Riding the AI wave without losing the day job In this AI era, things move fast—and staying in the game means learning just as quickly. I’ve made it a habit to balance daily responsibilities with steady upskilling: ship what matters today, invest an hour for tomorrow. What’s working for me: • Block small, consistent learning slots (no marathon, just daily reps) • Turn real work into learning (apply a new tool to a live problem) • Share drafts early—feedback beats perfectionism • Keep a “to-learn” backlog and pick one tiny topic per week The goal: stay competitive without burning out—deliver value now while building the skills that will matter next quarter. 💯

AI is shaking the foundations of work and life as we know it. Learning is the skill that will be central to success regardless of how the next few years play out. In the next few episodes, we will break down how we think that learning efforts can be improved to give you better results. Full video link in the comments

🧠 Curiosity: The Skill AI Can't Learn In a world obsessed with speed, slowing down to wonder might just be our most underrated advantage. We often focus on learning faster, but rarely pause to ask why we learn in the first place. In our regular KEMS (Knowledge, Experience & Meals Sharing) sessions — moments where the team trades ideas, experiences, and even personal passions over lunch — we're reminded that learning isn't just professional development. It's part of how we stay curious, grounded, and human. In our latest session, our Analyst Sekar J. shared reflections that stayed with us: 📍 The challenge isn't learning more, but learning with purpose. 📍 Curiosity turns research from a task into a journey of discovery. 📍 When we learn with empathy, insight becomes action. Technology can accelerate how we absorb information, but only curiosity turns it into wisdom. 💬 What's one habit that helps you keep curiosity alive in your daily work? #KiroyanPartners #PublicAffairs #KEMS #CriticalThinking #StrategicCommunication #LearningCulture #CuriosityDriven

🤖 AI evolves daily. Humans have to, too. 💭 Rewired for Growth I used to think mindset was attitude. Turns out, it’s architecture. A fixed mindset builds walls. A growth mindset builds doors. In an AI-driven world, value isn’t in what we know — it’s in how fast we can learn, unlearn, and rewire. 💡 Ready to hit refresh on your thinking? If AI can keep learning… why shouldn’t we?

Let’s be real, if you’re a new grad, the game has changed. Ten years ago, there was room to “learn on the job.” Today, AI is taking the easy stuff, and the space for experimentation is smaller. My advice? Focus on productivity. Learn how to leverage technology to deliver results that rival someone with a decade of experience. Output is what matters now, not just time served. If you can produce at that level, you’re not just surviving, you’re competing.

🍎 Gen Z and the new Education Compact 🍎   A new generation is reshaping how we think about learning and work. Gen Z (and soon, Gen Alpha) are demanding change in how we learn, build careers, and define success. They’re building new 🌱 compacts between learning, identity, and purpose. In this article (link below ⬇️), our Head of Platform and Research Rhys Spence was inspired by Laura McGinnis' blog “Gen Z's Reverse Flynn Effect: is it Brain Rot, AI or Just Microplastics?” - thundering through her personal and Balderton Capital's evolving thesis in this space.   He builds on the blog's central ideas 💡 and layers in some of our own. In short, claiming that this generation may be sketching a blueprint for the next era of learning - one in which: 🔹⁠ ⁠Credentials are increasingly portable 🔹 ⁠Mental health is infrastructural 🔹⁠ ⁠AI is a collaborator, not a threat The change is already happening. And new solutions are being built. If you’re one of the 🔨 builders, we’d love to talk to you. 🖇️ Check out the full blog post(s) here: https://lnkd.in/dH4HPd43

"The Mythical Agent-Month" should be a book. Adding more agents to a project doesn't make you faster. The same old traps we fall into over and over when building teams of humans are presenting themselves with agents. Want to deliver something faster? Throw more people at it! That's still so common that I think "The Mythical Man-Month" should be required reading for everybody in tech, regardless of position. But with AI, things are worse. Even seasoned people like me fall into the trap of believing things will be different with agents. After all, they all have cool parallelism features, such as subagents and using worktrees. But AI was created in our own image and likeness. And we suck at coordinating parallel complex work. Am I using parallel agents? Yes! 100%, all the time. But I'm not using them in the same projects. I work on multiple products in parallel, which is the new wonder of the times! But I don't fall into the mythical agent-month trap anymore :)

I've got to disagree with Daniel Weinmann here... Parallel agents are groundbreaking on the right task: a problem with related subtasks. The cheat code is focus on a problem and coordinating multiple simultaneous attacks. Working on multiple projects in parallel means constant context switching. Instead work on one problem sequentially by fanning out your agents to tackle chunks of the same problem. Yesterday it all clicked. I felt like a god orchestrating my minions while time fades away as we churn out code together. I was polishing Rezzy (the OwnerRez virtual assistant agent) with a punch list of refinements as we prepare for wide release. The perfect target for parallel agents. Related items in the same general area, close but not conflicting. Did I dump the bullet list on an agent and hope I didn't end up with a pile of slop? NO! I worked it item by item: - Spin up a new agent for each task - Spend a minute or two with each agent refining the plan to perfection - Greenlight and pivot to the next while the first cranks away By the time I'd planned everything, the first agent was done. Context was clean for followup refinement. Quick acceptance test, tweaks, code cleanup, commit. Rinse and repeat as agents check in. Crushed the entire punch list in ~2 hours. Let agents handle the multitasking. Stay in deep flow, watching tasks stack up in the "Done" column. Time compresses, productivity explodes.

I almost gave up on ai.Cook three times. Once when I spent crazy amounts of time building a feature I thought was genius. Showed it to friends. Crickets. Deleted the whole thing. Again when every recipe API I tried was either broken, expensive, or just... bad, really bad. Spent days trying to make them work before accepting I needed a different approach. And once more when I realized my "grand vision" was way too complicated. Had to start over. But what really made the difference was to actually start using it. Every day. Making real meals without the usual stress of "what's for dinner?" When you're solving your own problem, not some made-up persona's problem, every decision is clearer. You know instantly what matters and what doesn't. My friends gave brutally honest feedback on early versions (ego took a hit, but they were right). Fixed it. Now they can't wait to use it. Building products is humbling. But when you're creating something that'll genuinely make your own life easier - even just making dinner less annoying - the motivation hits different. Still in development, but getting closer every day 🍳

✨ Learning Is Earning ✨ At Ascension, we believe that true growth begins when we choose to keep learning. Inspired by the insights shared during the Augment.org session with Zack Kass of OpenAI, we’re reminded that AI isn’t here to replace us — it’s here to expand our human potential. This is a moment to stay curious, keep evolving, and lead with a forever-student mindset. Because when we keep learning, we keep earning, not just success, but growth and purpose. 💡