GitHub Copilot premium requests just changed in a way you can’t ignore. As of December 2, 2025, GitHub started removing legacy account-level $0 budgets for enterprise and team accounts created before August 22, 2025. That shifts control from a hard $0 cap to a policy-based model that either allows or blocks paid overages. If you rely on Copilot at scale, you need to review your settings now so you don’t accidentally throttle your engineers or swallow surprise bills.
Here’s the thing: “premium requests” aren’t your daily completions or baseline chat. They’re metered calls to advanced models and features tied to new SKUs (like the coding agent or Spark) that sit on top of your monthly allowance. Starting June 18, 2025, GitHub enforced monthly allowances across paid plans. December 2 is the cleanup date that removes the old, confusing $0 budget crutch for many orgs. The right move this week is to set your policy intentionally, set budgets at the right scope, and align dev workflow with finance guardrails.
What exactly changed for GitHub Copilot premium requests?
Two dates matter for teams in the United States (and everywhere else):
• June 18, 2025 — monthly premium request allowances were enforced across paid Copilot plans (Pro, Pro+, Business, Enterprise). Every user gets a monthly pool; premium features draw down from it. Counters reset on the first of each month.
• December 2, 2025 — GitHub began removing legacy $0 Copilot premium request budgets from enterprise and team accounts created before August 22, 2025. You now govern overages via a policy toggle (Enabled/Disabled). If you do nothing and your policy is Enabled, users can consume beyond their allowance and you’ll be billed per premium request (bounded by any budgets you configure). If your policy is Disabled, premium features stop when a user hits the allowance.
Individuals (Pro/Pro+) keep their default $0 budgets. Enterprise/Team is where the removal hits.
What counts as a premium request?
Premium requests are metered calls to certain advanced AI models and features outside the unlimited baseline. They’re grouped under dedicated SKUs so you can analyze and control spend per tool. Today the big drivers are the coding agent and Spark (GitHub’s faster copilot for quick tasks). Model choice and feature usage determine how fast a developer burns through the allowance and any overage budget you set.
What doesn’t count? Your bread-and-butter Autocomplete and the base agent/chat interactions that GitHub classifies as unlimited for paid plans, subject to rate limits. If developers say “Copilot stopped working,” nine times out of ten they’ve hit the premium allowance for the month or your policy is blocking overages.
Who’s affected—and how?
• Enterprise and Team accounts created before August 22, 2025: your old $0 budgets are being removed starting December 2. Your policy now decides whether paid overage is allowed.
• Newer enterprise accounts: you’ve already been on the policy-based model; you still need budgets and reports to control spend.
• Individuals (Pro/Pro+): default $0 budgets remain; no change in control, but the monthly allowance enforcement continues.
Symptoms you’ll see if you get this wrong
• Developers hit the allowance mid-month and premium features silently stop—tickets pile up with “Copilot agent unresponsive.”
• Finance sees an unexpected spike because the policy was Enabled and no budget cap existed at the org, cost center, or SKU level.
• Team leads can’t tell who’s burning through requests—no routine usage reports, no targets, no coaching.
The 30‑minute Copilot Billing Hardening playbook
Block a calendar slot today. You can do this in under 30 minutes and save days of churn.
1) Decide your stance: allow or block overages
In Copilot settings, find the premium request paid usage policy. Set it to Disabled if you want a hard stop after allowances—ideal while you baseline usage. Set to Enabled if uninterrupted access matters and you have budgets to cap exposure. Most enterprises start Disabled, gather two weeks of data, then move to Enabled with caps.
2) Set budgets where they actually help
Use a layered approach:
• Organization or enterprise budget: a monthly ceiling that protects the company.
• Cost center budgets: map to departments or product lines if you already tag spend that way.
• SKU-level budgets: apply different caps to the coding agent versus Spark. This prevents one feature from starving the rest.
Tip: if your policy is Enabled but you set the org budget to $0, you’ll recreate the old behavior and block overages anyway—hard to diagnose later. Choose an explicit number or disable overages cleanly.
3) Pull reports before you tweak allowances
Download the usage report. Identify who regularly exhausts allowances and which SKUs drive it. Don’t jump straight to bigger budgets; coach workflows first. Heavy usage can mean genuine leverage—or that a developer is looping the agent for tasks the IDE or a script could do faster.
4) Right-size allowances by role
Start with product engineering teams that live in the coding agent all day. Leave platform, data, and security teams on the default allowance unless they demonstrate sustained need. A 10–20% allowance bump for high-impact squads often unblocks work without exploding cost.
5) Add an engineering “spend guardrail” to your team charter
Set expectations in writing:
• Use the agent for exploratory spikes, refactors, and boilerplate; avoid burning premium requests on trivial renames or dead-end experiments.
