From IDE-first to agent-first: a new AI development workflow
AI coding agents are interactive command-line or in-editor assistants that can read project files, run tools, and write code changes, shifting development workflows from manual edits in an IDE toward agent-directed, terminal-based development where the human reviews and guides rather than types every line. Developers who embed agents like Claude Code into their terminal report that Visual Studio Code increasingly feels like a file viewer instead of the place where coding happens, because the agent reads context, runs tests, and applies patches directly from the shell. In this AI development workflow, the terminal becomes the command center: you describe a feature or bug, the agent inspects the repository, proposes changes, and executes commands, while the IDE stays open mainly to display diffs, navigate files, and handle occasional manual tweaks. This shift is creating real momentum for terminal-based development and VS Code alternatives.
Microsoft’s Intelligent Terminal and VS Code 1.123 make agents first-class citizens
Microsoft is experimenting with intelligent terminal tools that treat AI coding agents as built-in companions rather than optional add-ons. The new Intelligent Terminal 0.1 is an experimental shell companion that installs alongside Windows Terminal, opening a docked AI pane powered by GitHub Copilot CLI or other compatible agents to diagnose failed commands and suggest fixes without replacing the stable terminal. At the editor level, VS Code 1.123 turns AI session history into portable project memory: synced histories can follow developers across machines through their GitHub accounts, preserving conversations, repository context, and touched files as a multi-step task. According to WinBuzzer, VS Code 1.123 can use /chronicle commands to search past sessions, produce standup reports, and surface productivity tips by mining that project memory. Together, these features show Microsoft repositioning both the terminal and the editor around persistent, first-class AI coding agents.
Wave and Crush: terminals that behave like AI-centric development desktops
A new wave of intelligent terminal tools is competing directly with traditional emulators like iTerm2, Windows Terminal, and Konsole by centering AI coding agents. Wave Terminal blends a fully featured terminal emulator with a tiled workspace that can hold system monitors, a file explorer, a web browser, and native GitHub panes inside one window. Its AI coding widget can use local or cloud models and, with Widget Context enabled, see everything open inside Wave, so the agent can understand logs, code, and documentation side by side. Meanwhile, Crush (the successor to OpenCode) provides a colorful terminal user interface for AI coding sessions, supporting multimodal input and persistent sessions while letting developers switch between local or cloud models mid-session. These tools make terminal-based development feel closer to a full AI development workflow hub than a simple command shell.
Agents on the command line: when the terminal becomes the main IDE
Terminal-native AI coding agents are changing how developers think about VS Code alternatives and the role of the IDE itself. Tools such as Claude Code, Crush, and similar agentic interfaces live directly in the shell, where they can read project trees, call build systems, run tests, and write code back to disk. XDA developers describe a workflow where they ask an agent for a feature, the agent scans relevant source files, proposes changes, and updates the codebase, while VS Code remains open mainly to view results. The back-and-forth feels more like collaborating with a teammate than prompting an autocomplete model. Because these terminal-based agents are session-focused and conversational, they turn long-running tasks into ongoing dialogues instead of isolated edits, encouraging developers to treat the shell as the primary space where coding work happens.
Persistent memory and cloud access: scaling agent-driven development
For AI coding agents to become the durable center of the workflow, they need memory and scalable compute, and that is starting to appear across tools. VS Code 1.123’s synced AI session history and project memory features mean an agent’s understanding of a repository can persist across machines rather than living in a single local session. In the terminal world, session-based tools like Crush keep conversational context over time, while Wave’s Widget Context gives its AI awareness of the whole tiled workspace. On the infrastructure side, command-line bridges such as Google Colab CLI connect local terminal-based development to remote GPU environments, so agents can run heavier models or large experiments without leaving the shell. Together, these intelligent terminal tools, cloud integrations, and project memory systems make AI coding agents reliable, persistent collaborators instead of one-off assistants.
