We've built a new changelog to better highlight all the changes that will be coming in this new era of Sourcegraph. We are doubling down on the future of code understanding, and are ready to hit the ground running this year with exciting new improvements and features.

In the new Featured feed, you can find updates for our biggest changes in the form of standalone posts. In this feed, every Sourcegraph release - for example, Sourcegraph 6.12 - will get its own dedicated page that compiles all the changes from the release as well as all of its subsequent patches. Each release page will indicate the major updates included in the release, as well as a Details section with smaller improvements, fixes, and notes on deprecations.

You can now ask Deep Search questions directly from code navigation. Code you select in the blob view is automatically added as context to your conversation.

The Sourcegraph Slack integration is now available. When you mention @Sourcegraph in Slack discussions, a Deep Search conversation will be initiated directly in the Slack thread. You can also ask follow-up questions as the discussion goes on.

The Sourcegraph MCP server now supports OAuth authentication using the OAuth 2.0 Dynamic Client Registration Protocol (RFC 7591). This makes using the new Deep Search tool easier than ever.

Previously, connecting an AI agent like Claude Code or Amp to your Sourcegraph MCP server required specifying an access token header or creating an OAuth client for agents that supported specifying a custom client ID. Now, you can connect most AI agents to the Sourcegraph MCP server with one command.

We're reworking the Sourcegraph administration pages to make Sourcegraph easier to set up and maintain.

The overview page has been reworked to provide administrators with a quick overview of the instance, whether there are any notifications that need attention, and some recommendations on what they might want to view or set up next.

Sourcegraph administrators can now set per-user Deep Search usage limits using entitlements: classes of usage limits that can be assigned as a global default, or to specific users. Entitlements can be configured in the Administration → Entitlements page.

Sourcegraph now supports OAuth credentials for GitLab in Batch Changes. Previously, only API keys were supported.

Once a Sourcegraph administrator has set up a GitLab app for their instance, and configured this as an authentication provider in Sourcegraph, users can authenticate through this GitLab app in their Batch Change credential settings.

For almost two years, we have been working behind the scenes on a complete rewrite of Sourcegraph's user interface. The previous UI had accumulated more and more cruft, and it became increasingly difficult to maintain and to develop new features. Today, we're happy to share that this new UI is enabled for all customers, throughout the entire Sourcegraph experience.

This lays the foundation for a coherent, unified product. For our customers, this means a faster, more responsive experience with improved page load times and smoother navigation. For us, it means we can ship new features and improvements more quickly.

Cody Enterprise customers now have access to three new AI models: Claude Opus 4.5, Gemini 3 Pro, and GPT-5.1. Claude Opus 4.5 includes both standard and thinking-enabled variants for enhanced reasoning and problem-solving.

These models are available across VS Code, JetBrains IDEs, and Cody Web. Enterprise customers can immediately select their preferred model from the Cody interface to improve their coding, debugging, and development workflows.

Performance

Deep Search now leverages enhanced reasoning capabilities to optimize tool call use and response creation. This update lowers latency and improves context handling, enabling more interaction turns before hitting context limits.

Deep Search now includes inline citations to make answers strictly verifiable. Citations act as clickable annotations pointing to the specific code logic used in the response. You can now instantly navigate to and highlight the exact snippet that informed an answer rather than hunting through a list of files.

This eliminates the guesswork behind the model's reasoning. By allowing you to review the referenced code directly, you can quickly assess the quality of the answer and move forward with confidence.

Claude Haiku 4.5 offers improved speed and capabilities over previous versions. IDE support includes: VS Code, Visual Studio, JetBrains, and the web app.

You can now connect AI agents and applications to your Sourcegraph v6.8 instance's code search through the new official Sourcegraph Model Context Protocol (MCP) Server. Available on Enterprise plans, this experimental feature provides AI agents and applications with programmatic access to your Sourcegraph instance's code search, navigation, and analysis capabilities through a standardized interface.

Please note that this feature is experimental and might change or be removed in future releases.

