Claude Code CLI: The Economics Are Right, But You Can't Review Code in a Terminal

I came to Claude Code from Cursor. Not because I was unhappy with the code quality or the tab completion. Cursor's inline experience is still best-in-class. I switched because the economics stopped making sense. Cursor's token limits throttle you during heavy agentic sessions, and API mode turns into a blank check. Claude Code offered a more workable cost structure for how I actually use AI tools day to day. After spending serious hours with it, here's where it delivers and where it fundamentally falls short.

The Economics That Pulled Me In

The usage limits on Claude Code's Max plans feel meaningfully more generous for agentic workflows compared to what Cursor offers at similar price points. You can run longer, more complex sessions before hitting a wall.

More importantly, the API cost structure is workable. When I switched Cursor to API mode to avoid plan limits, the bills were unpredictable and climbed fast. With Claude Code on API, the per-token costs are more manageable and the sessions feel less like a meter is running. For a developer using AI tools all day, this matters. You shouldn't have to ration your interactions with a tool you're paying for.

The economics alone were enough to make me commit to learning the tool's workflow. Everything else I discovered, both good and bad, came from actually using it daily.

IDE Integration: Two Paths, Both Rough Around the Edges

One of the selling points of a CLI tool is that it works anywhere you have a terminal. In theory, this is great. In practice, both integration paths have real friction.

Terminal in Any IDE

I primarily used Claude Code via the integrated terminal in PyCharm and occasionally in Cursor. The beauty of this approach is simplicity: open a terminal panel, run claude, and you're working. No extensions to install, no compatibility issues, no waiting for plugin updates.

The IDE connector does its job for the most part. It picks up file context correctly, understands what project you're in, and can read and edit files in your workspace. The important stuff works.

But the diff view almost never works properly. When Claude Code makes edits, you're essentially trusting that the changes are correct because the inline diff rendering in the terminal is unreliable. You can see that files were changed, but getting a clear, reviewable picture of what changed requires leaving the tool and checking diffs in your IDE or Git. This becomes a recurring friction point that I'll come back to; it's the core problem with the entire experience.

VS Code / Cursor Extension

I also spent time with the dedicated VS Code integration, hoping it would bridge the gap between CLI power and editor UX.

The problem is architectural. VS Code and Cursor already have native chat interfaces: Copilot Chat, Cursor's own Composer panel. These tools own the default chat sidebar. Claude Code's extension can't replace them. It has to live in a separate, non-standard UI element: a different panel, a different interaction model, a different visual language than what the editor natively provides.

The result is an awkward experience where you have two AI interfaces coexisting in the same editor, neither fully integrated. You're constantly aware that Claude Code's panel is a guest in someone else's house. The edit and apply functionality through the extension is also inconsistent; sometimes changes apply cleanly, sometimes they don't land correctly, and you're back to manually verifying in the file.

Neither integration path feels fully baked. The terminal approach is more honest about what it is (a CLI tool), but the editor extension tries to be something it can't quite achieve within the constraints of existing IDE architectures.

Code Quality: Good, With the Right Approach

Setting aside the UX friction, the actual quality of code that Claude Code generates is good. Often very good. But there's a critical caveat: it's almost entirely dependent on the quality of your input.

Vague prompts produce vague code. Ask Claude Code to "add authentication" and you'll get a generic implementation that may or may not fit your stack, your patterns, or your existing architecture. Ask it to "add JWT authentication middleware to the Express router in src/api/router.ts using the existing verifyToken utility in src/lib/auth.ts" and you'll get something you can actually use.

This is the "garbage in, garbage out" principle applied to AI-assisted development. The model is capable, but it needs you to be specific about the task, the scope, and the context. The more precisely you define what you want, the better the output. This isn't unique to Claude Code; every AI coding tool works this way. However, because Claude Code is entirely prompt-driven (no inline suggestions to nudge you), the quality gap between good and bad prompts is more pronounced.

Plan Mode Is the Way

This is the single most important lesson from my time with Claude Code: do not one-shot it.

The temptation is strong, especially when you're used to fast iteration cycles. You want to type "build me a comment system with threaded replies" and get working code back. And Claude Code will try: it'll generate files, wire up components, write the logic. But the result almost always needs heavy rework. The model makes assumptions about your architecture, misses edge cases, picks patterns that don't match your codebase, or structures things in ways that create problems downstream.

The dramatically better workflow is to start with Plan mode. Describe what you want to build. Let the model research your codebase: it'll read files, understand your patterns, map out dependencies. Then it proposes a plan: what files it'll create or modify, what approach it'll take, what the architecture looks like. You iterate on that plan. You push back on decisions you disagree with. You ask questions. You refine the scope.

Then you implement.

The difference in output quality is night and day. When Claude Code has a well-defined plan and understands your codebase before writing a single line, the generated code is cleaner, more consistent with your existing patterns, and requires far less rework.

