GitHub Copilot Just Invented Loot Boxes for Coding

Remember when GitHub Copilot was simple?

You paid your monthly subscription.
You wrote code.
The AI occasionally hallucinated.
Everyone moved on with their lives.

Now I need a finance degree to understand whether asking Claude to rename a variable will cost me three credits, thirty credits, or my firstborn child.

GitHub's new AI Credits system officially landed this month, replacing the old request-based model with token-based billing. On paper, it sounds reasonable:

"Pay for what you use."

In reality, it feels more like:

"Good luck figuring out what you used."

Developers across Reddit are posting screenshots showing massive chunks of their monthly allowance disappearing after only a handful of agent requests, code reviews, or debugging sessions.

The funniest part?

For the last two years, AI companies trained us to write better prompts.

"Give more context."
"Provide the entire codebase."
"Let the agent reason deeply."
"Use autonomous workflows."

Now the bill arrives and suddenly every extra token feels like ordering guacamole at the airport.

We're being financially punished for following the best practices they taught us.

The old Copilot experience was predictable:

• Pay monthly
• Use it constantly
• Never think about accounting

The new experience:

• Open billing dashboard
• Watch credits evaporate
• Start calculating token economics
• Wonder if asking a follow-up question is worth it

Some developers have already started moving heavy reasoning work back to ChatGPT, Claude, Cursor, Cline, or local models while using Copilot only for IDE convenience.

And honestly?

That's probably the unintended consequence.

GitHub spent years convincing us that AI should be embedded into every step of software development.

Now they're teaching us to ration prompts like we're living through the Great Token Depression.

The most ironic outcome is that Copilot might accidentally make developers better engineers.

Because before every prompt we'll ask:

"Do I really need AI for this?"

And for the first time since 2023, the answer might be:

"No, I can probably write the damn function myself."