Code navigation now delivers faster Go to Definition and Find References operations with significantly improved accuracy across complex codebases. The rewritten navigation logic provides more precise results for interfaces and inheritance hierarchies, while ensuring consistent method reference results.

For Enterprise customers managing large monorepos with multiple SCIP uploads per repository, navigation commands now return consistent results, regardless of the triggering location, enabling more reliable code exploration and a deeper understanding of complex language features. This enhancement is available exclusively on the web interface.

Deep Search is moving out of free research preview

Since its launch in version 6.5, Deep Search has been free to use. Starting October 15, 2025, each Code Search seat will include 3 Deep Searches per month, shared across your organization. Unused searches expire at month-end, and extra usage will incur charges. Contact your AE for pricing details.

GPT-5 brings significant reasoning and coding improvements. IDE support includes: VS Code, Visual Studio, JetBrains, and the web app.

Syntax highlighting for SQL enhances readability, making complex queries easier to scan and understand.

Template variables such as repository.search_result_paths and previous_step.modified_files allow you to chain operations and optimize batch changes by processing only relevant files. The templating engine supports Go's text/template features including conditionals, loops, and custom helper functions, providing programmatic control over changeset generation and execution flow.

This feature is available on Enterprise plans and enables more sophisticated automation workflows for large-scale code modifications.

Inventory Stats, launched last month, make it easy to track how your codebase evolves over time, no search required. We’ve now added support for grouping metrics to help you create cleaner, more focused visualizations.

Grouped charts are especially useful for tracking migrations, understanding repo composition, or comparing multiple teams or projects in one view.

We’ve introduced a new Inventory Stats Code Insight that makes it easy to track how your codebase evolves over time, no search required. This insight complements existing Insights like Track Changes and Language Usage, but brings a more scalable and reliable way to monitor inventory-style metrics across repositories.

With Inventory Stats, you can [...]

Auto-edit, previously available in VS Code, is now rolling out to JetBrains and Visual Studio for Cody Gateway customers. This update enables auto-edit by default - providing inline code edits instead of autocomplete - with the option to opt out.

Enterprise customers can now use OAuth 2.0 to securely connect apps and scripts to Sourcegraph APIs, just like you would with GitHub or GitLab. This includes full support for OIDC, PKCE, device auth, and M2M tokens.

With short-lived access tokens, your tools can act on behalf of users, making it easier to build custom automations and workflows on top of Sourcegraph. If you’ve been blocked from integrating because auth was missing or hard to manage, this clears the path.

Developers increasingly want to work with more context, whether it's reviewing all files in a pull request, generating a new Dockerfile based on all others in a repo, or reasoning across a large set of project resources. But context limits have traditionally capped how much they can reference in a single request, leading to fragmented workflows or lower quality responses.

To help with this, we're expanding both input and output context windows in Cody Chat for Cody Enterprise customers.

We’ve introduced service sccounts, a new way for administrators to create Sourcegraph actors that are designed specifically for API access without UI access or user credentials.

As of July 23, 2025, we will no longer offer the following plans:

• Cody Free
• Cody Pro

We’ve shipped several updates to Sourcegraph Analytics to give you deeper and more flexible insights into how your teams are using Sourcegraph:

Time filters added to the analytics CSV export API

Sometimes you want to automate large-scale code changes without triggering a merge request, like updating internal tooling, modifying generated code, or experimenting with refactors. Until now, Batch Changes always assumed you wanted to open a merge request.

This update introduces a new type of changeset that doesn’t require a merge request. It simply [...]

When using AI-generated steps (like LLMs) in Batch Changes, results can vary run to run. Until now, re-running those steps meant re-executing the entire batch spec. That’s no longer necessary.

You can now re-execute changeset creation logic for individual workspaces, making it easier to regenerate or revise changesets without restarting from scratch.

Anthropic's new Claude 4 models are now available for Cody users, with the following models available for each plan:

Cody Free and Pro:

We’ve added a new option for site admins to set a default search context for all users on their instance. Previously users could set their own default context used when searching their codebase, but this update now allows admins to set this globally.

This helps teams improve onboarding and search quality by focusing searches on the most relevant parts of the codebase, rather than the entire indexed set of repositories.

