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The most common reasons Apple rejects your app

Getting a rejection email from App Review feels personal. It usually isn't. Apple runs the same review process against every submission, and most rejections trace back to a small number of guidelines that come up again and again. Knowing which ones, and what they actually mean, turns a vague rejection into a fixable checklist. How often this actually happens Apple's own 2024 App Store Transparency Report puts real numbers on this. Out of 7.77 million app submissions reviewed that year, 1.93 million were rejected, roughly 25%. Of those, 295,109 were fixed and approved on resubmission. Separately, 82,509 already-live apps were removed after the fact, most commonly for guideline or design violations (42,252), followed by fraud (38,315). Apple hasn't published a breakdown of rejections by specific guideline number, so treat any listicle claiming "62% of rejections are X" as unsourced. What Apple has said, in its own commentary alongside the report, is that the most common drivers, in order, are performance and bugs, legal issues, design problems, business-model (payment) violations, and safety risks. That ordering lines up with the specific guidelines below. The guidelines that actually catch people These are pulled directly from Apple's current App Store Review Guidelines, not paraphrased from a third party. Guideline 2.1, App Completeness. Covers crashes, obvious bugs, placeholder content, broken demo accounts, and non-functional in-app purchases. If a reviewer can't get past your login screen or your app crashes on launch, this is the line it gets cited under. It's the single most avoidable category, because it's the one you can actually test yourself before submitting. Guideline 4.2, Minimum Functionality. Your app has to be more than "a repackaged website." Apple wants "lasting entertainment value or adequate utility." A thin wrapper around a web view, with no native functionality added, gets flagged here. A sub-clause, 4.2.6, specifically targets apps built from c

2026-08-30 原文 →
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Archify (They've just got 4,239 Github stars on Aug 28, 2026)

Archify is taking GitHub by storm, hitting #1 on Trending and crossing 4,200+ stars in record time! If you use AI coding assistants like Cursor or Claude Code, Archify is an absolute game-changer. It allows your AI agent to automatically generate verifiable architecture, workflow, sequence, and data-flow diagrams as beautiful, self-contained HTML files (with dark/light themes and motion animations!). 🔗 Links & Resources: • Archify GitHub Repository: https://github.com/tt-a1i/archify • Try it yourself: npx skills add tt-a1i/archify -g 👇 What do you think of Archify? Are you going to use it for your next system design or PR review? Let me know in the comments! If you found this live demo helpful, please drop a LIKE and SUBSCRIBE for more cutting-edge AI developer tools. Archify #SoftwareArchitecture #Cursor #ClaudeCode #AI #SystemDesign #GitHubTrending #WebDev #OpenSource #DevTools

2026-08-30 原文 →
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GitHub Copilot Spending Limit: How to Set It, What It Caps

A GitHub Copilot spending limit is a monthly budget, set in billing settings, that caps metered AI credit consumption for an enterprise, an organization, a cost center, or a single user. Creating one takes about two minutes. Knowing what it stops takes longer, and the gap between those two things is where most surprise Copilot invoices live. Two facts account for nearly all of them. On enterprise, organization and cost center budgets, the setting that actually blocks usage is off by default, so a budget in its default state is an alert rather than a limit. And no budget of any kind caps seat cost, because seats are license-based rather than metered. A spending limit governs what happens after the included credit pool runs out, and nothing before it. How to set a GitHub Copilot spending limit Budgets live in the billing settings of the account that pays. Enterprise owners and billing managers can set every budget control, including enterprise, cost center and user-level budgets. Organization owners can set a budget for their own organization, and that budget can only restrict usage further below whatever an enterprise admin has already set. It cannot raise the ceiling. The mechanics are the same at every level. Choose the budget type, which determines the metered product being measured. Choose the scope, which determines whose usage counts against it. Enter a monthly amount. Then, if the option appears, enable Stop usage when budget limit is reached and switch on threshold alerts at 75, 90 and 100 percent. That single checkbox is the whole exercise. Skip it and you have built a notification. What a GitHub Copilot spending limit actually caps GitHub splits its products into license-based and metered. For license-based products, which include Copilot seats, setting a budget does not prevent usage above the amount. It only alerts. For metered products, which include Copilot AI credits, a budget can prevent usage once the threshold is reached. The consequence is worth st

2026-08-29 原文 →
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'Enshittified at a Surprising Clip': A Week of Hacker News on AI Coding Tools

Some fortnights the complaints about AI come from people who barely use it. This one they came from the people who use it most. Scroll Hacker News over the past week — the forum where developers argue about their tools in unusual detail — and the grievances about AI coding assistants weren’t existential. Nobody was worried about the robots waking up. They were worried about their bill, their UI, and the effort of reading what the model just wrote. Quotes sourced from: Hacker News. Every quote below was located at its comment permalink and reproduced verbatim; each is listed with its username, the platform, and the date in the Sources section. As always, we quote experiences, not verdicts — a forum comment is one practitioner’s account, often mid-argument, and we’ve framed them as exactly that. What makes this batch worth reading isn’t volume; it’s specificity. These are checkable complaints. “Enshittified at a surprising clip”: the dark-pattern gripe The sharpest thread of the fortnight was about Cursor, the AI code editor, and it wasn’t about the quality of its completions. It was about the way the product behaves around you. A user posting as jmuguy , on 20 August, laid out a bill of particulars that will sound familiar to anyone who’s watched a beloved tool curdle: “Cursor isn’t covering itself in glory regardless. The flagship app is getting enshittified at a surprising clip. It constantly pops up and interrupts your work pushing new features, changes your model to whatever the latest Grok is without prompting, has this mystery meat UI that is constantly changing, pushes cloud agents in ways that are definitely designed to trick you. We’re actively looking at alternatives, I wouldn’t touch anything this company produces from here on out.” Set aside the verdict at the end — that’s one person’s conclusion, not ours — and look at the specifics, because they’re the kind you can check: interruptions pushing new features, a model silently swapped to Grok, a UI that ke

2026-08-29 原文 →
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