User
Write something
Pinned
🎯 The Skill That Doesn't Show Up on the Task List
Most conversations about AI and productivity focus on task speed: how much faster can a draft, a report, a piece of research get done. That's a reasonable place to focus, since task speed is visible and easy to measure. You can time it. You can compare before and after. The gains are concrete. But task speed isn't where the real leverage is anymore, for a specific and important reason. When AI compresses task time across the board, the bottleneck in most workflows moves somewhere task speed can't reach: the speed at which decisions get made about what to do next. Decision speed, not task speed, is quietly becoming the more important variable, and it's not showing up on anyone's task list because it was never a task to begin with. ------------- Context ------------- Think about what a typical AI-assisted workflow actually looks like now. A draft that used to take two hours takes fifteen minutes. Research that used to take an afternoon takes twenty minutes. The execution layer of most knowledge work has compressed dramatically. What hasn't compressed at the same rate is the layer above execution: deciding what to work on, evaluating whether a direction is right, choosing between options, determining when something is good enough to move forward. This layer was always there. Before AI, it was partially hidden inside the execution time. Deciding what a report should argue happened, in part, while writing it. Deciding which research direction to pursue happened, in part, while doing the research. The thinking and the doing were intertwined, and the total time included both. Now that doing has compressed dramatically, the thinking that used to be embedded in it has to happen more explicitly and more separately. And for a lot of people, that thinking hasn't gotten any faster. It's the same deliberative process it always was, but it's now a larger proportion of the total time a piece of work takes, and it's often the part that isn't being tracked or improved at all. ------------- The Bottleneck Moved, and Most People Haven't Noticed -------------
🎯 The Skill That Doesn't Show Up on the Task List
Pinned
What Success Actually Buys You
Most people think success is about money. It's not. Money is just what buys you options. I've worked hard for decades. Not because I fell in love with the grind, but because I fell in love with what the work could create. Every uncomfortable conversation. Every risk. Every time I wanted to quit but didn't. None of it was just to make more. It was to own my time. To be there for the people I love. To create memories instead of regrets. To have the freedom to say yes to what matters and no to what doesn't. Don't chase success because you want to look successful. Chase it because one day you'll realize time is the only thing you can't earn back. Work hard. Do the uncomfortable things. Become the person capable of creating the life you want. Because real success isn't measured by what you own. It's measured by how fully you get to live. Question for you: If you had complete freedom over your time one year from now, what would you spend more of it doing... and who would you spend it with?
🤔 WE WANT YOUR HONEST OPINION!
We want to better understand what people are TRULY trying to accomplish when it comes to AI so we can make our products better. We know it’s broad and there are so many different lanes, but if you had to pick one of the 2 options below, which one would you choose?
Poll
860 members have voted
Two kinds of AI systems you should think about separately.
Two kinds of AI systems you should think about separately. First, the front-end stuff. Dashboards, client portals, tools that your team logs into and clicks around. These are the ones people get excited about because they look impressive. Second, back-end functions. Automated workflows, daily briefs that summarize everything happening in the business, systems that watch your numbers and flag issues before you know about them. Most people start with the front-end because it's visible. But the back-end is where the leverage lives. A daily brief that pulls from every call transcript, every pipeline update, every client health score, that changes how you run the business. You stop reacting. You start deciding based on a complete picture. The right order: build the back-end first. Get the data flowing and the intelligence working. Then build the front-end to make it accessible. What's one piece of internal data you wish you had a daily summary of?
I automated 80% of my LinkedIn outreach and finally stopped hating social media
Contrarian take: most "AI outreach" tools just spam faster. That is why my reply rates were stuck at 2% for months. Here is what actually moved the needle for me — a real number from last quarter: 340 personalized touches per week, ~14% reply rate, and I spent under 45 minutes/day reviewing them. The stack is boring on purpose: - n8n workflow pulls fresh leads from a signal source (job changes, funding rounds, content triggers) - Claude enriches each profile with a hook based on their last 3 posts - A queue drips messages during their timezone working hours - Replies route back into n8n for scoring, then into my inbox only if warm The unlock was not the AI. It was treating outreach like a pipeline with stages, not a to-do list. Every message has a source signal, a hypothesis, and a next step — same discipline you would apply to a sales funnel. Built this because I despise social media but still need pipeline. Turns out automation is the only honest way to be active without doom-scrolling. Full n8n build walkthrough: https://www.youtube.com/watch?v=vtrK85pFE1U Try it yourself at https://inboundy.app/ What is the one outreach step you would automate first if you had 2 hours this weekend?
0
0
1-30 of 19,914
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