packages/kilo-docs/pages/code-with-ai/platforms/vscode/whats-new.md
The Kilo Code extension has been completely rebuilt on a portable, open-source core shared across VS Code, the CLI, and Cloud Agents. This is the biggest update since launch: faster execution with parallel tool calls and subagents, the new Agent Manager for running multiple agents side by side, inline code review with line-level comments, multi-model comparisons, and access to 500+ models.
Whether you're writing features in VS Code, debugging over SSH, or reviewing code on Slack, Kilo now goes with you. Read the full announcement on the Kilo Blog for everything that's new.
A lot has changed under the hood, and some things have moved around. If you're coming from the previous extension, you might have questions about where to find certain features or how things work now. We've collected the most common questions below.
Still stumped after reading this? Come find us in discord at #vscode.
Code indexing is temporarily unavailable in the new extension. It is actively being worked on and is expected to return soon. Please follow this issue
Checkpoints are now called snapshots in the new extension. They use Git-based snapshots of your working directory, taken before and after agent edits. You can revert any message's changes directly from the chat, and a revert banner appears when you're viewing an earlier state. See the Checkpoints documentation for details.
The old auto-confirm commands UI has been replaced by a granular per-tool permission system.
Open Settings → Auto Approve to configure each tool (bash, read, edit, glob, grep, etc.) with Allow, Ask, or Deny.
There is no longer a separate command allowlist — shell execution is controlled by the bash tool permission.
See Auto-Approving Actions for more information.
Yes — the context progress graph (also known as the task timeline) is now available. It appears at the top of the chat panel and shows:
You can expand or collapse the graph — your preference is saved in the kilo-code.new.showTaskTimeline setting.
We are working to improve the experience in closely managing an agent. Identified improvements and progress are being tracked in a GitHub issue.
In the meantime we suggest exploring:
Modes have been renamed to Agents in the new extension. You can set the default model for each agent in Settings -> Models -> Model per Mode. For more information please check the agents documentation.
Each message that caused file changes shows a diff badge in the chat — click it to open the Diff Viewer and review what changed. The Agent Manager also includes a built-in diff reviewer that shows every change file by file, in unified or split view. For Markdown files, use the eye/code toggle in the file header to switch between rendered Markdown and the raw diff.
You can now trigger local AI-powered code reviews directly by using two commands: /local-review to review all changes on your current branch vs the base branch, and /local-review-uncommitted to review staged and unstaged changes.
See the Code Reviews documentation for the full setup and options.
In the model picker dropdown, click the expand button in the upper-right corner to switch to the full model picker view. From there, click on any model to see its details — including input and output pricing per million tokens, the context window size, and which capabilities the model supports (reasoning, text, images, etc.). This makes it easy to compare costs before selecting a model.
If you're using a custom model (e.g. via your own API key or a self-hosted provider), you can configure the context window size, max output tokens, and other parameters in your model settings. See the Custom Models documentation for the full guide on adding and configuring custom models.
In the new extension we simplified the model selection by removing the profile layer. To keep models easily reachable you don't need a profile — you can just star them in the model selector to mark them as favorites.
Orchestrator mode is deprecated. Agents with full tool access (Code, Plan, Debug) can now delegate to subagents automatically — you no longer need a dedicated orchestrator. Just pick the agent for your task and it will coordinate subagents when helpful. You can also define your own custom subagents. See the Orchestrator Mode page for the full details on what changed.