Most people use AI for answers. Fewer use it for leverage. From what I’ve seen, the biggest missed opportunities usually fall into three areas: 1) Planning Using AI to think before acting: clarifying goals, mapping options, stress-testing decisions, and spotting blind spots early. Most people skip this and jump straight to execution. 2) Execution Breaking vague ideas into concrete steps, timelines, checklists, and next actions. AI is incredibly good at turning “I want to do X” into “here’s what to do today.” 3) Communication Explaining ideas more clearly, adapting messages to different audiences, preparing tough conversations, or turning messy thinking into something structured and persuasive. My sense is that many professionals still treat AI like a smarter Google, instead of a thinking partner embedded in their workflow. Curious to hear from you: Where do you think AI is most underutilized right now — planning, execution, communication, or somewhere else entirely?

One of the most interesting questions right now is not whether AI helps us learn faster — but how far that acceleration actually goes. If someone starts close to zero today, AI can: - explain concepts on demand - adapt explanations to your level - generate examples, exercises, and feedback - help you practice more consistently This applies to many domains: - coding - languages - music - professional skills - analytical or creative work In many cases, AI seems to compress the early and middle stages of learning dramatically. But there are also limits: - intuition still takes time - taste and judgment aren’t instant - real-world constraints push back - some skills only solidify through repetition and exposure So the interesting question isn’t “Can AI make you an expert overnight?” It’s something more nuanced. How far can AI realistically take someone — and where does the acceleration slow down? And from your own experience: - Where did AI help you most? - Where did it stop being enough on its own? - What still required time, effort, or human feedback? Curious to hear how people here see the real ceiling of AI-accelerated learning — across different skills and professions.

Quick thought experiment: An eccentric millionaire commissions you to raise $10,000 in 10 days for a worthwhile cause. You don’t choose the cause — you just have to make it work. You’re allowed to use AI as part of the process — for thinking, planning, execution, and iteration — but you are still responsible for decisions and action. This isn’t about fantasy or perfect plans. It’s about how you’d realistically approach the problem. For example, AI could help you: - clarify constraints and priorities - brainstorm feasible fundraising approaches - evaluate what’s realistic under time pressure - shape messaging and outreach - design simple assets (copy, structure, scripts) - anticipate risks and bottlenecks - adjust the plan if something underperforms You don’t need a full strategy document. A rough but thoughtful outline is enough. Challenge: If you had to start today, how would you use AI to go from zero to $10,000 in 10 days? You can share: - the first concrete step you’d take - how AI fits into your process - or what you think would be the hardest part There’s no single right answer — the value is in seeing how different professionals think and execute.

A lot of the conversation around AI at work starts with fear: Will this replace me? Will my role still matter? What I’m seeing in practice is something more nuanced. AI doesn’t replace professionals directly. It amplifies how they already work. When AI is used mainly to: - generate generic output - follow templates without thinking - skip judgment and context the work becomes easier to replace. But when AI is used to: - clarify decisions earlier - explore trade-offs before committing - surface blind spots and assumptions - connect ideas across domains it actually strengthens the parts of the job that matter most. In my own work, AI hasn’t reduced my role. It has made the thinking layer more visible — and more valuable. The professionals who benefit most aren’t the ones chasing every new tool. They’re the ones who use AI to: - ask better questions - narrow scope instead of expanding it - make clearer decisions sooner AI doesn’t decide who’s replaceable. It rewards clarity, judgment, and context. I’m curious to hear your perspective: How do you think professionals can use AI to become harder to replace — not by doing more, but by strengthening what only they can provide?

Imagine you had the time (or permission) to explore one professional project with AI. Not necessarily something you’re launching tomorrow. Just an idea you’d like to build at some point — as: - a side project - a professional tool - an internal solution - or even a future side gig It could be: - a workflow or automation - a small internal product - a client-facing tool - a teaching or documentation system - something that solves a recurring pain in your work No need for a polished plan. Rough ideas are welcome. I’m curious: If AI made it easier to build, what professional product would you want to explore — and why?