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Temporary storage to share files securely Discussion | Link

It doesn't even have to be a big dramatic failures, more the small moments where something clicked and you went from trusting the output by default to double checking everything. For me it was watching an agent confidently rename a function across twelve files, then leave the original function untouched in a thirteenth file it apparently didn't search, with zero indication anything had been missed. It wasn't even a hard case, the file just wasn't in the directory it happened to grep first. What was your moment? And did it actually change your workflow afterward , or did the trust creep back in after a week like it always seems to for me?

Run agent apps inside your Claude or sell your own Discussion | Link

AI-native office leasing brokerage Discussion | Link

I Built Flowstate Because We Somehow Made Productivity More Complicated Than The Actual Work Live: https://flowstate.chromitedev.xyz/ GitHub: https://github.com/ChromiteDev/flowstate We have a strange problem. Humans built some of the most advanced technology in history. We created: Computers that fit in our pockets Instant communication across the planet Machines that explore space Software that can do incredible things And somehow... We still struggle with: "What should I actually focus on today?" That is the problem I wanted to solve. So I built Flowstate . The productivity paradox We have never had more productivity tools. Seriously. Think about it. There are apps for: Tasks Notes Calendars Habits Goals Projects Time tracking Team management There is probably an app to help you organize the apps that organize your life. At some point we stopped being productive and started managing productivity. The funniest part? Sometimes creating the perfect productivity system becomes the biggest productivity project. You spend two hours making a beautiful workspace... Then realize: You have done absolutely nothing. A masterpiece of organization. Zero progress. The moment I realized something was wrong I noticed a pattern. People were not struggling because they were lazy. They were struggling because their attention was constantly being divided. Every day we fight: Notifications Endless information Too many choices Too many responsibilities Too many things competing for our attention The internet gave us unlimited access to information. But our attention? That is still limited. The question behind Flowstate I kept coming back to one question: "What actually deserves my attention right now?" Not: "What are all the possible things I could do?" Not: "How can I create the most complicated workflow imaginable?" Not: "Should I reorganize my folders for the fifth time?" (We have all been there.) The goal was simple: Create a tool that helps people find clarity. Introducing Flowsta

The AI Recruiting Coordinator Discussion | Link

We've all had the same experience. You ask your coding agent to integrate with a new platform. It confidently writes code. It references endpoints that don't exist anymore. It misses required headers. It mixes API versions. It hallucinates authentication flows. None of this is surprising. Large language models don't "know" an API. They know about an API from their training data. Even when you hand them documentation, they're still trying to reconstruct a mental model from hundreds or thousands of pages of text. The problem isn't writing code. It's building context. Understanding an API is still mostly manual Every integration starts the same way. Read the authentication docs. Figure out the important entities. Learn the object relationships. Understand the common workflows. Find the endpoints that matter. Jump between documentation tabs for an hour. Only then do you actually start building. Ironically, AI made writing code dramatically faster while leaving this entire process mostly unchanged. Documentation wasn't designed for AI Most documentation is optimized for humans. OpenAPI specifications are optimized for machines. Neither tells the complete story on its own. The spec explains what exists. The documentation explains why it exists. Neither builds a coherent mental model. I wanted a better starting point That's why I built Scout. Scout takes an OpenAPI specification and the accompanying documentation, then synthesizes them into a grounded understanding of the platform. Instead of asking: "Can Claude figure this out?" The workflow becomes: import the API crawl the documentation build an understanding ask questions against grounded context generate integration code expose the same understanding to coding agents through MCP Everything runs locally. No hosted backend. No accounts. No telemetry. The interesting part isn't the AI The AI chat isn't the product. The generated code isn't the product. The MCP server isn't even the product. The product is the context tho

