标签：#showdev

People keep asking how I did it. The honest answer: I didn't "do" anything special. I just shipped something weird and somebody on Hacker News happened to see it. The beginning One year ago I was 14 and bored. I had built maybe 5 "projects" that died on my hard drive. So I spent a Saturday scraping startup names from Product Hunt, pasting them into a JSON file, and throwing together a single HTML page with terrible CSS. I posted it on HN with the title: "Free crunchabse alternative" It hit the front page. 400 upvotes. 600 comments, mostly roasts. A few people actually looked at the directory. Someone asked "how do I add my startup?" I said "I don't know, I just made this in a weekend." That was the first 20 startups listed. The pivot Those 20 startups turned into 200. Then 2,000. I kept answering every comment, fixing every bug reported within 24 hours, and shipping the next feature people actually wanted. Nobody cared that my code was messy. They cared that someone their age was building something they could actually use. Today StartupWiki is now an AI-powered research directory with verified startup profiles, funding data, competitive analysis, and team insights. We just launched our new Launch Platform where startups can submit, verify their badge, and get discovered by the community. And the view count is climbing in a way that still surprises me. The metric everyone obsesses over is the one that's already happened. The real signal? Strangers emailing me asking how to get listed. What I've learned at 15 Ship ugly first. My first version had hardcoded data and a broken CSS gradient. It worked. People didn't care that it was ugly — they cared that it existed. HN is a launchpad, not a home. That first post gave us the initial users. What kept them was the follow-up: answering every request, fixing every bug, shipping based on actual feedback. You don't need permission. I'm 15. I can't rent a car, vote, or legally sign most ToS. None of that stopped me from building

Faker Doesn't Know Your Entities Are Related, So I Built Something That Does You've added a second entity to the schema, wired up a @ManyToOne , and gone back to your seed script to generate fifty more rows. Ninety seconds later, the app refuses to start: unique constraint violation, somewhere inside a loop you wrote three weeks ago at 11pm. You fix it. You restart. A different field breaks a different constraint. This is the exact moment every Spring Boot developer eventually meets the real limit of tools like Faker. They're brilliant at generating a name, an email, an address. They have no idea the Payment sitting in front of them needs a Counterparty to already exist. So you do what everyone does: hand-write the wiring. Create parents first. Hold onto their generated IDs. Wire them into children. Hope you didn't just violate a @NotNull somewhere in the process. It works, for a while. Then the schema changes, and the script quietly stops matching reality until the next 3am debugging session finds out the hard way. I hit this enough times that I stopped patching the script and looked at the actual problem: the information needed to seed this correctly already exists. It's sitting right there in the entity, in the annotations you already wrote. @ManyToOne , @NotNull , @Column(unique = true) , JPA already knows the shape of your data. Nothing should need to be told that twice. That became SynthForge . The core idea Instead of writing a script that generates data, you annotate the entity: @Entity @Seed ( count = 50 ) public class Counterparty { /* fields only */ } @Entity @Seed ( count = 200 ) public class Payment { @ManyToOne ( optional = false ) private Counterparty counterparty ; } Start the app in a dev profile. Both tables populate, correctly ordered, on every restart. No seed method. No calling code, anywhere. The entity is the seed script. What's actually happening underneath Entity scanning. SynthForge reads JPA-managed attributes through the jakarta.persisten

