GitHub Copilot Review: The Platform Play That Wants to Own Your Entire Dev Workflow

GitHub Copilot is no longer just an autocomplete tool. What launched in 2021 as a VS Code extension that finished your code has grown into a sprawling platform - agent mode in the IDE, a freshly GA'd command-line interface, autonomous coding agents that open pull requests while you sleep, multi-model support spanning OpenAI, Anthropic, and Google, and a five-tier pricing structure that starts at free. With over 20 million users and 42% market share, Copilot is the AI coding assistant everyone compares against. After several weeks of intensive testing across all of its surfaces, here is where it actually stands.

What Copilot Is in 2026

Copilot has become an umbrella brand covering four distinct surfaces: inline code completions in your editor, Copilot Chat for conversational coding assistance, agent mode for autonomous multi-step tasks, and the Copilot CLI for terminal-native development. On top of these, the coding agent runs as a cloud-based GitHub Actions worker that can be assigned issues and autonomously produces pull requests.

The most significant recent milestone is the CLI reaching general availability on February 25, 2026. After five months in public preview, it shipped with plan mode (Shift+Tab to review before execution), autopilot mode for full autonomy, built-in MCP server support, session memory that persists across conversations, and model selection mid-session via /model commands. It runs on macOS, Linux, and Windows through npm, Homebrew, WinGet, or standalone binaries.

The multi-model story is equally significant. Copilot now supports 24 models from four providers: OpenAI (GPT-4.1 through GPT-5.3-Codex), Anthropic (Claude Haiku 4.5 through Claude Opus 4.6), Google (Gemini 2.5 Pro through Gemini 3.1 Pro), and xAI (Grok Code Fast 1). You can pick a specific model in the model picker or set it to Auto, which routes your request to whichever model Copilot thinks is best suited for the task.

Agent mode lets Copilot analyze your codebase, propose edits across multiple files, run tests, and iterate until the job is done.

Agent Mode - The Headline Feature

Agent mode is where Copilot makes its strongest case for being more than a glorified autocomplete. Available in VS Code and Visual Studio, it operates as an autonomous peer programmer that can analyze your codebase, read relevant files, propose multi-file edits, run terminal commands, execute tests, and iterate on failures without you touching the keyboard.

In practice, I used agent mode for a range of tasks: adding authentication middleware to an Express app, migrating a React component library from JavaScript to TypeScript, and writing integration tests for a REST API. For scoped, well-defined tasks, it performed admirably. The Express middleware task was completed in a single pass - Copilot created the middleware file, updated the route handlers, added the necessary dependencies, and ran the tests to verify everything worked. Every tool invocation was transparently displayed in the UI, and I could approve or reject individual terminal commands.

Where agent mode struggles is on the open-ended, multi-step tasks that dedicated agentic tools handle better. A request to "refactor error handling across the entire application" produced uneven results - some modules got thoughtful error boundaries while others got wrapped in generic try-catch blocks. Claude Code, by comparison, tends to produce more consistent results on this kind of sprawling refactoring work because it operates directly in your terminal with full local context. Cursor's approach to multi-file editing also felt more project-aware in my testing.

The coding agent - the cloud-based worker that runs in GitHub Actions - is a different beast entirely. Assign it a GitHub issue, and it spins up an ephemeral environment, creates a branch, writes code, runs your CI pipeline, and opens a draft PR for review. You can even delegate from the CLI by prefixing any prompt with & and use /resume to switch between local and cloud sessions. This is a powerful workflow for teams that want to offload routine tasks to background agents, though the cold boot time (90+ seconds to spin up an environment) can be frustrating.

The Multi-Model Advantage

This is where Copilot's platform strategy pays off. No other coding assistant gives you this much model flexibility without changing tools. The ability to start a conversation with Claude Sonnet 4.5 for fast iteration, switch to Claude Opus 4.6 for a tricky architectural question, and then drop to GPT-4.1 for free unlimited completions - all within the same interface - is truly useful.

Copilot supports 24 models across OpenAI, Anthropic, Google, and xAI - more than any competing coding assistant.