File and directory filtering has been added to the compare page in Code Search to make large diffs easier to navigate, manage and share. When comparing branches with thousands of changed files, you can now use the file picker to select specific files or directories to focus on. You can also filter files directly by constructing a URL with multiple file paths, or use a compressed file list for even larger selections.

This update gives you much greater control over which changes you view, helping teams review only the files relevant to them without endless scrolling.

Originally announced as an experimental feature, Cody's agentic context gathering is now generally available across all IDEs and the web.

The context gathering experience evaluates the provided context in a prompt, and fetches any additional context (via Sourcegraph search, terminal, etc.) to provide enhanced, context-aware capabilities. It aims to reduce the need to provide context manually, and at the same time improve the quality of prompt responses.

We've added support for service access tokens for Sourcegraph Analytics, enabling admins to programmatically access user-level analytics data without relying on browser-based authentication. These long-lived tokens are tied to individual accounts.sourcegraph.com users and allow customers to pull analytics data into their own systems securely and continuously.

Previously, customers had to manually extract session credentials to automate analytics access - this update eliminates that workaround and supports a more secure, standards-based integration with customer data pipelines.

Note: This page describes how MCP tools are used within Cody.

If you're looking for the Sourcegraph MCP Server (for connecting external AI agents and applications), see: Sourcegraph MCP server.

Cody now supports MCP tools via its agentic context gathering, enabling automated tool use to gather and inject context directly into Cody's responses.

We've updated the prompt library to make it easier for teams to collaborate using the Organizations feature. Prompts can already be owned by an organization - now, they're easier to find, filter, and manage.

We've added a variety of new LLM options from OpenAI and Google for Cody users:

Cody Free:

Smart Apply is a Cody feature that applies high-confidence code edits from chat responses directly into your codebase, streamlining your development workflow. Cody uses a targeted model for Smart Apply that is well-suited for low latency, and the previous model used (Claude 3.5 Sonnet) has been replaced by a new model: Qwen 2.5 Coder.

This update improves the responsiveness of Smart Apply in both VS Code and JetBrains by ~5x while preserving edit quality.

JetBrains users can now try auto-edit, now available as an experimental opt-in in the Cody plugin.

Auto-edit analyzes your recent changes and suggests context-aware edits—like cleaning up code, adding missing pieces, or improving structure. Instead of writing every change yourself, you can apply Cody's suggestions directly in your IDE.

Batch Changes now supports using GitHub fine-grained access tokens as credentials for creating and managing changesets. This support is experimental and is especially useful for customers who prefer not to use GitHub Apps due to their broad repo access, and who also disallow personal access tokens (PATs) because of their wide permissions and lack of expiration controls. Fine-grained access tokens strike a better balance: they’re more secure than PATs and more flexible than GitHub Apps.

They can be used for both user-level and site-admin credentials in Batch Changes. However, note that fine-grained tokens can be more complex to set up and may require admin approval in your GitHub organization.

Site admins can now fully customize the examples shown in the batch spec library - visible when defining a batch spec for a new batch change - using three new GraphQL APIs:

• createBatchSpecLibraryRecord
• updateBatchSpecLibraryRecord
• deleteBatchSpecLibraryRecord

Batch Changes now supports a new bulk action to help teams working in fast-moving codebases: rebase changesets.

This makes it significantly easier for teams to keep changesets up to date. Instead of rebasing each changeset manually, users can now do it all at once with a single action—streamlining workflows and reducing friction when managing large-scale changes.

Developers using Cody chat now have access to two variations of Claude 3.7 Sonnet: the standard model useful for faster, more responsive interactions, and another optimized for reasoning ("extended thinking").

With this update, Claude 3.7 Sonnet can now be used in different contexts depending on whether long-form reasoning is required or for tasks where speed and performance is a priority.

You can now sign commits with SSH keys in Batch Changes - giving enterprise teams a more secure, user-level alternative to GitHub Apps for commit verification. This feature is available in experimental form and currently supports GitHub and GitLab.