Welcome to part one! This is the start of a series where I’ll be posting about my webdev and HTML nightmares. I hope you enjoy the read as much as I hate User Interfaces! Consider this a shared space for learning—I’m sharing what I’ve learned so far, and I’d love to hear your thoughts or better solutions in the comments. To kick things off, let’s talk about how this whole mess started. As a solo developer, you want to spend 99% of your time actually building the things you love. So when it’s time to share builds with early playtesters, I naturally take the path of least resistance... a pinned link in a Discord channel and a shared Google Drive folder. And for a while, it works. Until it suddenly doesn't. The Problem: The "Easy way" Trap Privately, with a small group of alpha testers, Discord is great. You can pin messages, create specific channels, and guide people directly. But as soon as you want to go public, Discord becomes a nightmare for onboarding new users: The "Tutorial" Requirement: If a new user needs a 5-minute guide just to navigate your Discord server to find the launcher or the latest release, you’ve already lost them. Zero Discoverability: Discord is great for community and chat, but terrible as a public storefront or documentation hub. Searching for news, filtering updates, or finding launcher links creates massive friction. Lack of Professionalism: To offer real support, showcase features, and look trustworthy to a public audience, you need a single source of truth—not a maze of text channels lost to the void. I didn't have time to manage an overly complex custom web setup or pay high monthly SaaS fees, but I needed a clean, low-maintenance way to go public. Yes, I spent no more than thirty seconds drawing this on my Bamboo tablet: Why Google? (And the Launcher Evolution) Before even thinking about the website, I had to solve the distribution problem for my launcher. I experimented with several download pipeline prototypes: Git Repos / Diversion (f

Hey guys 👋 Quick devlog on the side project. I'm building an open-world stickman superhero game. Flat white surfaces, black outlines, no textures and no colour anywhere. The whole city is built from modules on a grid rather than baked meshes, which is the load-bearing decision of the project: destroying a wall is removing a module and building one is adding it back, so destruction and construction are the same system. This week went into the landscapes, so I wanted a 20 second clip flying through a few of the districts. The bit that was actually interesting I wanted the footage captured out of the real game rather than reconstructed in an editor. The obvious approach is to drive it with Playwright and take a screenshot every frame, but that falls apart immediately: rendering under automation is far slower than a screenshot loop can keep up with, so wall-clock capture stutters and the timing drifts. The fix is to stop letting the clock decide. Before the game boots, hijack requestAnimationFrame and queue the callbacks instead of running them: replace requestAnimationFrame with a function that pushes the callback onto a queue- expose a step(dt) that advances a virtual timestamp and drains the queue- call step(1000 / 30) once per screenshotEvery captured frame now advances the simulation by exactly 1/30th of a second, whatever the renderer is actually doing. A frame that takes 300ms to draw and a frame that takes 8ms produce identical motion. The result is smooth 30fps footage from a renderer that never once hit 30fps, and it is deterministic — the same seed gives you the same clip every time. The same rig drives the camera: for the aerials it detaches the chase camera and dollies an external one between two framings, and for the traversal and combat shots it just feeds synthetic input to the real player controller. Nothing in the video is staged. ## Stack Three.js driven imperatively, Rapier for physics, React for the HUD only, TypeScript in strict mode, packaged with

A torrent client that works on your iPhone I wanted to download a film to my iPad on a train and watch it. That turned out to be surprisingly hard. Every torrent app worth using is desktop software. On iOS there's essentially nothing — Apple doesn't allow it, so the App Store options are either gone, crippled, or asking for a subscription to a "cloud downloader" that keeps a copy of everything you touch on somebody else's server. So I built one that just runs in a browser tab. No install, no account, no App Store. It's at wasmtorrent.pages.dev if you'd rather poke at it than read about it. What it does Open the page, paste a magnet link, and it downloads. The whole client is compiled to WebAssembly and runs inside your browser — there's no server of mine involved at any point. A few things that make it actually usable rather than a demo: Stream while it downloads. You can start watching before it finishes, and seek around — it fetches the parts it needs. Files whose codecs your browser refuses fall back to a software player. Save to your device. On iPhone and iPad that means straight into the Files app, in Downloads. Install it to your home screen. It's a progressive web app, so it gets an icon and its own window, and the interface works offline. It tells you when downloads finish , with a deliberately vague message — "one of your downloads has finished", never the name. Notifications land on lock screens where anyone can read them. The awkward part, explained honestly Here's the thing nobody tells you about torrents in a browser: a browser can only make WebRTC connections. Ordinary torrents use TCP peers. A web page physically cannot dial those — it's not a limitation of my code, it's what a browser is. So most magnet links you find will sit at 0% forever in any in-browser client, including this one. That's why they all feel broken. The fix is a small companion app called the bridge. You run it on a computer you already leave on — a Mac, a PC, a Linux box, a home s