This is counterintuitive for developers used to rapid prototyping. Spending ten minutes on a plan before generating code feels slow. But it saves you thirty minutes of fixing the one-shot attempt. It's a workflow shift: you become an architect first, a reviewer second, and a typist almost never.

Context Management Is a Skill You Have to Learn

Working effectively with Claude Code means learning to manage context like a resource, because it is one.

The most practical habit I've developed is clearing context aggressively between unrelated tasks. If I'm done refactoring a component and moving on to a database migration, I start a fresh session. Stale context from the previous task actively degrades the next one. The model carries forward assumptions, file references, and mental models from the old task that pollute the new one.

Using /compact manually between tasks also works well. It compresses the conversation history and keeps the model focused on what matters for the current task rather than dragging along the full weight of everything you discussed before.

Auto compact, the tool's built-in context management, is decent, but it comes with a notable downside. It reserves a meaningful portion of your available context window for its own overhead. This means you have less working context available for the actual task at hand. On complex tasks where you need the model to hold a lot of codebase context simultaneously, auto compact can feel like it's eating capacity you need. You end up in situations where the model is forgetting things it should know because the auto compact system decided to trim context you still needed.

Learning when to clear, when to compact manually, and when to start fresh is part of becoming effective with the tool. It's not something the tool teaches you; you figure it out through hours of practice and noticing patterns in when output quality drops.

The Paradigm Flip: Vibe Coding Over Engineering

Claude Code flips the traditional practice of software engineering on its head.

In a conventional workflow, you think through the problem, design the architecture, consider edge cases, and then write code deliberately. The writing is the culmination of the engineering process. With Claude Code, the default mode is almost the reverse: describe what you want in natural language, let the AI figure out the implementation, and review what it produced.

Out of the box, this promotes what the community has started calling "vibe coding": you describe the vibe of what you want and the tool generates something that matches. It's powerful for velocity. You can scaffold entire features in minutes. The feedback loop from idea to working code is compressed dramatically.

But this comes with a trade-off. The default workflow deprioritizes the engineering discipline of thinking through architecture, patterns, and edge cases before code exists. The code shows up immediately, and the temptation is to accept it if it runs rather than evaluate whether it's the right approach.

Plan mode counteracts this by forcing the architecture step back into the process. But it's opt-in, not the default. The tool's out-of-the-box experience encourages speed over rigor. That's great for prototyping, exploration, and personal projects. It's less great for production codebases where the long-term cost of poorly considered architecture far exceeds the short-term gain of faster generation.

The Dealbreaker: You Can't Review Code in a Terminal

Here's the fundamental problem, and it's the reason Claude Code alone isn't enough for production work.

When AI writes your code, the most important activity shifts from writing to reviewing. You're no longer the author; you're the reviewer. And most of your time should be spent reading, understanding, and evaluating the changes the AI made. This is the critical activity. This is where bugs get caught, where architectural problems surface, where you ensure the generated code actually does what you intended.

Claude Code provides almost no support for this activity.

The tool operates in a terminal. When it makes changes across multiple files, you get a text-based summary of what was modified. There's no syntax-highlighted diff view. No inline annotations. No side-by-side comparison. No easy way to navigate between changed files and understand the full picture of what the AI did to your codebase. You either trust the output or you leave the tool entirely to inspect changes in your IDE or Git client.

For small, scoped changes, this is manageable. For anything substantial (a multi-file refactor, a new feature touching several components, a migration that touches data models and API layers), reviewing in a terminal is effectively impossible. You can't hold the full scope of changes in your head from scrolling terminal output.

This means that in practice, Claude Code handles one half of the AI-assisted workflow (the generation) and completely punts on the other half (the review). You need a separate tool, a separate context switch, and a separate workflow to actually verify what the AI produced. The tool that writes your code isn't the tool where you review your code, and that disconnect creates friction in every single session.

For production codebases where code review isn't optional, this isn't a minor inconvenience. It's a gap in the workflow that the tool doesn't acknowledge or address.

The Verdict

Claude Code gets the economics right. The usage limits are more generous than Cursor's for agentic workflows, and the API costs are predictable enough for daily use. If cost was the barrier keeping you from leaning into AI-assisted development, Claude Code removes it.

The code quality is genuinely good when you work with the tool correctly: use Plan mode, be specific with your prompts, manage your context, and don't try to one-shot complex tasks. The learning curve is real, but once you internalize the workflow, the output is consistently solid.

But the reviewing problem is real and it's fundamental. AI-assisted development shifts the core developer activity from writing to reviewing, and Claude Code provides no tooling for the activity you'll spend the most time on. A terminal is not a code review interface. Until that gap is addressed (whether through better IDE integrations, a dedicated review UI, or something else entirely), Claude Code is best used as part of a multi-tool workflow rather than a standalone solution.

My current setup: Claude Code for generation, planning, and codebase exploration. My IDE for review, fine-tuning, and the final pass before anything gets committed. It's not seamless, but it works. The tool that thinks about code and the tool that shows you code are still two different things.