标签：#Product

Test firmware on a virtual chip with no hardware needed Discussion | Link

2K+ free hand-drawn illustrations for your projects, CC0 Discussion | Link

The worst test suite I ever inherited had 400 tests, and I trusted about six of them. The rest were either testing implementation details nobody cared about, duplicating each other, or so tightly coupled to internal function names that a harmless refactor broke thirty tests for no real reason. Reading that codebase taught me more about what not to do than any greenfield project ever has. So when you're starting from zero, the goal isn't "write a lot of tests fast." It's building a suite you'll still trust a year from now. If you're new to this, getting the software testing basics right early matters more than covering everything - learning how to build a first test suite from scratch teaches you what to prioritize in a way that inheriting someone else's bloated suite never will. Here's roughly how I'd approach it. Start with what would actually hurt if it broke Before writing a single test, list the handful of things that would be genuinely bad if they silently broke - checkout completing, auth working, the core thing your product does actually happening. Not every function, not every branch. Just the stuff where a silent failure costs you money, users, or trust. This list is usually shorter than people expect. Five to ten flows for most early-stage products. That's your actual test suite's job in the first few months, not "100% coverage." Unit tests for logic, not for plumbing Unit tests are for things with actual decision-making in them - pricing calculations, validation rules, state transitions, anything where "given this input, is the output correct" is a real question with a wrong answer possible. They're fast, they're cheap, and they should make up the bulk of your suite. Skip unit-testing pure plumbing: a function that just calls another function and returns its result doesn't need its own test. That's the kind of test that pads a coverage number without catching anything real, and it's exactly the kind of test that made that 400-test suite so hard to trust.

Grok Bot is your team of always-on agents Discussion | Link

YouArt AI Feature Launch Video Generator Discussion | Link

OpenRouter for tools with 2,600 APIs, 0% markup Discussion | Link

Run and train AI models locally on your desktop Discussion | Link

Writing Takes 40 Minutes, Publishing Takes 30 — How I Solved It Last Wednesday, 22:00. I just finished writing a tutorial on Python async programming — 2200 words, clean Markdown, syntax-highlighted code blocks. 22:03, open Juejin. Paste title. Paste content. Code highlighting gone. Fix manually. Pick tags. Publish. 22:08, open Zhihu. Paste title. Paste content. The Draft.js editor merged async def into asyncdef . Fix line by line. Publish. 22:15, open CSDN. Paste title. Content looks fine. But the category dropdown has 50 options and "Python" is buried. Publish. 22:20, open Cnblogs. Must add [Markdown] tag to categories or the whole article renders as garbled HTML. Publish. 22:25, open SegmentFault. Search tags for "Python async" — zero results. Type manually. Publish. 22:30, open Dev.to. Translate title. Translate content. Publish. Forty minutes to write. Thirty minutes to publish. 22:35, all done. But the next morning, I wanted to check stats — another round of logging into each platform's dashboard one by one. I'm Not Alone Searching forums and social platforms, I found many developers share this pain: "Every time I publish an article, I open 7-8 tabs, copy-paste 7-8 times, fix formatting 7-8 times. The joy of writing gets killed by the drudgery of publishing." "I usually only publish on one platform now. It's just too much work to do more. But then search engine exposure suffers." Why "Just Copy-Paste" Doesn't Work Each platform has a different editor: Platform Editor Markdown Handling Juejin Custom Markdown Good, but code highlighting sometimes breaks Zhihu Draft.js rich text No Markdown support, eats line breaks CSDN Dual-mode Mode switching corrupts formatting Cnblogs TinyMCE Must add [Markdown] tag or disaster SegmentFault Markdown Okay, but tag system is painful Dev.to Markdown Best experience, but English-only audience The same Markdown renders differently everywhere. Copy-paste doesn't solve it. What I Built I spent two weeks of evenings building PolyPos

A neutral control plane for enterprise AI agents Discussion | Link

why use many token when few do trick Discussion | Link

The open-source shared folder for your team's AI agents Discussion | Link

AGENTS.md vs CLAUDE.md: Where Agent Context Actually Lives If you have opened three different repos this month and found three different context files (AGENTS.md in one, CLAUDE.md in another, both in a third, out of sync), you are not imagining the mess. AGENTS.md is now an open, vendor neutral standard that most major coding agents read, but CLAUDE.md has not gone away, and knowing which file wins where saves you from an agent quietly following stale instructions. What AGENTS.md actually is AGENTS.md started as a proposal from Sourcegraph's Amp team to fix a specific problem: every coding agent invented its own context file, so teams ended up maintaining CLAUDE.md, .cursorrules, .windsurfrules, and whatever else, all describing the same project. OpenAI and Google backed the standard, and it has since moved under the Linux Foundation's Agentic AI Foundation. Guides tracking adoption report 28+ supporting tools and more than 60,000 open source repos containing the file (secondary source, treat the exact counts as approximate, not audited). The pitch is simple: one Markdown file, one format, every agent reads the same source of truth instead of you hand syncing five files that drift within a week. Which tools actually read it This is the part that matters when you are deciding whether to migrate. Tools with native AGENTS.md support include: GitHub Copilot coding agent Cursor Amp Factory RooCode Zed Warp Notice what is not confirmed on that list. Reports that Claude Code reads AGENTS.md natively circulate in comparison guides, but I could not verify this against Anthropic's own changelog, so I am stating it qualitatively here rather than as fact: treat it as unconfirmed until you see it in Anthropic's own docs, and keep CLAUDE.md in place as your safety net if you rely on Claude Code specifically. AGENTS.md vs CLAUDE.md vs the well known directory Three layers get conflated constantly, and they solve different problems. Layer What it is Scope AGENTS.md Vendor neutral p

An independent receipt for every LLM API call Discussion | Link

The agentic interface Discussion | Link

Run a fleet of AI agents across your machines Discussion | Link

Turn Anki flashcards into real English conversations Discussion | Link

Live research context for ChatGPT and Claude Discussion | Link

The AI that refuses to let you drop the ball Discussion | Link

Where humans and agents come to work. Discussion | Link

The PC gaming world has tried to move on from bulky, heavier mice, but the Naga V3 Pro proves that it still has its place.