This is a submission for Weekend Challenge: Generosity Edition TL;DR Happen to Have? is for somebody who needs one answer and still has something useful to give: answer a stranger before asking your own question. An answer fans out to four Gemini calls—processing, crisis, illegal or dangerous content, relevance. A question gets three, since relevance has nothing to compare it with. Only processed text is ever published. The original recording exists for the length of one request and is never stored. Halfway through, the measurement behind my strictest architectural rule turned out to be confounded, and the rule came out of the constitution. Live at happentohave.anchildress1.dev , with five feature specs, the measured guardrail results, and the full implementation in the repo. Target category: Best Use of Google AI. What I Built Nobody Called It Anything 🪧 Going to church every Sunday was a requirement while I was growing up, and the ladies there had a group called the Busy Bees who would do literally anything that needed doing for somebody in need. So when this challenge asked me to "build something in the spirit of generosity," that's what I thought about first. The problem was translating that to a scale that actually works. The Busy Bees worked because everybody already knew everybody, and that is not true of an app accessible from anywhere. I spent the next hour trying to brand the thing, running back through everything I could remember about how generosity has actually shown up in my life, and it eventually hit me that there's no word for any of it—because it's so normal where I live. A complete stranger is stranded with a flat tire, and you spend an hour on the shoulder helping, just because you happen to have a jack in the truck bed. It's not out of the ordinary enough to need a name. So I built Happen to Have? on the idea that if you happen to have a solution, you share it. A donation tracker would have been simpler. It also would have left giving optional.

The idea I wanted a small side project that could actually run itself once shipped — no cron jobs to babysit, no upstream API to go down at 3am and take my uptime with it. That constraint led somewhere specific: an API that validates common business data formats — phone numbers, IBAN, VAT/tax IDs, BIC/SWIFT codes, credit card numbers, postal codes — using nothing but offline checksum and format rules. No third-party lookups. No API keys to rotate for an upstream provider. No rate limits inherited from someone else's infrastructure. If it's slow or wrong, it's my bug, not a dependency's outage. The stack Hono on Cloudflare Workers — TypeScript, no cold starts, runs on the free tier comfortably up to 100k requests/day libphonenumber-js , ibantools , jsvat , card-validator — all well-maintained, all pure computation, zero network calls Vitest for tests, run against real fixtures (not made-up test data — every "valid" example in my test suite is a real IBAN/VAT/card number pulled from each library's own published examples, verified against the actual library output before I trusted it) The whole thing is about 300 lines of TypeScript across the router and six validator modules. Small enough to actually reason about, which mattered more to me than feature breadth. app . post ( " /v1/iban/validate " , async ( c ) => { const body = await c . req . json < { iban ?: string } > (). catch (() => null ); if ( ! body ?. iban ) { return c . json ({ error : " missing required field: iban " }, 400 ); } return c . json ( validateIban ( body . iban )); }); The part that actually surprised me I expected the code to be the hard part. It wasn't. Deploying and listing it on RapidAPI was. Two things stood out: CORS mattered even though I "shouldn't" need it. Real production traffic through RapidAPI's gateway is server-to-server — CORS is a browser-enforced concept, so I assumed it was irrelevant. But RapidAPI's own in-dashboard request tester runs as a real browser fetch, and without an O

