Top AI Product

If you’re building anything with LLMs right now, you probably know the pain. You’ve got OpenAI keys, Anthropic keys, Google keys, maybe DeepSeek too — and suddenly you’re managing a mess of API endpoints, juggling rate limits, and praying that one provider doesn’t go down at 2 AM on a Friday. That’s exactly the problem… Continue reading

If you’ve spent any time with AI coding agents lately — Claude Code, Codex, Cursor, whatever your flavor — you know the drill. You kick off a task, tab over to Slack or Reddit, and then completely forget your agent finished three minutes ago. Or worse, it’s been sitting there waiting for permission while you’re… Continue reading

So [nineninesix.ai](https://www.nineninesix.ai/) quietly released Kani-TTS-2 today, and honestly, I think this one deserves way more attention than it’s getting. It’s a 400M parameter open-source text-to-speech model that runs on as little as 3GB of VRAM. That means your old RTX 3060 sitting in a drawer? Yeah, that works. No cloud GPU rental needed, no waiting… Continue reading

If you’ve been anywhere near the AI coding space in the past year, you’ve probably bumped into [Cline](https://github.com/cline/cline). The open-source VS Code extension has quietly built up a massive following — over 5 million developers, 57K+ GitHub stars, and the title of fastest-growing AI open-source project by contributors on GitHub Octoverse. So when the team… Continue reading

I’ve been keeping an eye on the local-first AI assistant space for a while, and most projects in this area feel like duct-taped Python scripts held together by prayers and pip install. So when [Moltis](https://www.moltis.org/) popped up on [Hacker News](https://news.ycombinator.com/item?id=46993587) yesterday and quickly climbed to 118 points, I had to look into it. Here’s the… Continue reading

If you’ve been building anything with LLMs in React, you’ve probably hit the same wall I did — the AI spits out a block of text, and then you’re stuck figuring out how to turn that into something your users can actually interact with. That’s exactly the problem [Tambo](https://tambo.co/) solves, and honestly, it’s one of… Continue reading

So, MiniMax quietly released [M2.5](https://www.minimax.io/models/text) on February 12th, and honestly, the numbers are kind of absurd. We’re talking about an open-weight model that scores 80.2% on SWE-Bench Verified — just 0.6 points behind Claude Opus 4.6. Let that sink in for a second. An open model is now essentially neck-and-neck with the best proprietary coding… Continue reading

I stumbled across [Migma AI](https://migma.ai/) while browsing Product Hunt the other day, and honestly, it stopped me mid-scroll. The tagline “Lovable for emails” is bold, but after poking around, I kind of get it. Just like Lovable lets you describe what you want and spits out a working website, Migma does the same thing for… Continue reading

If you’ve spent any time shipping AI-generated code this year, you know the drill. Copilot or Claude writes something that looks perfectly reasonable, the PR gets merged, and three days later you find out that “null-safe” function was anything but. The AI *said* it handled edge cases. It lied. Or rather, it hallucinated — and… Continue reading

I’ve been testing a bunch of AI coding tools lately, and one thing keeps bugging me — how do you actually know which model writes better code? Benchmarks are everywhere, but most of them feel disconnected from real work. That’s where [Code Arena](https://arena.ai/?chat-modality=code) comes in, and honestly, it’s the closest thing I’ve found to an… Continue reading