• Prefer repository-level context and smaller prompts. Long, open-ended queries can chew through allowance fast with weaker outcomes.
• When the agent stalls, don’t spam retries—file a ticket with the prompt and repo so we can tune patterns.
6) Instrument the developer experience
Ask teams to keep the Copilot status indicator visible in the IDE. Pair that with a weekly usage digest to the team Slack channel: top 5 users by premium requests, top SKUs, and one “win story” that justifies the spend. Visibility beats after-the-fact finance escalations.
What about Copilot Enterprise—do we need it to manage this?
No. Policy toggles, budgets, and reports are available at org/enterprise scope without forcing an Enterprise plan upgrade for every seat. Enterprise brings governance and features many companies want anyway, but the Dec 2 change is neutral on upgrading. Make your plan decision based on security requirements and feature fit, not just billing control.
Will developers be blocked if we disable overages?
Only premium features stop when a user exhausts their allowance; completions and baseline chat still work (rate limits apply). For high-velocity teams, a middle-ground is setting a modest cap (for example, $10–$20 per user per month of premium overage) and revisiting after two billing cycles.
How do counters reset—and can we forecast spend?
Counters reset on the first day of each month, local to GitHub’s billing period. For forecasting, multiply your active seat count by average premium requests per role, then add a 10% contingency for spikes in releases or incident weeks. Compare that to your org budget and adjust caps before month-end to avoid last‑day surprises.
A practical mapping from engineering needs to budget control
Here’s a simple framework I use with clients:
• Strategic squads (checkout, onboarding, infra) — policy Enabled, SKU-level budgets with a 2–3x allowance buffer, monthly review with cost per deploy metric.
• Feature squads — policy Enabled with a smaller buffer, weekly digest; cap Spark tighter than the coding agent.
• Shared services and enablement — policy Disabled initially; gather two weeks of data; open the tap gradually if needed.
• Contractors — require budgets at the cost center level; rotate reports to the vendor manager.
“Why did our bill jump?” A plausible scenario
Picture a company that left the policy Enabled when the $0 budget vanished on December 2. One high-profile team ran a migration and leaned on the coding agent for bulk code edits and test generation. The org had no SKU-level budget, so the agent burned most of the shared pool before other teams started their day. Spend spiked, engineers on other teams lost access to premium features, and leadership assumed Copilot was “down.” The fix wasn’t to turn Copilot off; it was to bound the agent with its own budget and publish a short, clear usage playbook.
People also ask
Can we cap premium requests per team?
Yes—use cost center budgets tied to your identity groups. It takes an extra step to map teams to cost centers, but once you do, you can allocate separate ceilings and avoid cross-team cannibalization.
Do dedicated SKUs make this harder?
They make it easier once you set them up. Each AI tool shows up with its own usage line, so you can tune caps where value is strongest instead of swinging a single blunt org-wide budget.
What if we ignore all this?
You’ll either block premium features exactly when engineers need them, or you’ll pay for usage you can’t explain. Neither outcome survives the next QBR.
Governance that doesn’t suffocate delivery
The goal isn’t to ration AI; it’s to buy impact with intent. A lightweight workflow works best: policy decision, budgets, a weekly 5‑minute readout, and one coaching note in each retro. If you’re early in your rollout, keep the policy Disabled for two weeks while you baseline. If you’ve got a year of Copilot under your belt, consider policy Enabled with tight SKU caps and a fast appeal path for spikes.
What to do next (today)
• Open your Copilot policy. Decide Enabled vs Disabled and write it down.
• Create three budgets: enterprise ceiling, two cost center budgets, and a coding‑agent SKU cap.
• Download usage reports and post a snapshot to Slack with an owner for next steps.
• Add a one-paragraph “spend guardrail” to your team charter and pin it in the repo.
• Schedule a 15‑minute end-of-month review to adjust caps before counters reset.
Need a second set of eyes?
If you want help modeling allowances, mapping teams to cost centers, or designing a developer-friendly policy, our team does this every week. See how we structure AI rollouts on our services page, and browse related pieces like the Dec 2 rulebook for Copilot premium requests and our quick update on Dec 2 being live. If you’re comparing AI platform investments, our take on AWS’s model customization push in Nova Forge going live offers a complementary angle on build vs buy. When you’re ready, get in touch and we’ll review your setup together.
Final word
December 2 isn’t a scary change—it’s a nudge to be deliberate. Set a policy on GitHub Copilot premium requests that matches your risk tolerance, give your best teams enough headroom to ship, and make budgets visible so finance sees the ROI instead of a mystery line item. A few clear choices today will save you a month of thrash later.