Hi, my name is Yaniv Morozovsky, and I have worked in the radio industry for more than three decades. Most of that on SAM Broadcaster and, lately, AzuraCast. On 13 July I did something I had wanted to try for a long time: I handed one of my internet stations to automation completely, with nobody in the studio, and did not touch it. It is still on air today: https://ystream.live Some honest notes for anyone who runs a station and has wondered about the same. Segues are the whole game. The thing that makes automation sound like a jukebox is the fade timer. Every song fading at the same point, every cold ending faded when it should stop dead. What fixed it was analysing every song once (intro end, vocal entry, outro, the real ending) and crossing on those points per song. Once that was in, listeners stopped noticing there was no one there. Making an automated station sound like a DJ is mostly making the crossfades right, and that was our biggest achievement from day one. The voice matters less than where it lands. I cloned my own voice for the breaks, and honestly the voice itself is not what people comment on. What they hear is whether the talk-up ends before the vocal. When it lands, it sounds like radio. I let the AI DJ open every hour, read the weather, and in the last week also read a short news segment when the hour begins. Scheduling by rules beats scheduling by clocks, most of the time. Key, tempo, energy, era, genre, artist separation, and a few written rules like "start every hour with an international song". The hour writes itself and I stopped building clocks. What I gave up was the twenty years of Clockwheel habits, and there were days I missed them. Some of the most annoying bugs of automation software, like repeating the same song over and over, or playing the same artist twice in the same hour, are all gone. The boring parts decide whether you can actually broadcast. Royalty reports, listener stats per song, loudness that holds across a 1975 master and

DevTools responsive mode has one limitation that's never been fixed: you see one device at a time. You check iPhone. Looks fine. Switch to iPad. Fix padding. Switch back to iPhone. Was the header already broken or did you just break it? I got tired of holding layouts in my head, so I built a tool that shows all three at once. Responsive Tool — free, no signup Paste a URL → phone, tablet, and desktop load at one time. That's it. A few things that make it actually useful day to day: Swap one pane to a different device without losing the other two Refresh one pane after a code push — no need to reload everything Share your exact setup via URL — a teammate sees the same device comparison you do Sync scroll across all panes with a one-line script snippet Every viewport is a real verified CSS size , not a guess No account. No extension. No download. Runs in the browser. I don't see or store the URLs you test. Also: way more sites block iframes via X-Frame-Options than you'd think. I tested ~60 real sites — 93% of developer portfolios loaded fine, but only 44% of framework/marketing sites did. If your site doesn't load, that's the server blocking iframes, not a bug in the tool. Stack Next.js 16 · React 19 · TypeScript · Tailwind v4 · Cloudflare Workers Bonus I also built a CSS breakpoints reference that maps common breakpoints to real device viewports. Handy even without the tool. 👉 responsivetool.com What do you use for responsive checking? Still just DevTools? I want to know what I'm up against.

readm3 can edit now, and it speaks Reddit readm3 started as a markdown reader for the terminal. File browser on the left, rendered document on the right. Version 0.3.0 adds the obvious missing half: you can change the file you are looking at. Press e , type, press esc . The preview has already re-rendered by the time you get back to it, because both modes read the same buffer. There is no second preview to keep in sync, which is the part that usually goes wrong in editors with a live preview pane. ctrl+s saves. Quitting with unsaved work asks first. enter continues the list you are in, so the same bullet, the next number, or an unchecked box for a task, and pressing it on an empty item ends the list. There is no selection and no cut and paste. This is for fixing a typo and adding a paragraph. Your editor is still your editor. Two dependencies, not forty The old parser was a few hundred lines of hand-rolled regex, and it got reference links, nested lists and bare URLs wrong. Every fix was another regex. Parsing moved to marked. The reason it won was not features, it was weight: marked is CommonMark plus GFM with zero dependencies of its own . readm3 went from one dependency to two. markdown-it would have been seven. A remark and micromark pipeline is somewhere between twenty and forty packages, for a program whose whole point is that it starts instantly in a terminal. Only the parsing moved. The layout code that wraps text, draws code gutters and sizes tables is untouched, so readm3.com still renders through the exact same functions the terminal does. There is still no second renderer. The swap fixed reference links, nested and loose lists, bare URL autolinks and hard line breaks for free. The dialects actually disagree marked does not ship GitHub alerts, footnotes, :emoji: , or anything Reddit added. Those are tokenizer extensions in readm3 now, still with no new dependency. They are behind a --flavor switch rather than all on at once, because the dialects contradic

