Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is...

The biggest mistake people make about AI is thinking it’s coming for artists, writers, musicians, or programmers. They’re just first. AI is coming for almost every profession that depends more on a brain than a body. Accountants. Lawyers. Teachers. Consultants. Analysts. Customer service. Marketing. Management. Software engineering. Research. Finance. Medicine. Eventually almost every job where the primary product is human thought. Manual labor only looks safe because robotics hasn’t caught up yet. AI doesn’t have to replace an entire profession to destroy it. It only has to let one person do the work of ten. Companies don’t need AI to be perfect. They need it to be cheaper than you. Once that happens, replacing people stops being a technological question and becomes an accounting decision. For most workers, there is no safe career waiting on the other side. People tell themselves we’ll adapt like we always have. We won’t. The Industrial Revolution replaced muscle while making human intelligence more valuable. AI replaces the intelligence behind the work itself. Every previous technological revolution created new industries that still needed millions of people. AI is being built for the opposite purpose: producing more with fewer humans. The next comforting myth is that people will simply buy human-made products instead. No, they won’t. There will always be a luxury market for handmade art, music, books, furniture, and clothing. There are still people who buy mechanical watches and vinyl records. That’s a niche—not an economy. Most people buy whatever is cheaper, faster, easier, and good enough. Businesses care even less. They exist to reduce costs, increase output, and beat competitors. Sentiment doesn’t survive quarterly earnings. There is no hidden human economy large enough to rescue everyone AI makes unnecessary. The consequences don’t stop with unemployment. Workers are also consumers and taxpayers. If hundreds of millions of people lose well-paid jobs, they s

This is a submission for DEV's Summer Bug Smash: Smash Stories powered by Sentry. ...

submitted by /u/alphacolony21 [link] [留言]

Marketing teams sit on more data than ever, yet many still spend a large part of the week just assembling reports. By the time the numbers are clean and explained, the window to act has already narrowed. A more practical use of AI in this space focuses on detection and explanation rather than another dashboard. The system watches for unusual movements, surfaces the likely drivers, and presents them in plain language. Analysts spend less time pulling the same weekly views and more time deciding what to do next. The useful part is speed. When something shifts in performance, the team hears about it earlier instead of discovering it during a scheduled review. Of course this only works if the underlying data is reliable, otherwise the explanations become noise. Is anyone here already using AI this way for marketing performance, or are most teams still in the experimental stage? submitted by /u/Cloudy_Day912 [link] [留言]

Hey guys, What is currently the best tool for autocomplete in vscode given the recent changes to GitHub copilot free tier usage limits? Thanks in advance! submitted by /u/TalkHot2112 [link] [留言]

submitted by /u/Fcking_Chuck [link] [留言]

GitHub热门项目 | Self-hosted family planner - tasks, calendars, shopping, meals, budget. Your data, your server. | Stars: 1,205 | 25 stars today | 语言: JavaScript

Angular is well served for icons. Material Symbols alone runs to thousands of glyphs, and the community wrappers pull in dozens of other sets on top. Geography is where the shelf runs out. You get globes and map pins, sometimes a set of flags, rarely the outline of Japan and almost never the six states of the GCC. GeoIcons ships country and area icons as Angular standalone components, 422 of them at the time of writing. Adding one takes three steps: install the package, import the component by its ISO code, and render its selector. npm i @geoicons/angular import { Component } from ' @angular/core ' ; import { Us } from ' @geoicons/angular/countries ' ; @ Component ({ selector : ' app-root ' , imports : [ Us ], template : `<geoicon-us aria-label="United States" />` , }) export class App {} See it live on geoicons.io → That is the whole path. Below: inputs, styling, accessibility, and picking an icon when you only know the country at runtime. Key takeaways Install @geoicons/angular , import each country by its ISO 3166 alpha-2 code in PascalCase, and add it to the component's imports array. The class is Us ; the selector you write in the template is <geoicon-us /> . Styling props are explicit inputs, because Angular has no rest spread. Everything else goes on the host element. Icons render as decorative unless you name them, so reach for aria-label only where no adjacent text says the country. Step 1: Install the Angular package Add the package to your project: npm i @geoicons/angular It needs @angular/core and @angular/common 15.1 or newer, plus rxjs 7 or newer. That 15.1 floor comes from hostDirectives , which the icons use to share their styling inputs and which landed in that release alongside standalone components . The package sets "sideEffects": false , so the CLI can drop what you never import. List three icons in a component and you ship three. Why that matters for icon libraries . Step 2: Import by ISO code Every country ships as a named export under its ISO