Vin Patel is an AI technologist and published author with 25+ years of experience. He is the creator of Manuscript (open-source AI content detection), AEORank (AI Engine Optimization), and the Bhagavad Gita App. His work has been archived by the British Library and cited by UKCERT.

AEORank is an open-source CLI tool that scans any website across 12 AI visibility dimensions, scores it from 0-100, and generates 8 deployment-ready files that improve discoverability by AI engines like ChatGPT, Perplexity, and Claude. Free at aeorank.dev.

What is the Bhagavad Gita App?

A verse-by-verse platform at bhagavad.net presenting all 700 Gita verses through 8 philosophical traditions with multi-tradition synthesis, life applications across 4 pillars, and 5,600+ searchable life questions. Open source and MIT licensed.

Manuscript is the only open-source AI content detector that runs 100% on your infrastructure. It detects AI-generated text, images, audio, and video with zero external API calls. Built in Go, self-hosted via Docker. Visit manuscript.dev.

How can I work with Vin Patel?

Vin is available for speaking engagements, podcast interviews, and consulting on AI strategy. He also runs the IdeaForge Workshop, a 4-day intensive for building AI products. Contact vinpatel.pro@gmail.com or visit vinpatel.com/speaking.

Claude's February Updates Break Complex Engineering Workflows

The signal: Developers report Claude’s February updates significantly degraded complex engineering tasks, with many switching to alternative tools. Over 1000 comments confirm widespread impact.

Why it matters: This exposes the fragility of AI-dependent workflows. Anthropic likely optimized for benchmarks or safety and broke practical coding capabilities. These models are black boxes — when they break, we can’t fix them ourselves.

The pattern I’m watching: Classic model regression playing out in real-time. GPT-4 had similar episodes. GitHub Copilot too. Vendor dependency in AI tooling is a real business risk.

What I’d do with this: Don’t single-vendor your AI tooling. Keep multiple tools in your stack as backups. Document which tools work best for your specific use cases so you can pivot fast. This is a good reminder to maintain your core coding skills — AI should augment, not replace.