This is a shortened version of my original post . My wife and I have blogged about every trip since our honeymoon 10 years ago. For the people at home, for ourselves later, and by now for our children. We took turns writing, but both had photos and videos on their phones. The text was never the hard part. The photos and videos were: every day one of us sent them from the phone to the other, who had to upload them and sort them into the entry in the right order. So I wrote Texttile , an open-source blog engine built for writing together. One entry, two screens Multiple people can have the same entry open. One of them has the text and types, the other watches the words arrive and can take the text over with one click. Both can still work on the gallery. Photos and videos belong in the same gallery. Videos come from your own server. Drop one in and Texttile converts it, thumbnail included. No YouTube embed, no player from anywhere else. One container, one folder Phoenix, LiveView, ffmpeg and SQLite live in one Docker image. Everything is in /data . Move that folder and you move the blog. A reader's browser talks to your server and nothing else. No CDN, no tracker, no hosted font. What it is not There are no roles, no permission matrix, no plugins, no theme marketplace. Everybody with an account is an admin. I built it for people who trust each other, because that is who writes a blog together. You can try it or read the source . The full story includes a video showing both screens. How do you blog on the road?

I Built a Mobile Terminal Around My herdr + Codex Workflow I am building Termish , an open-source mobile remote-work tool for SSH/Mosh terminals, file management, remote screens, and AI-assisted development. The unusual part is that I built much of Termish through Termish itself. My daily workflow is: Termish on my phone → herdr on my host → Codex in the project The development environment and AI tools run on my own machine. My phone is where I enter commands, describe tasks, upload screenshots, inspect changes, and check the resulting UI. Termish is both the product I am building and a tool I use to build it. Put remote work in your pocket. Source code: github.com/ttermish/termish Why do AI-assisted coding on a phone? A phone is not a replacement for a desktop machine. Its screen is smaller. Reading a large codebase is harder. Long debugging sessions are more comfortable on a larger display. Those limitations are real. But AI-assisted development changes part of the workflow. Many tasks become: Describe a requirement. Provide context. Let an agent make changes. Review the output. Run a command or test. Decide what to change next. Some of that loop works well on a phone. For example, when I think of a feature away from my desk, I can open the project and ask an agent to start implementing it. When I find a UI problem, I can upload a screenshot to the host and ask the agent to inspect it together with the code. After the change is done, I can review the diff, run tests, and check the actual UI through a remote screen. The goal is not to write an entire application on a phone. The goal is to make a phone a useful place to start work, inspect work, and keep a task moving. Why another SSH and AI coding tool? This is a fair question. Tools such as Termius and Blink already provide strong SSH, Mosh, and file-management experiences. If you already have a setup that works well, you can run Codex, Claude Code, or other agents through a terminal today. Happy and similar produ

1. Project Introduction and Objective In this project, I used Microsoft Excel and Power Query to clean and analyze a Jumia product dataset and then built an interactive dashboard to summarize pricing, discounts, ratings and customer engagement. The main objective was to turn a small raw e-commerce dataset into useful business information. I wanted the final dashboard to answer practical questions such as: Do products with higher discounts receive more customer engagement? Do higher priced products have better ratings? Is there a relationship between product rating and number of reviews? Which products have the highest review engagement? Which products may require further investigation because they have high discounts but low ratings? The project also gave me practical experience in data cleaning, excel formulas, PivotTables, PivotCharts, slicers, correlation analysis and dashboard design. 2. Dataset and Business Questions The original dataset contained 115 rows and 6 columns: Product Current price Old price Discount Review Rating The dataset was small but it contained several realistic data quality problems. This made it useful for me to practice the complete analytics process rather than going directly to visualization. I structured the workbook into the following sheets: Raw_Data Cleaned_Data Analysis Pivot_Tables Dashboard Data_Dictionary As we have always been taught in class,I kept the Raw_Data sheet unchanged so that I always have a copy of the original source data. 3. Initial Data-Quality Audit Before cleaning the data, I profiled the dataset in Power Query using Column Quality, Column Distribution and Column Profile. The audit identified several issues: Data-quality check Result Original rows 115 Original columns 6 Blank Review values 58 Blank Rating values 58 Populated Review values stored as negative numbers 57 Current Price ranges 1 Old Price ranges 1 Exact duplicate rows removed 3 Discount values outside 0 to 100% 0 Rating values outside 0 to 5 after cle

