Proven frameworks, Notion setups, and smart work systems.
TL;DR: I didn’t touch ChatGPT or Claude for 4 days — not by plan, just how the calendar fell. Nothing in my actual job broke. What piled up was busywork. What I noticed, only because I slowed down, was a habit I’d quietly stopped doing myself. Here’s the short answer: my job survived 4 days … 더 읽기
TL;DR: The one habit from my first year in supply chain planning that no AI formula generator has replaced: before I trust any number, I calculate it two structurally different ways and make sure they match. It takes about 30 seconds and it catches exactly the kind of silent errors I found when I tested … 더 읽기
TL;DR: After testing AI formula generation (ChatGPT-4o, Claude 3.5, and Formula Bot) across 50 real enterprise datasets, complex REGEX text extraction and multi-criteria lookups proved 100% reliable. However, dynamic array spills, circular inventory logic, and multi-sheet date offsets consistently created silent calculation errors. Here is where I rely on AI in Excel, where I refuse … 더 읽기
TL;DR: After 6 months of relying on AI meeting notetakers across 150+ operational calls, I discovered a critical flaw: AI tools transcribe 100% of spoken words, but consistently miss hesitant resistance, unspoken ownership handovers, and dealbreaker disclaimers. Verbatim transcripts create a dangerous illusion of consensus. Here is the 3-minute post-meeting protocol I use to fix … 더 읽기
TL;DR: Over a 14-day rigorous time audit (38.5 total hours logged in ChatGPT and Claude), only 50% (19.2 hrs) produced genuine high-leverage output. 31% (12.1 hrs) was eaten by prompt-fiddling and hallucination checks, while 19% (7.2 hrs) disappeared into aimless AI procrastination. AI does not automatically save time—it shifts time into new friction loops unless … 더 읽기
TL;DR: When tested on a delicate, real-world business negotiation email, Claude 3.5 Sonnet won decisively on tone nuance and required less than 2 minutes of editing. ChatGPT-4o was the strongest for mathematical logic and spreadsheet structuring, while Gemini excelled at large document digestion but lagged in human-sounding email register. Here is the direct verdict up … 더 읽기
TL;DR: The one document I will never delegate to ChatGPT, Claude, or any optimization algorithm is the Critical Component Shortage & Customer Allocation Report. When physical supply runs short, mathematical optimization fails because it ignores unwritten contract penalties, vendor reliability nuances, and personal accountability when a plant stops. Here is the short answer: I will … 더 읽기
TL;DR: AI translators nail grammar, but getting the right tone is still a gamble. I trust them completely for low-stakes factual lookups, but for anything human-facing, I still write in English directly and only polish sentences with AI. Short answer: grammar isn’t the problem anymore — tone is. AI translation tools are excellent at sentence … 더 읽기
TL;DR: Where a 13-year supply chain planner actually uses AI — and where I deliberately don’t. I use it for spotting demand patterns, but never for final inventory formulas or confidential order-level data. Short answer: yes, but only for spotting patterns in the numbers — never for the actual inventory formulas, and never with real … 더 읽기
TL;DR: I tested 4 AI background removal tools across 200 real site images over 5 days. For clean, single-subject shots, remove.bg is the fastest. For messy, low-contrast, or cluttered images, PhotoRoom is noticeably better. If you only need this occasionally, remove.bg is more than enough. Every post on this site needs 2-3 images, and every … 더 읽기