From editor-first to terminal-first development
Terminal AI agents are command-line tools that read project files, run shell commands, and write code changes, turning the terminal into a primary AI-powered development workflow instead of a passive console. For a growing group of developers, that means terminal-based coding has become the main interface, with Visual Studio Code or other editors reduced to a secondary viewing window. In one reported workflow, an agent in the project directory runs tests, checks dependencies, edits files, and pushes changes while the developer watches results in VS Code like a live dashboard. The human role shifts toward describing features, reviewing diffs, and correcting edge cases rather than typing every line. This is not framed as abandoning IDEs, but as rearranging the stack: the command line and its AI agent become the center of gravity, and GUI tools orbit around them.
Microsoft’s intelligent terminal and agent-centric VS Code
Microsoft is quietly acknowledging the rise of command-line AI tools by experimenting with an Intelligent Terminal fork that adds AI agent panes alongside the shell. These panes aim to debug failed commands, explain errors, and propose immediate fixes, turning “command not found” moments into interactive repair sessions. At the editor level, VS Code 1.123 treats AI-assisted work as a continuous process instead of isolated chats. The release introduces portable AI-session history tied to GitHub accounts, so developers can move between machines while keeping a shared log of conversations, touched files, and referenced pull requests. According to WinBuzzer’s coverage of VS Code 1.123, the new /chronicle commands can search past sessions and generate standup-style summaries from that history. Together, these features show Microsoft preparing for workflows where the AI agent, not the editor frame, owns the narrative of a project over time.
Wave and Crush reimagine what a terminal can be
New terminals are embracing AI as a first-class feature instead of a bolt-on extension. Wave Terminal takes a tiled approach that feels like a development desktop inside a shell window: system monitors, file explorers, GitHub pages, and a web browser share space with a command line. Its AI coding widget can run local or cloud models and, with context sharing enabled, see everything open across those panes. That turns Wave into a hub for terminal AI agents that understand the full workflow, not only the current buffer. In parallel, Crush—formerly OpenCode—offers a colorful terminal user interface focused on multimodal, session-based AI coding. It supports multiple models with mid-session switching, which lets developers swap between planning, implementation, and revisions without leaving the terminal. For long-time iTerm2, Windows Terminal, or Konsole users, these tools present a credible VS Code alternative for day-to-day coding.
Colab CLI and the rise of cloud-linked shells
The next step in terminal-based coding is linking local shells to remote compute, and Google Colab CLI points in that direction. While classic Colab lives in the browser, the CLI exposes Colab’s cloud GPU environments from a standard terminal, so developers can run heavy workloads without leaving their command-line AI tools. A terminal AI agent can orchestrate local file edits, run tests, then push selected jobs to a Colab-backed session for training or inference. This pattern blurs borders between laptop and cloud: the shell becomes the single pane for both environments. When paired with agent-aware terminals like Wave or TUI-first tools like Crush, Colab CLI helps frame a new stack where the command line is not a legacy interface but the preferred front door for AI coding. In that world, GUI IDEs look more like optional companions than mandatory centers of development.