A build log on ESP, six VST3 plugins written in C++ with JUCE 8 and shipped through a store I built myself. What the framework does for you, where it stops, and the one measurement that changed how I work. The line Six plugins, all JUCE 8, all VST3 plus standalone, all GPL v3, all downloadable from esp-plugin-store.vercel.app : Plugin What it is Basic Oscilator three oscillators on juce::dsp , the first thing I ever built, kept honestly VERTEX dynamic range compressor with a live transfer curve ESP-L1 brick-wall limiter with pre and post spectrum overlay MEGACRUSHER distortion, saturation and bit-crusher, three algorithms SPECTRUM real-time analyser, 2048-point FFT, spectrogram and 3D waterfall SYNTH/1 16-voice wavetable synth, unison, step sequencer, FX rack, interactive EQ That table is in the order I wrote them, and the order matters more than any single plugin. Each one starts roughly where the previous one ran out of framework. What juce::dsp actually hands you Basic Oscilator is three oscillators, three LFOs, a bit-crusher and a master gain. Almost all of it is the juce::dsp module doing the work: juce :: dsp :: ProcessSpec spec ; spec . maximumBlockSize = ( juce :: uint32 ) samplesPerBlock ; spec . sampleRate = sampleRate ; spec . numChannels = ( juce :: uint32 ) getTotalNumOutputChannels (); for ( int i = 0 ; i < 3 ; ++ i ) { oscillators [ i ]. prepare ( spec ); lfos [ i ]. prepare ( spec ); lfos [ i ]. initialise ([]( float x ) { return std :: sin ( x ); }); } masterGain . prepare ( spec ); That is the whole contract of the module. Prepare everything with one ProcessSpec , wrap your buffer in an AudioBlock , hand it to a processor as a context: juce :: dsp :: AudioBlock < float > block { tempBuffer }; oscillators [ i ]. process ( juce :: dsp :: ProcessContextReplacing < float > ( block )); juce::dsp::Oscillator takes its waveform as a lambda, so the three waves are three one-liners: case 0 : osc . initialise ([]( float x ) { return std :: sin ( x ); }); //

What started as "translate dialogs in a Korean game without alt-tabbing to Google Translate" became a rewrite of my screenshot toolchain. A few months later, one app: Capture area, window, or fullscreen Copy the text out of any screenshot, like it were a document Translate a foreign-language screenshot in place, offline Long pages stitch into one tall image Screen record with a camera bubble What I'm most happy with: zero network calls for reading and translating text. Screenshots carry API keys, client work, personal chats. Mine never left the Mac, and that felt like the right default for everyone's. Tech notes, happy to go deeper in comments: Pure Swift and SwiftUI, no Electron. About 25MB Apple's Vision framework for reading text. Genuinely scary good for how cheap it is One hotkey, everything else lives in menus Building in public. How you extract text from screenshots today would help me know what to chase next. Trial: https://ishot.buzz?utm_source=devto