But the model flexibility comes with a cost that isn't immediately obvious: the premium request system. Each model has a multiplier that determines how many premium requests a single interaction consumes. GPT-4.1 and GPT-5 mini are free (0x multiplier). Claude Sonnet 4 and Gemini 2.5 Pro consume 1x. Claude Opus 4.6 costs 3x. And if you want Claude Opus 4.6 in fast mode, that is 30x - meaning a single request burns 30 of your monthly allowance.

The Pro plan gives you 300 premium requests per month. If you use Claude Opus 4.6 exclusively, that's 100 interactions before you're cut off. If you use the fast mode variant, you get exactly 10. This is where the pricing starts to feel opaque. You need to actively track your consumption and make per-request decisions about which model to use, which adds cognitive overhead that competing tools don't impose.

The Five Tiers

Copilot's pricing structure has expanded to five tiers:

• Free ($0): 2,000 completions, 50 chat requests per month. No agent mode.
• Pro ($10/month): Unlimited completions, 300 premium requests, agent mode, coding agent access
• Pro+ ($39/month): 1,500 premium requests, access to all models including the most expensive ones, GitHub Spark
• Business ($19/user/month): 300 premium requests per user, centralized management, IP indemnity
• Enterprise ($39/user/month): 1,000 premium requests per user, all models including Claude Opus 4.6, knowledge bases

The Pro tier at $10/month is the clear value play. For individual developers, it offers unlimited completions, agent mode, and enough premium requests for moderate use. Compared to the best AI coding assistants in the market, it's the cheapest entry point with this breadth of features.

The free tier, while heavily marketed, is too limited to be truly useful. Fifty chat requests per month is roughly two interactions per workday. That's enough to assess the tool, not to actually use it.

The Enterprise tier at $39/user/month is harder to justify. The 1,000 premium requests per user sounds generous until you factor in model multipliers. A team of five developers using Claude Opus 4.6 for code review would burn through their combined allocation in a few days. The knowledge base feature - which indexes your organization's codebase for more tailored suggestions - is the real differentiator, but only if your organization is large enough for it to matter.

The CLI - Finally Ready

The Copilot CLI reaching GA is the development I have been waiting for. Terminal-native AI coding is where the most sophisticated developer workflows happen, and Copilot's entry into this space puts it in direct competition with Claude Code and other CLI-based coding tools.

The newly GA'd Copilot CLI supports plan mode, autopilot mode, MCP servers, and session memory across conversations.

The feature set is comprehensive: plan mode for structured implementation with approval, autopilot mode for autonomous execution, built-in MCP server support for custom tool integration, markdown-based skill files, session memory that carries context between sessions, and auto-compacting conversations when you approach the context window limit. The /diff command for reviewing changes with inline commenting is particularly well-done.

In my testing, the CLI performed well on focused tasks but did not quite match the depth of Claude Code on extended, multi-session projects. Where Claude Code maintains richer context about your codebase conventions across sessions, Copilot CLI's memory felt more superficial - it remembered file locations and basic patterns but sometimes lost the thread on architectural decisions made in earlier sessions.

The model selection in the CLI is a strong differentiator. Being able to switch between Claude Sonnet 4.6 for quick changes and GPT-5.3-Codex for complex reasoning, without leaving your terminal, is something no other CLI tool offers. The /model command makes this smooth.

GitHub Integration - The Moat

This is Copilot's true competitive advantage, and it is one that cannot be easily copied. Because GitHub owns the platform where most of the world's code is hosted, Copilot's integrations with pull requests, issues, code review, and Actions workflows are deeply native.

Copilot code review can be triggered automatically on PRs, leaving inline comments with specific, actionable suggestions. In my testing, it caught a missing null check in a TypeScript handler, flagged a N+1 query in a Django view, and identified a race condition in concurrent Go code. These weren't generic "consider handling errors" comments - they were specific to the code being reviewed.

The coding agent's ability to be assigned issues and produce PRs autonomously creates a workflow that is unique to the GitHub ecosystem. You create an issue, assign it to Copilot, and get a draft PR back. For routine bug fixes, documentation updates, and dependency bumps, this is a genuine time saver. The fact that it runs in your CI pipeline means you get the same checks that human-authored code receives.

