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In this session, we mix math, agents, real-world dev practice, and careers into one focused hour. We start with the Challenge of the Week: Prove that n² − n is always even. There are 7 different proofs of this simple-looking statement, and we’ll use them to talk about mathematical habits of mind: pattern spotting, generalizing, using structure, and checking edge cases. Then we move into AI news and a fun but serious topic: AI agents go shopping—how agents can browse, compare, and “decide” on purchases, and what that means for real-world workflows and products. Next, we go behind the scenes with a personal dev story: How I used Antigravity to develop 12 functionalities while working only half an hour a night. You’ll see how small, consistent chunks of work plus the right AI tools can lead to surprisingly big progress. Finally, we shift into careers and talk about how to get a job—especially in and around AI. We’ll discuss practical steps, portfolio ideas, and how to present your projects (including math challenges and side projects) as real value to employers. What We’ll Cover 🧩 Challenge of the Week: Prove n² − n Is Always Even Why n² − n is divisible by 2 for every integer n. Up to 7 different proofs, including: Factoring (n(n − 1)) Parity argument (n is even or odd) Visual / geometric reasoning Modular arithmetic How exploring multiple proofs builds good mathematical habits: curiosity, rigor, and flexibility in thinking. 📰 AI News A quick roundup of the most interesting AI updates from the week. How these trends connect to agents, automation, and everyday workflows. 🛒 AI Agents Go Shopping What it means for an AI agent to “go shopping”: browsing, comparing, and ranking options. Possible use cases: procurement, personal assistants, price comparison, recommendation flows. Risks and guardrails: bias, hallucinated products, and over-trusting agent decisions. 🧪 How I Used Antigravity to Build 12 Features in Half an Hour a Night The idea: tiny daily time blocks + a powerful coding assistant (Antigravity). How to break a project into small, shippable functionalities. What worked well, what didn’t, and how to avoid getting stuck. How you can adopt the same pattern in your own evening or side projects. 💼 Let’s Talk About How to Get a Job (Especially in AI) Why projects + proof of work matter more than buzzwords. How to turn: Math challenges Agent demos Small Antigravity / coding-assistant projects into portfolio pieces. Practical steps: Where to showcase your work (GitHub, personal site, LinkedIn). How to describe projects in a way hiring managers understand. Building a learning → practice → project → job pipeline for yourself. Resources Antigravity / Coding Assistant Demo: (Add your repo or demo link here) AI Agents & Shopping Examples (if any): (Add link here) Career / Job Prep Resources: (Add your doc or page if you have one) Host: Mark Kerzner – / markkerzner ElephantScale Webinars: https://elephantscale.com/webinars/ Keywords n² − n even, Number Theory Challenge, Irrational Proof Style, Mathematical Habits of Mind, AI News, AI Agents Go Shopping, Shopping Agents, Antigravity Coding Assistant, Build Features Fast, Side Projects with AI, How to Get a Job in AI, AI Careers, Developer Portfolio, Mark Kerzner, ElephantScale, Weekly AI Webinar. If you want to grow your math brain, ship more features, and move closer to an AI job, hit the subscribe button and click the bell 🔔 so you don’t miss upcoming challenges and sessions.