To get started, users add a personal access token (PAT) and check a box to enable commit signing. When they do, Sourcegraph generates an SSH key pair, surfaces the public key, and guides users to add it to their code host as a signing key. Site admins can also add PATs, and they function as a global credential to all users who don't set their own.

We’ve improved how Sourcegraph ranks results in the main search bar to deliver more relevant results tailored to each user. When you search for something like data router, Sourcegraph now applies best-in-class ranking strategies that better understand your full query - not just keywords in isolation. In addition, we boost results from repositories you’ve recently contributed to, making it easier to find the code you care about faster.

Flexible code search queries - where you are looking for something, but don’t 100% remember the name - has been improved. Below is a before and after for the query contributors job that highlights this improvement and our use of BM25 ranking.

The Batch Changes list page now supports searching by title, letting you filter down results by typing keywords that match the batch change’s name. Previously, the list view only showed the 15 most recent batch changes by default, with the option to load 15 more at a time. For customers with long histories of batch changes - sometimes hundreds deep - this made it time-consuming to locate a specific one.

Now you can simply search by title to quickly narrow the list and jump straight to the change you care about, significantly improving the experience for teams managing large volumes of batch changes.

Announced in January, auto-edit goes beyond traditional autocomplete by analyzing recent edits and suggesting context-aware changes that offers a seamless, non-linear coding experience.

Sourcegraph Analytics now has an Overview page that highlights and explains key value metrics including usage, time saved with Sourcegraph, and Percentage of Code Written (PCW) by Cody.

Our guiding philosophy is to provide users access to the latest and greatest models, and we review model availability based off usage and feedback as older models are replaced by newer ones. With the latest update of Sourcegraph and IDE plugins, we are making the following changes to model availability for Cody Free, Cody Pro, Sourcegraph Enterprise Starter and Enterprise customers who use Cody Gateway.

We are deprecating the following models [...]

OpenAI's latest cost-efficient reasoning model o3-mini was announced last month, and in Sourcegraph 6.1 we are making o3-mini-high available to all Enterprise Starter and Enterprise customers.

o3-mini is purported to be OpenAI's "highest performing released model on SWEbench-verified" for software engineering tasks, and we're excited to provide access to this model to customers.

A few weeks ago we added a major upgrade to the Prompt Library, with the ability to add specific files, repositories, and other context in saved prompts. With this update we've streamlined the UI in the editor by moving all of the 'current' context buttons like Current File and Current Selection into the @-mentions menu, creating a more natural-feeling spot for all of your context options to live in one place.

This change does not break existing prompts that use cody:// syntax and they will function as normal.

We recently announced the experimental version of Cody for Visual Studio, starting with chat functionality to help you understand the code you're working with, and today we're excited to add autocomplete to the latest version of the plugin.

Visual Studio users can now leverage the same autocomplete experience as they would in Cody for VS Code and JetBrains, with Cody providing accurate single and multi-line autocomplete suggestions while writing code.

We're making Sourcegraph more accessible to growing teams! Enterprise Starter is a new plan designed for teams of up to 50 developers, giving them access to powerful code search, AI chat, multi-repo context, and more—all for just $19 per user/month.

What's included:

With Sourcegraph 6.0, we're updating the chat experience by introducing a unified interface that combines AI-powered chat and code search into a single, seamless UI. This update helps you search, understand, and create code faster and more efficiently, whether you're in VS Code, JetBrains IDEs, or using Sourcegraph on the web.

What's new:

Sourcegraph is industrializing enterprise software development with the introduction of AI agents, designed to automate repetitive, time-consuming tasks and accelerate how enterprises build software.

The first available agent, the Code Review Agent, is now in Early Access, with additional agents for code migration, testing, documentation, and notifications coming soon. These agents are customizable, enabling enterprises to address bottlenecks and accelerate progress across large, complex codebases. This allows AI to impact and scale beyond individual developers and across the whole company.

Formerly Cody Analytics, Sourcegraph Analytics now provides customers with aggregate and product-specific metrics for Code Search, Batch Changes, and Code Insights, in addition to the Cody metrics that were previously available. The change in name reflects the new metrics that provide insight into how your developers are interacting with features across the entire Sourcegraph platform, and can help you understand ROI.

