标签：#m

Every camera-equipped connected device you build today, from a smart doorbell to an ESP32-CAM streaming frames over Wi-Fi to a factory machine-vision rig, is a descendant of one clunky, toaster-sized prototype: the first digital camera , built at Eastman Kodak in December 1975. It weighed about 8 pounds, took 23 seconds to capture a single 0.01-megapixel black-and-white image, and recorded that image to a cassette tape. It looked like a science-fair project, but it proved a radical idea that underpins the entire IoT sensing industry: an image could be captured, digitized, and stored as data with no film at all. An engineer, a side project, and a CCD The camera was built by a 24-year-old Kodak engineer named Steven Sasson . His manager had handed him a loose assignment: could the newly invented charge-coupled device (CCD) image sensor be used to build a camera with no moving film? The CCD, developed at Bell Labs in 1969, converts light falling on an array of tiny capacitors into electrical charge, pixel by pixel. Sasson took a Fairchild 100-by-100-pixel CCD, bolted it to a lens from a Super 8 movie camera, added a digitizer, and wired the output to a portable cassette recorder. The result captured just 0.01 megapixels, a grid of 10,000 pixels. To view a photo, Sasson's team built a custom playback rig that read the tape and painted the image onto a television screen. That first image, a Kodak lab technician, took 23 seconds to write to tape and several more to display. Crude, yes, but it was the first fully electronic, filmless photograph. Why Kodak shelved the future Here is the twist that every embedded engineer should remember. Kodak owned the patent on the first digital camera, but the company made its money selling film, chemicals, and photo paper. Executives saw a filmless camera as a threat to that business, so the project was quietly set aside. Kodak did file the patent in 1978 and collected licensing revenue for decades, but it never led the digital transiti

The Quest shipwreck is in worse shape than expected, but it has turned into a thriving marine ecosystem.

When Niantic dropped the first Pokémon Go trailer in 2015, it was hard to grasp how a bunch of players could work together to catch a pokémon like Mewtwo. But this week at the game's 10th anniversary event in New York City, Pokémon Go showed the world how it's done. Almost 2,000 players (many of […]

Six years in prison for man who "sold out the very victims he was hired to represent."

Backlash online is changing how (or if) people wear Meta's smart glasses.

The children who get a combination shot are some of the most vulnerable.

Stop Writing Prompt Strings: Meet PromptForge Core As AI becomes part of modern applications, prompts are no longer just strings—they're becoming part of your codebase . Yet most of us still write prompts like this: const prompt = " You are a helpful assistant. \n " + " Summarize the following text. \n " + " Return the output as JSON. \n " + " Keep it concise. \n " + " Use simple language. " ; This works... Until your project grows. The Problem As prompts become larger, they quickly become difficult to maintain. You start dealing with: ❌ Giant string templates ❌ Copy-pasted prompts ❌ Missing variables ❌ Inconsistent formatting ❌ Provider-specific implementations ❌ Difficult debugging Unlike your application code, your prompts have: No structure No validation No type safety What if prompts were treated like code? That's exactly why I built PromptForge Core . PromptForge is an open-source TypeScript toolkit for building production-ready prompts using a clean, structured API. Instead of writing strings... const prompt = " You are... " You write import { pf } from " @promptforgee/core " ; const summarize = pf . define ({ input : z . object ({ text : z . string (), }), output : z . object ({ summary : z . string (), }), messages : ({ text }) => [ pf . system ` You are an expert summarizer. ` , pf . user ` Summarize: ${ text } ` , ], }); Much easier to read. Much easier to maintain. Features PromptForge focuses on developer experience. ✅ Type-safe prompt definitions ✅ Structured prompt composition ✅ Prompt compilation ✅ Validation ✅ Provider-agnostic architecture ✅ Reusable prompt blocks ✅ Modern TypeScript API Compile Once, Use Anywhere Instead of maintaining different formats for every provider... PromptForge compiles your prompt into provider-specific formats. Prompt Definition ↓ Prompt Compiler ↓ OpenAI Anthropic Gemini Ollama Write once. Compile anywhere. Composable Prompts Large AI applications usually repeat the same instructions. With PromptForge you can compose p

