The New IDE Is Not an Editor

Editorial June 2026 AI-Native Dev

The IDE is not dead.
It just changed shape.

Claude Code, Codex CLI, Gemini 3.5 CLI, and Grok CLI are not tools that live inside an editor. They are the editor. Your terminal is the new development environment.

Claude Code Codex CLI Gemini 3.5 CLI Grok CLI

Something shifted in how serious development teams are working, and it did not happen gradually. When a company reports compressing months of engineering into days on a 50-million-line codebase, that is not an autocomplete story. That is a different kind of tool doing a different kind of job. The IDE as most developers know it was not part of that workflow.

This is our read on what is happening. It is not a product review, and it is not a formal study. It is an observation shared by a lot of engineers and founders we talk to: the terminal is becoming the development environment, and the tools driving that shift are Claude Code, OpenAI's Codex CLI, Google's Gemini 3.5 CLI, and xAI's Grok CLI. VS Code is still excellent at what it was designed to do. The question is whether what it was designed to do is still the primary job.

50M
Lines migrated in a day, reported by Stripe
80.3%
SWE-Bench Pro score, Claude Fable 5
4
Major AI CLI tools in production 2026
10x
Faster cycles, reported by early adopters

The IDE Was Built Around a Human at the Keyboard

This is not a criticism of VS Code. It is one of the best-designed developer tools ever built. But it was designed around a specific assumption: a human is writing every line, and the tool's job is to make that human faster and less error-prone.

That is why it has syntax highlighting, autocomplete, a debugger, an integrated terminal, and a Git panel. Every feature compensates for a human limitation. It reduces the friction between intent and implementation — but it still assumes the human is the implementer.

JetBrains, Sublime, Vim — same design philosophy, different execution. The editor is an extension of the developer's hands. That was the right model for a long time. The best developers were the ones who knew their editor deeply and moved through code quickly. Speed and familiarity were the competitive advantage.

That model is not broken. It is just no longer the only model available.

The Bottleneck Has Moved

Here is what we are seeing in the teams that have adopted CLI-first AI tools seriously: the expensive part of development is no longer writing. It is deciding what to write, reviewing what was written, and catching what was missed.

When you can describe a task and have it executed across your entire codebase, the bottleneck moves upstream. It becomes the quality of the prompt, the clarity of the spec, the rigour of the review. The cursor-on-screen work, the file-to-file navigation, the manual function authoring: that is the part that is being automated.

How it worked

Human writes, tool assists

  • 1Open file in editor
  • 2Write function manually
  • 3Lint, debug, fix errors
  • 4Test, repeat across files
  • 5Open PR, review by hand
How it works now

Agent executes, human directs

  • 1Describe the task in terminal
  • 2Agent reads the full codebase
  • 3Agent writes, tests, iterates
  • 4Developer reviews the diff
  • 5Ship

Not every task looks like this yet. But the tasks where it does are growing in number and complexity. And teams that have restructured around this pattern are shipping faster with fewer people doing the line-by-line work.

What the New IDE Actually Looks Like

The new development environment has four qualities that make it different from anything that came before.

It is terminal-native. There is no GUI. You open a shell, you describe what needs to happen, and the agent works. The codebase is its context window, not a file you navigate to.

It has full repository awareness. A traditional editor knows the open file. Maybe the imports. The new tools read everything: every module, every test, every config. This is how a 50-million-line migration becomes a one-day task instead of a two-month project.

It executes rather than suggests. Early AI tools offered autocomplete. You accepted or rejected, line by line. These tools do not wait. They run, hit a build error, fix it, run tests, fix what fails, and return a finished diff. The loop runs inside the agent, not inside your head.

It converses. You review the output, give feedback, the agent adjusts. The session in the terminal is the development session. Not a file. A conversation with an outcome.

terminal — your-project

$ claude "migrate all API endpoints to the new auth middleware, update tests"

Reading codebase... 847 files indexed

Identified 23 endpoints across 11 files

Applying migration...

Tests failing on auth/refresh.js, fixing...

Running test suite... 94/94 passing

Done. 31 files changed. Review diff before committing.

No editor was open. No file was navigated to. That is a development session.

The Tools Representing This Shift

Four tools are defining what CLI-first development looks like in 2026. They each come from a different ecosystem, and that matters for the teams evaluating them.

CC
Claude Code
Anthropic

The most capable software engineering agent available today, powered by Claude Fable 5. Reads your full codebase, handles multi-file migrations and refactors, and runs autonomous loops until the task is done. The 80.3% SWE-Bench Pro score is the ceiling right now.

CLI · Full codebase · Agentic
CX
Codex CLI
OpenAI

OpenAI's terminal-native agent built on GPT-5.5. Strong on agentic task execution and tightly integrated with the OpenAI tooling ecosystem. The natural choice for teams already running on OpenAI infrastructure who want to extend it to the development workflow.

CLI · Shell-native · GPT-5.5
GC
Gemini 3.5 CLI
Google

Google's entry into the CLI-first developer space. Gemini's long-context architecture gives it a particular edge on large repositories where understanding the full codebase before touching anything is what separates a good migration from a broken one.