What Could Be Better

The premium request metering system is Copilot's weakest point. The combination of model-specific multipliers, tier-specific allowances, and monthly reset cycles creates a billing model that developers actively complain about. GitHub community forums are filled with confusion about why requests are being consumed faster than expected. A simpler, more transparent billing model would clearly improve the experience.

Agent mode, while functional, lags behind purpose-built agentic tools. Cursor is more project-aware for multi-file refactoring. Claude Code produces more consistent results on extended, complex tasks. Copilot's advantage is breadth - it does everything adequately - but depth is where the specialists still win.

The coding agent's cold boot time (90+ seconds for environment spin-up) makes it impractical for quick tasks. If the agent encounters an issue and shuts down mid-task, you are waiting through another full boot cycle. For asynchronous background work this is acceptable, but it limits the tool's usefulness for iterative, interactive development.

Enterprise features like knowledge bases and fine-tuned models are available but feel underdeveloped compared to what companies like Sourcegraph offer with Cody. The enterprise value proposition needs to extend beyond "Copilot, but with admin controls."

Strengths

• Multi-model flexibility across 24 models from four providers, switchable per-request
• Deep GitHub integration for PR review, issue management, and autonomous coding agents
• CLI general availability brings terminal-native AI coding with plan and autopilot modes
• Pro tier value at $10/month is the most affordable entry for this feature breadth
• Agent mode handles scoped tasks reliably with transparent tool invocations
• Coding agent enables genuinely asynchronous development through GitHub Actions

Weaknesses

• Premium request metering is confusing, opaque, and a constant source of developer frustration
• Agent mode depth lags behind Cursor and Claude Code on complex, multi-file tasks
• Coding agent cold boot (90+ seconds) makes iterative use impractical
• Free tier is too limited at 50 chat requests to be meaningful for real development
• Enterprise pricing is hard to justify given premium request multipliers eating through allowances
• Session memory in the CLI is shallower than Claude Code's cross-session context retention

The Verdict - 7.5/10

GitHub Copilot in 2026 is the most complete AI coding platform available. No other tool spans inline completions, IDE chat, agent mode, a terminal CLI, autonomous cloud agents, code review, and multi-model support within a single subscription. The breadth is truly impressive, and the GitHub integration creates a competitive moat that no competitor can easily cross.

But breadth comes at the cost of depth. Agent mode works, but dedicated tools do it better. The CLI is capable, but Claude Code is more powerful for extended terminal workflows. The multi-model story is compelling, but the premium request system adds friction that undermines it. And the pricing, while starting cheap, scales confusingly once you factor in model multipliers.

If you are a developer already living in the GitHub ecosystem - writing code in VS Code, reviewing PRs on github.com, running CI through Actions - Copilot is the natural choice. It meets you where you already work, and at $10/month for the Pro tier, the value is hard to beat. For teams that need centralized management and IP indemnity, the Business tier makes a straightforward case.

But if deep agentic capability is your priority, or you want the most powerful CLI experience, or you care about transparent pricing without metering games, you should look at the specialists. The AI coding market is maturing rapidly, and being the biggest platform isn't the same as being the best tool for every job. As we covered in our best AI coding assistants comparison, the right answer depends on what kind of work you do. Copilot's bet is that most developers will choose the platform that does everything over the one that does one thing brilliantly. For many, that bet will pay off.

Sources

• GitHub Copilot Plans and Pricing - GitHub
• GitHub Copilot CLI is now generally available - GitHub Changelog
• Supported AI models in GitHub Copilot - GitHub Docs
• About GitHub Copilot coding agent - GitHub Docs
• How to maximize GitHub Copilot's agentic capabilities - GitHub Blog
• GitHub Copilot Introduces Agent Mode - GitHub Newsroom
• Introducing GitHub Copilot agent mode - VS Code Blog
• Bringing developer choice to Copilot with Anthropic, Google, and OpenAI - GitHub Blog
• Premium requests in GitHub Copilot - GitHub Docs
• GitHub Copilot Statistics 2026 - Panto