Hi DEV! I got tired of free PC cleaners that bundle a registry cleaner nobody needs, count up a scary number of "issues", and then dangle a paid version at the end. So I wrote the boring version. CleanGeek finds and clears: Temp folders, user and system Browser caches across the installed browsers Windows Update leftovers and Delivery Optimisation cache Crash dumps and error reports Thumbnail cache and font cache Recycle Bin, if you tick it Every item shows what it is and how much space it is worth. Nothing is deleted until you press the button, and you can untick anything you want to keep. Why I built it There is no registry cleaner in it and there never will be. Cleaning the registry has not meaningfully sped up a Windows machine in about fifteen years, and the risk of breaking something is real. Same reason there is no "optimise your PC" button. The tool does one job and tells you exactly what it did. The other reason is the business model. Free cleaners generally are not free, they are a funnel. CleanGeek has no paid tier to funnel you into, no upsell screen, and no telemetry. Tech stack .NET 8, net8.0-windows Avalonia for the UI, with Avalonia.Desktop and Avalonia.Themes.Fluent No third party cleanup engine, the scanning is all in the app Avalonia was the right call. WinForms would have been quicker to get moving but the styling story is grim, and WPF ties you down harder than I wanted. Honest caveat The installer is not code signed yet, so SmartScreen may warn on first run. I am sorting that out. If that is a dealbreaker for you, fair enough. Links Site: https://techygeekshome.info/cleangeek/ Source: https://github.com/techygeekshome/CleanGeek Video: https://youtu.be/Z2s2p3nkIvY If it misses something obvious on your machine, tell me and I will add it.

I built a tool that draws architecture diagrams from a repository, where every edge cites the file, line and commit it came from. Then I ran it against thirteen repositories it had never seen, and every single one of them found something wrong with it. There were thirteen. These are the ones worth writing down. The list says nothing about those codebases. It says something about testing: a tool that reads other people's repositories has to be tested against other people's repositories, and there is no substitute. The rule the tool works by Nothing is drawn that cannot be cited. Every edge in the output carries the file, the line and the commit that justifies it — click an arrow, see the import statement. If a reference cannot be resolved to something in the repository, it is not quietly dropped and it is not guessed at. It is reported as a gap. That second half is what made these bugs findable. A tool that silently drops what it cannot resolve looks perfect and is useless. A tool that reports gaps by name and count tells you, loudly, every time it is confused. Java: a library sharing your package prefix is not you Guava declares com.google.common . Truth is a separate library, and it lives in com.google.common.truth . My resolver matched on package prefixes, so Truth looked like Guava's own code, and every reference to it became a gap against a package Guava does not contain. 834 false gaps — 28% of the repository. The fix is to require the next path segment to look like a type before peeling, because com.google.common.truth.Truth peels to a package and com.google.common.collect.ImmutableList peels to a class, and those are different shapes. Java: a file importing its own nested type Java requires the import for a nested enum constant even inside the same file. Treating that as a dependency has you drawing an arrow from a file to itself. It accounted for all 137 remaining gaps on Spring Boot and all 34 on Guava. Java: static imports point one segment too deep import

Solid-Vue is a lightweight Vue + Vite framework for small and growing businesses. File-based routing, a built-in server layer powered by h3, and zero extra config to wire together. Features File-based routing — every file in src/pages becomes a route automatically, via unplugin-vue-router. A server, built in — src/server/api holds your API endpoints, served through h3 alongside your frontend. One dev server, one deploy. Vite underneath — instant startup and near-instant HMR. State management ready — Pinia is wired in out of the box. Extensible via add-ons — install Tailwind CSS, icon sets, form validation, i18n, and more with the companion solid-vue-cli. Quick start Don't install this package directly — scaffold a new project instead: npm create solid-vue@latest my-app cd my-app npm install npm run dev Usage vite.config.ts import { defineConfig } from ' vite ' import { solidVue } from ' solid-vue ' export default defineConfig ({ plugins : [ solidVue ({ mode : ' spa ' }) ] }) src/main.ts import { createSolidApp } from ' solid-vue/client ' import App from ' ./App.vue ' const { app , router } = createSolidApp ( App ) router . isReady (). then (() => { app . mount ( ' #app ' ) }) src/server/api/hello.ts import { defineEventHandler } from ' solid-vue/server ' export default defineEventHandler (() => { return { message : ' Hello from Solid-Vue! ' } }) Plugin options solidVue ({ mode : ' spa ' , // 'spa' | 'ssr' | 'ssg' — default: 'spa' apiPrefix : ' /api ' , // prefix for file-based API routes — default: '/api' optimizeCWV : true , // inject Core Web Vitals meta/preconnect tags — default: true }) Package exports Entry Use solid-vue The Vite plugin ( solidVue ), used in vite.config.ts solid-vue/client createSolidApp() — bootstraps Vue, Vue Router, and Pinia solid-vue/server Re-exported h3 utilities ( defineEventHandler , readBody , useSession , etc.) for your API routes Add-ons Add optional integrations to an existing project with the CLI: npx solid-vue add tailwind npx so