CLI · Long-context · Google
GK
Grok CLI
xAI

The one tool in this group with live data access. Grok's integration with the X data stream means developers building products that touch real-time information have context no other CLI tool can match. A specific advantage, not a universal one.

CLI · Real-time data · xAI

We are not picking a winner here. Each of these tools is well-suited to different teams and different infrastructure choices. What they share is the paradigm: agent-centric, terminal-first, full-codebase-aware. Naraway can help you pick and implement the right one

Cursor and Windsurf Are the Bridge, Not the Destination

Cursor and Windsurf deserve credit. They are the best GUI coding environments available and they have genuinely changed how developers work. Both are VS Code forks rebuilt around AI as the primary interface. The editor is familiar, but the AI is not a plugin — it is the core of the experience.

Transitional

Cursor

VS Code rebuilt around Claude. The familiar layout, the familiar shortcuts, but with deep multi-file AI editing baked in. The best bridge for teams not ready to go fully terminal-first. Many teams will live here for a while, and that is a perfectly reasonable call.

Transitional

Windsurf

Codeium's AI-first editor. Similar positioning to Cursor: a visual environment where the AI drives, not assists. Strong contextual awareness and autonomous multi-step edits. A solid choice if your team needs the visual feedback loop while adopting agentic workflows.

These tools are not wrong. They are transitional in the sense that the trajectory of the industry runs past them. The GUI editor with AI built in is one generation behind the agent that operates without an editor at all. Teams using Cursor today are primed to move further when they are ready. The direction is clear even if the pace varies.

What This Actually Means If You Run a Team

This shift does not mean hiring fewer developers and calling it done. It means the role changes. What makes a good engineer in an agentic workflow is different from what made a good engineer in an editor-centric one.

Junior Developers

The floor rose significantly

Scaffolding, boilerplate, standard patterns: the work that consumed early careers is now largely automated. A junior developer who learns to direct and review agents well will ship at a level that used to take years to reach.

Senior Developers

Writing less, reviewing more

The most valuable senior skill is no longer raw coding speed. It is the ability to catch what the agent missed: the architectural edge case, the unhandled error path, the test that passes but does not actually test anything meaningful.

Tech Leads

Output per person increases

A focused team using agent-centric workflows can deliver considerably more routine feature work than the same team would have managed before. The structure question shifts from headcount to how many good reviewers you have directing the agents.

Founders and CTOs

Lean teams, real leverage

The startup advantage here is genuine. Fast-moving teams running Claude Code or Codex CLI on a well-structured codebase can execute development cycles that previously required significantly more engineering headcount. The leverage is real if the workflow is set up correctly. Naraway helps set it up

Want to Run Your Team on Agent-Centric Dev?

The tools exist. What most teams need is workflow design, codebase preparation, and the right system prompt architecture to get consistent results. Naraway's tech team implements Claude Code and Codex CLI workflows for startups and growing businesses, from first setup to team adoption.

Talk to Naraway's AI Team

How to Start Without Disrupting Your Sprint

The teams making this shift well are not doing it all at once. They are starting with low-risk, high-repetition tasks and building from there.

Start with something contained

Treat prompting as a team skill

Redesign your review process for larger diffs

VS Code will not disappear from desktops any time soon. Neither will JetBrains or Vim for the developers who know them deeply. But the frontier of how software gets built has moved, and it moved fast. The teams working at that frontier are not opening files and writing functions. They are opening a terminal and describing outcomes. The distinction sounds subtle. In practice, it is a different job. We help you make that shift

KA
Keshav Agarwal
Editor, Naraway

Keshav covers AI tools, developer ecosystems, and startup technology at Naraway. He writes about what is actually changing in how software gets built, for the teams building it.

Frequently Asked Questions

What is replacing VS Code in 2026?

Not one tool, but a paradigm shift. AI-native CLI tools like Claude Code, Codex CLI, Gemini 3.5 CLI, and Grok CLI are redefining what a development environment is. Instead of helping you write code faster, they execute development tasks autonomously. The developer's job shifts from writing to directing and reviewing.

What is Claude Code and how is it different from an IDE?

Claude Code is Anthropic's CLI-first coding agent. It runs in the terminal, reads the full codebase, and executes tasks across multiple files autonomously. Unlike an IDE that assists a human writing code, Claude Code acts as an agent that writes, tests, debugs, and iterates without waiting for you to approve each line.

Is VS Code still relevant in 2026?

Yes, and for many teams it will remain the primary environment for a while. AI-enhanced forks like Cursor and Windsurf have made the VS Code paradigm significantly more capable. But the fastest-growing developer workflows are terminal-first and agent-driven. Cursor and Windsurf are transitional; the direction is toward full CLI-native agents.

What is Gemini 3.5 CLI?

Google's terminal-native AI coding tool. It brings Gemini's long-context reasoning into the developer command line, enabling autonomous multi-file coding tasks. Its long-context architecture gives it a specific advantage on large codebases where understanding the full repository before making changes matters.

Should startups adopt AI CLI tools now?

For startups trying to move fast with lean teams, yes. The productivity gains on repetitive engineering work — migrations, scaffolding, test generation, API boilerplate — are significant and available today. Start with a contained task, measure the output, and expand from there.