Last month I watched Cursor confidently rename a field across an entire API, commit it, and open a PR. Clean diff, tests green, looked great. It had also just broken a mobile client and a partner integration that were still reading the old field name — and neither Cursor nor I noticed until much later. That's the thing about AI coding agents and APIs: they're fast, they're fearless, and they have zero awareness of your API contract . An agent will drop an endpoint, make a request field required, or change a response type without any sense that a real consumer out there depends on the old shape. The code compiles. Your tests pass (your tests — not the consumer's). The breakage is completely silent until someone downstream feels it, usually in production, usually from an angry message rather than a failing build. We keep giving agents more power to write API changes and nothing to tell them whether a change is safe to ship . So I built that missing piece as an MCP server. The gap: there's no "is this safe?" step in the loop Think about how you'd catch this manually. You'd diff the old and new OpenAPI spec, look for removed endpoints, removed response fields, tightened request contracts, enum narrowing — the classic breaking changes — and decide whether it's safe to merge or whether you need a version bump and a heads-up to consumers. An agent never does that. It has the code in context, not the contract implications . And "did I just break a consumer?" is exactly the kind of question it should be asking before it hands you a diff. Enter MCP If you haven't used it yet: the Model Context Protocol is a standard way to give AI agents tools — little capabilities they can call. Claude, Cursor, and others all speak it. Instead of the agent guessing, it can call a tool and get a real answer. So the fix is simple to state: give the agent a tool that answers "is this API change safe to ship to my consumers?" — and have it call that before it proposes the change. That's the hero

While building a Computer-Based Testing (CBT) platform, I ran into an unexpected problem. Creating mathematics and chemistry questions wasn't nearly as straightforward as I expected. Although there are many excellent editors and open-source libraries available, I couldn't find one that brought everything together in a way that was simple, lightweight, and designed specifically for CBT systems. Instead of building everything from scratch, I took a different approach. I combined several powerful open-source technologies into a single editor that focuses on one job—making it easy to create mathematics and chemistry content for online examinations. The result is CBT Editor, a free and open-source equation editor built for developers, schools, and educational platforms. It supports common mathematical expressions, chemistry notation, scientific symbols, fractions, superscripts, subscripts, and more, while remaining easy to integrate into existing projects. This project isn't meant to replace the fantastic libraries that already exist. In fact, it depends on them. The goal is to provide a clean, unified experience so developers don't have to spend hours combining multiple tools just to support technical examination questions. If you're building a CBT platform, an online examination system, or any educational application that requires mathematics and chemistry editing, I'd love for you to give CBT Editor a try and share your feedback. 🔗 Live Demo: https://holygist.github.io/cbt-editor/ Open-source software grows through collaboration. If you find the project useful, feel free to contribute, report issues, suggest improvements, or simply share it with other developers.

Learn TypeScript From First Principles to Senior/Staff-Level Production Engineering If you searched for how to learn TypeScript properly — not just the syntax, but the thinking behind it — this guide is built for that. Most TypeScript tutorials stop at "here's an interface, here's a generic." This one goes further: it's a single, exhaustive TypeScript tutorial and reference that walks through the type system, object-oriented programming, generics, async programming, design patterns, SOLID and DRY principles, error handling, testing, and the tooling that real production teams run in CI — the same TypeScript best practices used at top-tier engineering organizations. Whether you're a beginner looking for a structured TypeScript for beginners path, or an experienced JavaScript developer making the jump to advanced TypeScript and system design, you can read this end to end or jump straight to the section you need using the linked table of contents below. Table of Contents 1. Introduction — What Is TypeScript & Why It Exists 2. Installation, Setup & tsconfig.json Deep Dive 3. Variables & the Complete Type System 4. Functions — Every Form, Overloads, this , and Best Practices 5. Arrays & Tuples 6. Objects & Type Aliases 7. Interfaces 8. Enums & Literal Types 9. Union, Intersection & Discriminated Unions 10. Type Narrowing, Assertions & Type Guards 11. Classes & Object-Oriented Programming 12. Generics — Basic to Advanced 13. Modules, Namespaces & Project Structure 14. Asynchronous Programming — Event Loop to Production Patterns 15. Advanced/Utility Types & the Type-Level Programming Toolkit 16. Design Patterns in TypeScript 17. SOLID, DRY, KISS, YAGNI — Principles Applied With Real TS Code 18. Error Handling Strategies 19. Testing TypeScript 20. Tooling, Linting, Build Systems & CI/CD for Production TS 21. Performance, Compiler Internals & Scaling Large Codebases 22. Interview Cheat Sheet (Expanded) 23. One-Page Quick Revision Sheet 1. Introduction — What Is TypeScript & W

