In-depth reviews and guides for modern AI tools and autonomous agents.
TL;DR: AI wrote most of my iPhone app, and it built without a single error. That was the dangerous part. A ten-minute check before submitting found five hidden problems, from a crash waiting to happen to a payment bug that would have given away free upgrades. The checklist and the exact prompt I use are … 더 읽기
TL;DR: I have spent thirteen years planning semiconductor and consumer supply chains in spreadsheets. I did not know how to write a single line of Swift. On September 21st, I shipped a fully native iOS Dynamic Island utility clock to TestFlight. I did not write code; I wrote specifications. When non-engineers paste raw AI snippets … 더 읽기
Google announced Gemini 4 Argon with an unprecedented 1-million-token output limit. While tech feeds celebrate generating 800-page software suites with one prompt, operational reality paints a different picture: Verification Debt. Here is why unchecked long outputs multiply silent hallucinations, and the 3-Gate Sanity Protocol our team enforces before trusting autonomous code.
TL;DR: Every operations manager hits the same compliance wall: you want AI to summarize a messy 60-page carrier contract or redline a supplier dispute memo, but company policy strictly forbids pasting unreleased tier-1 pricing sheets into cloud LLMs. For the past three weeks, I ran local, offline models on an M3 Max Mac (64GB unified … 더 읽기
TL;DR: AI tool sprawl happens quietly. You sign up for a $20/month browser research tool for a single vendor negotiation, spin up two extra Claude seats for a temporary intern, and configure a headless Python script to parse freight manifests. Two months later, the project ends, but the billing goes on forever. On September 4th, … 더 읽기
TL;DR: Large language models are trained to please you. When you draft an ambitious operations timeline or a new supplier consolidation plan and ask an AI for feedback, it will flatter your judgment, validate your assumptions, and tell you your proposal looks exceptional. That polite sycophancy cost our logistics desk an expensive weekend delay back … 더 읽기
TL;DR: Whenever our warehouse leads needed a quick safety stock calculation or a container pack estimate, they opened an Excel sheet with 14 tabs and broken macros. It was slow, ugly, and prone to overwritten formulas. Last Tuesday, I used Claude 3.5 Sonnet’s Artifacts feature to build four standalone interactive web calculators—with sliders, reactive graphs, … 더 읽기
TL;DR: In my last post, I shared how dirty spreadsheets cause a 31% silent error rate when processed through Claude or ChatGPT. Doing the 7-step pre-flight checklist by hand takes 6 minutes per file. If you run multiple vendor sheets a day, that friction kills the habit. I wrote a standalone 90-line Python script that … 더 읽기
TL;DR: After 90 days feeding real production spreadsheets to Claude and ChatGPT, I found 3 errors that kept recurring silently: date format collisions that skew averages, blank rows that inflate totals, and cross-sheet formula references that break the moment you upload a file to an AI session. None of them threw an error message. All … 더 읽기
TL;DR: Single-chat AI threads die by Day 5 of any real project. They forget your negative constraints, truncate background PDFs, and force you to re-paste guidelines twenty times. Both Anthropic’s Claude Projects and OpenAI’s Custom GPTs claim to solve this with dedicated project workspaces. After running a multi-week supplier freight RFP and a warehouse SLA … 더 읽기