Cursor OpenAI Models Ending: What Developers Need to Do Before November 12, 2026 ``` AI Developer Update Cursor OpenAI Models Ending: What Developers Need to Do Before November 12, 2026 If you use OpenAI models inside Cursor, there is a change you should probably start preparing for now. OpenAI says it intends to wind down its contract supplying OpenAI models to Cursor, with November 12, 2026 proposed as the transition date. That headline can sound worse than it actually is. Cursor itself is not shutting down. The change concerns the agreement under which OpenAI models are supplied directly through Cursor. For developers, the practical question is much simpler: Will my current workflow still work, and what should I change if it does not? The good news is that OpenAI has already published guidance describing several ways devel...

10 Business Ideas That Somehow Don't Exist Yet (And Are Stupidly Easy to Build)   Every few months I go hunting for gaps — problems people complain about but nobody's actually solved with a simple product. Most "startup idea" lists online are either too vague ("build an AI tool for X") or too ambitious (requiring a team of ten and a Series A before you ship anything). This list is neither. Every idea here can be built by one person, with an unglamorous tech stack, in weeks — not months. No proprietary models, no massive infrastructure, no permission needed. 1. A Single Dashboard for Cancelling Subscriptions Everyone has 8-12 recurring subscriptions scattered across email inboxes. Nobody has one place that tracks them, reminds you before renewal, and gives you the direct cancellation link for each service. Why it's easy: No AI needed. A database of cancellation URLs, a simple form to log your subscriptions, and email reminders. A weekend project wit...

Why Your AI Coding Assistant Broke Other Files (And How to Fix It) Your AI Coding Agent Says the Bug Is Fixed — Here's What It Broke While You Weren't Looking Quick answer: Yes — an AI coding agent can genuinely remove the bug you reported while changing behaviour somewhere else in the codebase, and this isn't a rare edge case. The most detailed public measurement of it comes from a March 2026 study that ran a coding agent against 100 real GitHub issues from SWE-bench Verified and found it broke, on average, 6.5 previously-passing tests for every patch it generated. A separate review by METR found that roughly half of AI-written pull requests that pass a benchmark's automated tests would not actually be merged by the maintainers of the project. The tests passing and the bug being "fixed" are not the same claim as the codebase being safe to ship. Treat the agent's output as a draft patch, not a finished one: read the diff, understand every f...