How I Supervise Three Engineering Workflows at Once Three Workflows, One Operator Right now, I have three engineering workflows open. One is under council review. Four AI roles are challenging an architectural proposal, and I will need to decide which objections actually change the plan. The second is already in implementation. That one does not need me at the moment. The specification is approved, the boundaries are clear, and the executor can keep moving. The third has come back from audit. The findings are valid, but corrective work is paused. A remediation plan exists, and someone other than the executor needs to review it before any more code changes. This is the part that still feels new: I can move between all three without reopening old chats and rebuilding the story in my head. A few months ago, even one workflow could take most of my attention. I carried context between every stage: rewriting role prompts, moving decisions between conversations, tracking the current document, and turning audit findings into the next round of work. The AI council itself was already useful. It produced strong reasoning and exposed assumptions I would probably have missed. But I was still the glue around it. The council improved the decisions. The system around it made those decisions easier to carry into implementation, audit, and correction without losing control. Conversations Were No Longer the Workflow The main change was simple to describe: I stopped treating the workflow as a series of conversations. Chats are good for thinking. They are not a good place to keep authority. Before this change, a decision might exist somewhere in a long discussion. The next agent had to interpret it, and I had to remember whether it was final, provisional, or already replaced. Now the state of the work lives in a small set of artifacts. Evidence becomes a source-grounded brief. Decisions become an approved specification. The specification becomes bounded implementation. The implementatio

Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. Star git-lrc to help devs discover the project. Do give it a try and share your feedback. You've been using the terminal for months/ years. Maybe you cd into a folder, ls around, run your script, and call it a day. That's fine. That's like knowing how to boil water and calling yourself a chef. But the terminal has layers . It's basically an onion that occasionally makes you cry, usually around 12 AM when a script fails silently and you have no idea why. So grab your coffee and let's talk about the command line tricks that actually make your life better. Not the "did you know ls -la shows hidden files" tier tips. Your Terminal Has A Memory. Use It. Most devs mash the up arrow like it's 2007 and they're trying to beat a Flash game. Stop that. Press ctrl-r instead. It searches your command history live. Type a few letters, it finds the last matching command. Press ctrl-r again to cycle back further. Found it? Hit Enter to run it, or the right arrow to drop it into your prompt so you can edit it first. ctrl-r ( reverse-i-search ) ` docker run ` : docker run -it --rm -v $( pwd ) :/app node:20 bash Pair this with ctrl-w (delete last word) and ctrl-u (nuke the line back to the cursor) and you'll start editing commands like you're speedrunning a text adventure. And if you're the type who types a whole essay of a command and then realizes you forgot something at the start, ctrl-a jumps to the beginning of the line and ctrl-e jumps to the end. No more holding the left arrow key like it owes you money. Pro tip: if you're a TUI fan and ctrl-r's default search feels a bit flat, check out McFly xargs Is The Friend Who Actually Shows Up Pipes ( | ) are great. They pass output from one command into another. But sometimes you don't want to pass output as input , you want to pass it as arguments . That's where xargs comes in, and once you get it,

Better to sacrifice a part to preserve the whole. — The 36 Stratagems, Sacrifice the Plum Tree to...

Solid-state batteries are safer and more capable—but harder to mass-produce. They also represent an opportunity for non-Chinese companies to get back in the game.

The movie-centric social network is said to be seeking new ownership.

HyperTexting's new app aims to make the open web feel more like social media by turning websites, blogs, newsletters, and podcasts into a scrollable feed, while also making it easier to post to your own website.

Nearly every streaming service has an ad-supported plan, but Disney might take the unusual step of making it free.

Spotify is giving listeners control to fine-tune what gets surfaced for them in Release Radar - one of its most popular weekly playlists. The new options allow you to narrow the playlist to a specific genre, focus on artists that are new to you, and more. Listeners can choose from up to five options like […]

Dozens of titles too taxing for Steam Deck are still unrated for the new hardware.

China's state-owned space company recovered its first orbital rocket booster after launch.