Give Claude Code missions to spawn a team of agents Discussion | Link

I run a consumer product company by myself. Physical inventory, two storefronts, multiple marketplaces, subscription billing, bookkeeping, tax filings, government paperwork, content in two languages, and a codebase that ships to production most weeks. Headcount: one. Not "one plus a virtual assistant." One. Three years ago this was not possible. It is also not possible today by keeping a chat window open and asking it questions. The thing that changed is not that models got smarter in the abstract. The thing that changed is that agents can now operate software the way an employee does : click through admin dashboards, fill in government forms, read email, write and deploy code, remember what happened last Tuesday, and run on a schedule without being asked. Once that is true, most of what a small company's staff does becomes a workflow you can write down, hand to an agent, and audit weekly instead of doing daily. Everything I run sits on five primitives. Tool names will churn every six months. These won't. 1. A browser-operating agent An agent that drives a real browser session with my real logins: seller dashboards, banking portals, government sites, ad platforms, email. This is the highest-leverage primitive, and it is the one most people skip. The reason is uncomfortable: roughly 90% of small-business operations live behind a login wall with no usable API. Your marketplace seller console. Your payment provider's merchant dashboard. Your country's tax portal. The grant program that still ships application forms as attachments. If your automation strategy requires an official API for everything, you will automate the 10% that already had one, and you will still be doing the other 90% by hand at 11pm. The browser agent is my hands. It logs in, navigates, reads what's on screen, fills forms, downloads documents, and reports what it found. 2. A coding agent An agent that reads my repositories, writes changes, opens a review pass, and deploys. I treat it exactly like a

This series follows a fictional conversation between an experienced engineer and his nephew. Every episode explores one stage of how software moves from an idea to production. 👦 Nephew: Uncle, requirements are clear. I checked the codebase — there's already a FavoritesService I can extend for Wishlist. Now can I open VS Code? 👨‍🦳 Uncle: Almost. Tell me — what do you think HLD even is ? You've heard the term in every interview. What do you think it actually means? 👦 Nephew: Some kind of... diagram? Boxes connected with lines, before you start coding? 👨‍🦳 Uncle: That's what it looks like. That's not what it's for . Let me ask differently. Why do you think experienced engineers insist on drawing this before touching code, when they could just start building? 👦 Nephew: ...to plan the work? 👨‍🦳 Uncle: Closer, but still not it. Here's the real answer: HLD exists to decide, in advance, where the walls go — so that six months from now, when someone adds a new feature, they know exactly which room to build it in, without knocking down a wall that was holding up the ceiling. 👦 Nephew: That's a strange way to describe a diagram. 👨‍🦳 Uncle: Then let me show you, instead of describing it. That's the only way this actually lands. What Talks to What 👨‍🦳 Uncle: Suppose we're building this at Flipkart. Not a college project — a company with hundreds of live services, where breaking one thing can affect ten others you've never even heard of. Here's the simplest picture for Wishlist. Frontend ↓ Wishlist API ↓ Wishlist Service ↓ Database 👦 Nephew: That's it? Four boxes? 👨‍🦳 Uncle: That's it. HLD answers exactly one question, and nothing more — what talks to what. Not how the button looks. Not what fields the database table has. Just: which component calls which, and in what direction. 👦 Nephew: Then why does everyone treat it like it's such a big deal? This took ten seconds to draw. 👨‍🦳 Uncle: Because the value isn't in the ten seconds you spend drawing it today. The value is in what i

Did you know that Kiro doesn't just have a Spec-Driven Development (SDD) flow, but also a bug fix workflow that helps you resolve one issue at a time? That's one of seven features worth knowing about. If you're completely new to Kiro, it's an agentic harness for the CLI, web, IDE, iOS, and more. It helps teams and individuals do their best work while coding. I've been using it since it launched in July last year, and I keep finding features I didn't know were there. (Full disclosure: I'm a Developer Advocate at AWS, and Kiro is a part of AWS. I use it every day, and I'll be forthcoming about the parts that are still preview or experimental.) Heads up: Kiro ships fast. I've flagged the version-sensitive bits of these features inline. Check the docs if something looks different in your build. 1. Stop approving every single command After talking to a lot of people about Kiro, one of the main pieces of feedback I get is on approving commands. When Kiro asks permission to run a shell command, the default reaction is to hit yes and move on. Then it asks again for the next git command. And the next one. Press Tab instead in the CLI. This allows you to edit it and put the exact permissions you'd like. For example you can be pickier on the trust tiers: git pull --rebase # this exact command git pull * # git pull with any arguments git * # anything git * # the entire shell tool Whatever you pick persists for the session and gets stored as a regex in your agent's allowedCommands . There's also /tools trust-all , which trusts everything. It's the documented replacement for the old /acceptall , and the security docs are blunt about it: don't use it in production or with sensitive data, and you're responsible for whatever it does. One version note: on CLI v3 this moves to a permissions.yaml file, so the agent JSON advice above is v2. More on v3 in a minute. Full details: tool permissions 2. The # menu is bigger than #file in the IDE Type # in the IDE chat and you get a list of co

