Prompts are predefined, ready-to-use actions that you can run from the Cody sidebar, which we recently introduced in VS Code alongside the Prompt Library.

In this update, we've made improvements to the Cody sidebar, cleaning up the interface and making it easier to find and use Prompts. The 'Chat' tab of the sidebar now shows a shortlist of your commonly-used Prompts and commands. The 'Prompts & Commands' tab now shows a list of all available custom Prompts, custom commands, and out-of-the-box commands.

We're excited to announce the release of Cody v1.38, which brings notable improvements to chat performance.

Improved chat performance

DeepSeek-V2 was recently introduced as the default autocomplete model for Cody Enterprise customers, and in this release we have implemented optimizations to prompt caching and direct routing that have resulted in improved latency and quality for both single-line and multi-line completions.

These improvements to autocomplete are available to all Cody Enterprise customers who are using DeepSeek-V2 via Cody Gateway.

AI code assistants are only as good as the context they're given, and Cody uses the context of your codebase as part of its prompt construction to deliver high quality responses to your chats (you can learn more about how Cody understands your codebase here). Cody allows users to @-mention specific repos, directories, and files in your prompts as context to provide greater precision and to increase the likelihood of higher quality responses, and in this release for Enterprise Cloud customers we've made improvements to how Cody handles and fetches context from @-mentioned repos.

High signal code snippets and files are now ranked higher and earlier to the LLM

We announced in Sourcegraph 5.6.0 that we were making single job pods for native Kubernetes Executors the default method over the previous multiple job pod configuration, with the option to switch to multiple job pods if required. We continue to receive positive feedback about this change, and in this release we are removing multiple job pod configurations and making single job pods the default and only way for Executors to run in Kubernetes natively.

Learn more about native Kubernetes Executors in our docs.

Smart Apply lets Cody users take suggestions from the Cody chat window and near-instantly take action with a simple click of the button. Previously focused on code suggestions and turning them into diffs in your code, Smart Apply now supports the executing of commands in the terminal. When you ask Cody a question related to terminal commands, you can now execute the suggestion in your terminal by clicking the Execute button in the chat window.

Executing commands using Smart Apply is available to all VS Code users working in a trusted workspace, and is available in the latest version of VS Code (v1.36).

OpenAI just unveiled its latest models, 01-preview and o1-mini, which offer enhanced reasoning capabilities for tackling complex tasks. Both models are now available in Cody as a limited release. To get on the waitlist for access, navigate to the model selector in the Cody extension and click "Join Waitlist."

We are sunsetting Cody Ignore in this release. Cody Ignore was an experimental feature that was off by default for all users, only enabled via the experimental feature setting in the Cody extension. It lets users specify files or folders in a .cody/ignore file which were then ignored by Cody and disregarded from context.

Although we're not moving this feature into beta, Cody Enterprise users who are interested in excluding files from context can also do this using Context Filters. Context Filters support both exclusion and inclusion rules for determining what files can be used as context, and those rules can be set account-wide. Read more about Context Filters.

Cody chat lets developers @ mention specific repos or files as context in a prompt to improve the quality of the answer it provides. This works well for codebases made up of multiple repos or if you know the exact file you wish to work with, but we've heard feedback from users that quality of results suffered when working with larger, more complex repos like monorepos and you're not sure of or need to reference more than one file.

We're happy to announce an experimental feature that offers users the ability to mention directories when using Cody chat, starting with Enterprise users referencing remote repositories, and for open source repos when using Cody Web. Users can now define context for a prompt one level deeper than a repo without referencing specific files, improving the quality of answers Cody provides from the get-go.

Code Monitors are user-defined queries that alert users whenever a new search result or change appears, and they can trigger actions to run automatically via email, Slack notification, or webhook. Slack notifications were made generally available in July's release, and in this month's release we are now making webhooks generally available.

You can configure a Code Monitor to send webhook notifications by first creating a webhook receiver that accepts an HTTP POST request with the contents of the webhook notification. Then create or edit an existing Code Monitor and select "Call a webhook", pasting the webhook URL into the appropriate "Webhook URL" field and saving the Code Monitor.

The core experience of using Cody is alongside your code in your IDE of choice, but there are often times when you want to interact with Cody via the web. It can be particularly helpful as part of a workflow where you're performing a search via Code Search and need help from Cody, or if you're on your mobile device and want to ask it a question. Many users have also been using Cody Web and its access to leading models from Anthropic and OpenAI to ask non-code related questions as well.

We're happy to announce that Cody Web is now generally available and includes numerous improvements to make the web experience better and more consistent.

Cody is built on model interoperability and we aim to provide access to the best and latest models, and today we're making an update to the default models offered to Enterprise customers.

DeepSeek-V2 for autocomplete

In our quest for consistency across how you use Cody, JetBrains users now get the same side panel experience found in Cody for VS Code and on the web. This update includes improvements such as:

• Chat lives directly in the side panel: Chatting with Cody happens primarily in the side panel, with the option to open a dedicated chat window.
• Dedicated tabs in the side panel: Toggle between chat, history, Prompt Library, setting, and account at the top of the sidebar, making it easier to navigate between commonly performed actions.
• Prompts are easier to discover and use: The new Prompts and Prompt Library appear underneath the chat, making it easier to use and create Prompts while chatting with Cody.

Announced for VS Code users in the last IDE release (v1.32), Smart Apply is now available for JetBrains and allows users to take suggestions from the Cody chat window and near-instantly turn them into diffs in your code. Every code block presented in a chat window will now have a new "Apply" button shown to the user and when clicked, Cody will automatically analyze your open code file, find where that relevant code should live, and add a diff.

The most common use case when searching your codebase is to find the best match to your query as quickly as possible. However, for some use cases such as audits and security checks, completeness of results are far more important. Search Jobs allow search queries to be run across your entire codebase (including repos, branches, and revisions) at scale and prioritize completeness over quick response times and results ranking.

In beta and available by default since Sourcegraph 5.3, we're happy to announce that Search Jobs are now generally available. Learn more about Search Jobs in our docs.

You can now control which parts of a multi-line edit to accept with more granularity. When you ask Cody to edit a block of code, the presented diff will be split into discrete code blocks, and you can accept or reject each diff separately.

Huge thank you to Justin Milner for making this contribution!

We heard from users that the chat wasn't using the full sidebar width, and the chat text was narrower than needed. We've updated this to make chat more space-efficient.

Autocomplete has been overhauled with multiple under-the-hood changes, making it both faster and more accurate:

• P75 latency is down by 350 milliseconds
• Multi-line completions are significantly more accurate and relevant to the surrounding context
• The average completion acceptance rate (CAR) for early users is up by >4%

The Ask Cody to Fix button (released in v6.0.25) is now available on Windows. With just a single button, you can go from seeing an error in your IDE to implementing a fix.

Chat-oriented programming (CHOP) is a new paradigm for chatting with AI to work through problems, write code, and build solutions. CHOP is now even more powerful with the Smart Apply feature, which lets you take suggestions from Cody in the chat and near-instantly turn them into diffs in your code.

Whenever Cody provides a code block as a suggestion in chat, press Apply, and Cody will analyze your open code file, find where that relevant code should live, and introduce a diff. For chat messages where Cody presents multiple code suggestions, you can apply each in sequence to go from chat suggestions to written code in only a few seconds.