AI is showing us where work has always depended on tribal knowledge rather than shared understanding. ------------- The Hidden Dependence on Tacit Knowledge ------------- Tacit knowledge is what people know but rarely write down. It includes how to prioritize when everything is urgent. Which requests can wait. Who really needs to be looped in. What “good enough” means in different contexts. These judgments are learned over time, often through mistakes. Because tacit knowledge works, it feels efficient. Writing it down feels unnecessary. Until someone new joins. Or until work scales. Or until we ask AI to help. When AI enters the picture, tacit knowledge becomes a bottleneck. The system asks questions humans never had to articulate. What counts as complete? Which exception matters? When do we escalate? AI exposes how much of our work relies on shared assumptions rather than shared definitions. ------------- Why Informality Has Been Carrying More Weight Than We Admit ------------- Informal work has always absorbed complexity.
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2d •
The Habit That Quietly Kills Momentum in Business
Most entrepreneurs aren’t stuck because they’re lazy or incapable. They’re stuck because they’re waiting. Quietly. Waiting for more clarity, better timing, more confidence, or for things to settle down. As long as you’re waiting, your potential and your business stays parked. Progress in business doesn’t come from more preparation. It comes from decisions. Every time you explain why you’re not moving yet, you hand control to something outside yourself: the market, the economy, your schedule, your past results. None of those are coming to build the business for you. The people who actually break through don’t feel ready. They move while uncertain. They don’t wait for perfect conditions... they adapt to the conditions they’re in. They don’t wait for permission, because no one is handing it out. Most people keep their effort conditional. “I’ll go all in when things calm down.” “I’ll commit once I feel more confident.” “I’ll start after this next thing.” And months (sometimes years) pass. Not because the idea wasn’t good, but because the conditions were never removed. So here’s something actionable for the week ahead: Pick one decision you’ve been delaying because you wanted more clarity. Make it by the end of the week...imperfectly. Then take the first uncomfortable action that follows from that decision. No optimizing. No overthinking. Just movement. Clarity shows up after action, not before it. Drop in the comments: What’s the one decision you’re done waiting on this week?
Pinned
3d •
Claude is Officially Better Than ChatGPT & More AI News You Can Use
In this video, I break down the week's happenings in AI including Clawdbot (Moltbot), a ton of new upgrades to the Claude ecosystem, new techniques and workflows people are using to create short films with AI, and more. Enjoy!
4d •
🧠 The Confidence Gap: Why AI Adoption Fails After the Demo
Most AI initiatives do not fail because the technology disappoints. They fail because confidence never catches up to capability. The demo impresses, the pilot proves feasibility, and then daily usage quietly stalls. ------------- Context ------------- Across teams and organizations, we see the same pattern repeat. An AI tool is introduced with enthusiasm, leadership signals support, and early results look promising. The technology works. The use cases make sense. The potential feels obvious. Then something subtle happens. Usage plateaus. Only a small group keeps experimenting. Others revert to old habits, not because they doubt the value of AI, but because using it feels socially risky. The tool exists, but it never becomes normal. This is where many organizations misdiagnose the problem. They assume the answer is more training, better prompts, or a stronger mandate. But the issue is not knowledge. It is confidence. Specifically, confidence in how AI fits into real work, real judgment, and real accountability. AI adoption is not blocked by fear of technology. It is blocked by fear of exposure. ------------- Confidence Is Not the Same as Competence ------------- A person can fully understand what an AI tool does and still hesitate to use it. This distinction matters more than most teams realize. Competence is cognitive. Confidence is social. Competence answers, “Can I do this?” Confidence answers, “What happens if I do?” When someone uses AI in their work, they reveal drafts, thinking processes, assumptions, and uncertainty. They expose how they arrived at an answer, not just the answer itself. That exposure feels risky in environments where polish is rewarded more than learning. This is why training alone rarely drives adoption. People may know how to use the tool, but they are unsure how its use will be judged. Will AI-assisted work be seen as smart or lazy? Will mistakes be forgiven or scrutinized? Will experimentation be rewarded or remembered? Until those questions are resolved through lived experience, competence will not turn into confidence.
24h •
Intro
Hey, I'm Shel. After 35+ years running businesses, I now help women simplify the back end of theirs, feel confident with their numbers, and build businesses that support their life, not drain it. I'm a techie nerd who's owned computers since the 1980's (yeah, some gray hair on this head)
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