Your voice-first AI assistant for macOS Discussion | Link

A little cat who loves being read to Discussion | Link

A workspace & 2nd brain for you, your agent, and your team Discussion | Link

Why Claude Code runs on Bun: runtime tradeoffs in TypeScript CLI tooling Anthropic recently shipped Claude Code — their agentic CLI coding assistant — on Bun instead of Node.js. For most product announcements, the runtime choice would be a footnote. Here it's worth unpacking, because the tradeoffs Anthropic navigated are exactly the ones you hit when building or evaluating TypeScript-heavy developer tooling: startup latency, bundling strategy, native module compatibility, and what "good enough" dependency management actually looks like in 2025. This isn't a Bun vs. Node benchmarking post. It's an examination of why the decision makes sense for a CLI tool specifically, what it signals about the broader ecosystem, and where the tradeoffs still bite you. Why runtime choice matters more for CLIs than for servers For a long-running server process, Node.js startup cost of 50–150ms is irrelevant — you pay it once. For a CLI invoked dozens of times per development session, cold-start latency is a first-class UX concern. Bun's startup time is consistently in the 5–15ms range for a simple script. Node.js lands closer to 50–80ms before your first line of application code runs. That delta is imperceptible in a single invocation. Run a CLI 30 times in a session and you've saved a couple of seconds — more importantly, you've removed the subjective sense of lag that makes a tool feel heavy. This is the same reason Deno has gained traction in scripting contexts despite losing the server-side battle to Node. Fast startup is a feature, and for AI-assisted tooling where the human is waiting in a tight feedback loop, it matters. Bun's bundler as a distribution primitive Bun ships a first-party bundler. For a CLI, this is significant. The standard Node.js distribution story for a TypeScript CLI involves: Compile TypeScript with tsc or esbuild Bundle with esbuild or rollup to collapse the dependency graph Either ship node_modules (large, fragile) or use a tool like pkg or nexe to produce

Lightweight, powerful, and generally inexpensive, the handheld vacuum is the perfect household helper.

A svelte smart ring can track important activity, sleep, and health metrics. Plus, unlike most smartwatches, it doesn’t need to be charged every day.

Self-hosted radio with an AI DJ and one shared stream Discussion | Link

I tested the Soundcore Nebula P1i, an affordable projector, to see if it could overcome the typical drawbacks that most budget projectors suffer from.

Free Online PDF Converter – Word, HTML, Image & More Tools Free online PDF converter with complete privacy protection. Merge, split, compress, sign, and convert PDFs directly in your browser — plus a free age calculator and scientific calculator. No uploads, no data storage. onepagepdfconverter.com I built One Page PDF Converter (onepagepdfconverter.com) — a set of 20+ PDF tools (merge, split, compress, sign, convert to/from Word/Excel/PowerPoint/images, etc.) plus a couple of everyday calculators, all running entirely client-side in the browser. There's no backend processing your files: no upload, no storage, no server round-trip. Everything happens locally via JS, so your documents never leave your device. That's the whole pitch — it's the same reason I built it, since most PDF tools online quietly funnel your files through a server you have no visibility into. All 20+ tools are free with no sign-up. Today I'm adding a small premium option: batch processing, for ₹9.99 per batch (~$0.10 USD), one-time — no subscription. Run a tool across multiple files in one go instead of one at a time. Everything else on the site stays free and unlimited. Tech-wise it's a single HTML file backed by client-side JS libraries — no framework, no build step. It's a PWA, so it installs and works offline once loaded. Would love feedback — especially on the privacy angle, the batch pricing, or tools you think are missing. Free Online PDF Converter – Word, HTML, Image & More Tools Free online PDF converter with complete privacy protection. Merge, split, compress, sign, and convert PDFs directly in your browser — plus a free age calculator and scientific calculator. No uploads, no data storage. onepagepdfconverter.com