Google engineers just lost access to GitHub Copilot, and they're not happy about it. Having spent years watching corporate policies screw over developers, I can tell you exactly how this plays out: management thinks internal tools are better, developers know they're usually garbage, and everyone pretends it's fine until productivity numbers tank.
Research shows developers code way faster with AI assistants like Copilot. But corporate mandates often force engineers into inferior alternatives for "security" reasons that mostly boil down to executive paranoia.
Cider: Google's "Totally Better Than Copilot" Internal Tool
Google launched their internal coding AI and now they're forcing everyone to use it. Classic corporate move - build something internally, declare it better than the industry standard, then ban the thing everyone actually wants to use.
I've used plenty of internal tools at big tech companies. They're usually fine for simple stuff but fall apart when you need something complex. Cider claims it's trained on Google's internal codebase, which sounds great until you realize that means it's optimized for Google's specific weird patterns and architectural decisions. Last internal AI tool I used kept suggesting deprecated APIs from version 2.3 while our team was on 4.1 - spent three hours debugging why shit wouldn't compile.
Most users access it weekly, which Google spins as "strong adoption." But that's probably because managers are breathing down everyone's necks asking "are you using internal AI tools daily?" in performance reviews. GitHub's own research shows real productivity gains require voluntary adoption, not corporate mandates.
The Real Reason: Data Paranoia
Google's official line is about "security" and "competitive advantage," but the real reason is simpler: they're terrified of their code patterns leaking to Microsoft and OpenAI.
Fair enough - I wouldn't want my proprietary algorithms training my competitors' models either. But here's the thing: most day-to-day coding isn't top-secret architecture. It's fixing bugs, writing tests, and refactoring legacy bullshit.
Making engineers get manager approval to use Copilot for mundane tasks is like requiring a security clearance to use Stack Overflow.
30% AI-Generated Code Sounds Terrifying
Google's been throwing around claims that roughly a third of their code is AI-generated now. As someone who's debugged AI-generated code, that scares the shit out of me. Research shows concerns about the long-term effects of AI-generated code on maintainability.
AI is great at writing boilerplate and basic functions. It's terrible at understanding business logic, edge cases, and architectural decisions. That chunk of AI code is going to turn into a maintenance nightmare when some poor bastard has to debug shit they didn't write and barely understand. I spent four hours last month tracking down a race condition in AI-generated async code that looked perfect but failed under load in production.
The "productivity boost" claims are classic management bullshit. Sure, you write code faster. Then you spend way more time debugging the weird edge cases the AI didn't consider. Studies show the productivity gains often disappear when you account for maintenance costs.
Performance Reviews Now Include AI Usage
The most dystopian part? Google managers are now asking engineers to demonstrate daily AI usage in performance reviews. Your career advancement now depends on using the approved corporate AI tool, regardless of whether it actually helps you do your job better.
I've seen this movie before. Some engineer will get dinged on their performance review for "insufficient AI adoption" because they prefer to actually understand the code they're writing. Meanwhile, the engineer who rubber-stamps everything Cider suggests will get promoted despite introducing bugs that crash production.
Why Internal Tools Usually Suck
Having worked at companies with internal tool mandates, I can predict exactly how this goes:
Engineers complain the internal tool sucks for their specific use cases. Management says "give it time, it'll improve" while ignoring productivity metrics. Engineers waste time fighting inferior tools. Management doubles down because they've invested too much to admit failure. Good engineers leave for companies that don't micromanage their toolbox.
It's the same corporate playbook every time. Internal tools optimize for executive control, not getting shit done.
What This Means for Everyone Else
Google's move signals that big tech is done pretending external AI tools are partners. They're competitors now, and companies are choosing sides.
If you're a developer, this trend should worry you. Tool choice is one of the few areas where engineers still have autonomy. When companies start dictating which AI assistant you can use, what's next? Mandated text editors? Approved programming languages only?
The Bottom Line
Google engineers are about to learn what every corporate developer knows: internal tools are rarely better than external ones, but you use them anyway because you don't have a choice.
The real test will be in six months when productivity metrics tell the real story. My bet? Cider works fine for simple stuff but fails spectacularly for complex problems, and Google will quietly start approving external tool exceptions while claiming victory.