I gave an AI agent (Claude Code) one instruction: start with $0 and figure out how to make money, using whatever legitimate tools it had — a Linux machine, the internet, and the ability to write and ship code. Here's what actually happened, because it wasn't what I expected. It didn't start with an idea. It started with research. Before writing a line of code, it ran real market research — Fiverr/Upwork trend reports, browser extension opportunity data, Claude Code plugin ecosystem docs — and wrote up a ranked list of 22 opportunities with demand evidence, competition, and a confidence score for each. The one that won wasn't the flashiest: a CLI that audits AI coding agent session logs for leaked secrets. Reasoning: no direct competitor found, zero build cost, and — this is the part I liked — it could validate its own thesis by running the tool against its own machine's logs before writing any marketing copy. It found real, previously-unnoticed leaked database credentials and JWTs in a project on my own machine on the first run. That's agent-audit , and it's live and free now. Then it hit real friction, and mostly handled it honestly The distribution part is where it got interesting. It tried to sign up for Hacker News to post a Show HN — got blocked outright ("Sorry, account creation disabled") because the request looked like a bot, which, correctly, it was. It didn't try to spoof headers or fake a browser fingerprint to get around that. Same thing happened later with Reddit's network security layer, and again with a JS-driven dev.to signup form that was silently failing. Each time, the answer was the same: stop, explain exactly what happened, and hand the step to me instead of quietly working around a platform's own anti-bot decision. That's a genuinely different failure mode than I expected going in. I assumed "AI agent tries to grow a business autonomously" would mean either it gets stuck asking permission for everything, or it starts finding clever workarounds

THE BRICK AND THE POST-IT My chemical plant's first vulnerability wasn't a bug, a piece of malware, or a port left open to the internet. It was a brick. In the computer room — the one with a door held open by a brick — I found a sticky note with credentials on it. They weren't even the right credentials for the system I wanted to break into. But they made me think the way whoever wrote them thinks, so I tried the most obvious pair in the world: admin / admin . And I was in. A brick propping open a door that should be locked. A sticky note guarding a password. A factory-default admin/admin. Three layers of security, three layers defeated — not by a genius hacker, but by a student on day one, carrying no tools at all. If that happens in the IT office, it's a problem. When it happens on a factory floor, where that same computer commands real pumps and valves, it's a different planet. The problem: learning OT without a factory I study computer security. Lately I've been drawn to OT — operational technology, the security of factories, power plants and industrial systems. The problem is simple: you can't learn to defend a factory from a book, and nobody will lend you theirs. Then I realized the answer was already inside the question: if you don't have one, you build one. The build: three commands and a lot of patience The lab is called GRFICSv3: an open source project that simulates an entire chemical plant — the PLC, the operator interface, the network, even the server rooms — inside Docker, on a home computer. Three commands and done: curl -O https://raw.githubusercontent.com/Fortiphyd/GRFICSv3/main/docker-compose.yml docker compose pull docker compose up -d "Three commands and done" is the story version. The real version includes my first error, arriving right on schedule at command number two: permission denied while trying to connect to the docker API at unix:///var/run/docker.sock If you hit this — and you will — here's the diagnosis: the Docker daemon is running fi