Sourcegraph Analytics also includes a CSV export with key metrics like number of searches, chats, autocomplete suggestions, completion acceptance rate (CAR %), and more, by user, day, client, and language — perfect for automating retrieval and analyzing data in ways that make the most sense to your organization.

We're introducing agentic chat to Cody users—a transformative upgrade that makes Cody smarter and more autonomous.

With agentic chat, Cody proactively gathers, reviews, and refines context from your codebase, shell, and the web to deliver high-quality, context-rich responses. Whether generating accurate unit tests, answering complex questions, or retrieving the latest API docs, agentic chat eliminates the need for manual context input, saving time and ensuring precision.

The Prompt Library is getting a major update for teams: the ability to embed specific files, repositories, and other context directly into prompts. This feature enables teams to create precise, reusable prompts tailored to their unique workflows, helping ensure collaboration, consistency, and high-quality outputs across their team.

We're excited to introduce auto-edit, an experimental feature now available in Cody for VS Code. Auto-edit goes beyond traditional autocomplete by analyzing recent edits and suggesting context-aware changes, enabling a seamless, non-linear coding experience.

Prompts provide Cody users the ability to create and share actions that can be tailored specifically to their development workflow. In this month's release, Enterprise users can now add tags to prompts, making it easier to group, organize, and filter prompts for easier discovery in the Prompt Library.

Gemini 2.0 Flash Experimental was announced last week, and we're happy to announce support for Google's latest model across all plans for Cody chat. Google indicates Gemini 2.0 Flash outperforms Gemini 1.5 Pro on key benchmarks at twice the speed, with promising improvements across developer-related benchmarks.

Cody users will now see Gemini 2.0 Flash Experimental in the model selection list for them to use when using chat, and the model is available in the latest versions of Cody for VS Code, JetBrains, and Cody Web. For Cody Enterprise customers, the new model is only available via Cody Gateway. These customers will need to upgrade to the latest release (5.11) and use modelConfig to access the model.

We're excited to announce the release of Cody for Eclipse! Eclipse devs can now natively work with Cody in their editor, including users on all Cody plans (Free, Pro, and Enterprise). This release is experimental, and it includes Cody's chat and Prompts functions.

Ask questions about your code, generate code, and fix code all through Cody chat. You can also automate your work with the Prompt Library. Autocomplete and inline editing capabilities will come in a future release.

While Cody primarily lives in your editor, the broadly trained LLMs it uses under the hood let it answer a wide range of questions beyond just coding. We're introducing a new feature for Cody Enterprise that allows teams to give Cody more prescriptive guidance on what kinds of questions it can answer.

Admins on Cody Enterprise instances can now configure prompt pre-instructions. These are text instructions that Cody uses for every chat query, allowing teams to shape how Cody responds to users. For example, if you don't want Cody to answer questions relating to sensitive non-code matters, you can pre-instruct Cody against them.

Cody is built to support the latest and greatest LLMs interchangeably so that developers always have access to the most powerful code AI solution. For Cody Enterprise customers, we're expanding Cody to be even more flexible and allow admins to select multiple models from multiple providers, which end users can then choose from on-demand.

We're excited to announce general availability for enterprise model election. Cody Enterprise users can now select and hot-swap between multiple model options. Cody Enterprise admins can select which models to provide for users, including models from different providers, including Amazon Bedrock, Azure OpenAI, and Google Cloud Vertex AI.

Currently, Sourcegraph's minimum required version of Postgres, the database management system used for all Sourcegraph instances, is Postgres 12. Postgres 12 is reaching end-of-life and will no longer be supported by Postgres. Because of this, Sourcegraph will be updating our minimum supported version to Postgres 16.

If you are using Sourcegraph's released Postgres images, these images will be updated to Postgres 16 as part of the Sourcegraph 5.10 release and all near-term subsequent releases. With this update, Sourcegraph will experience a longer-than-average downtime at the time of the upgrade to version 5.10 or beyond. This downtime is proportional to the amount of code indexed in your instance and can range from approximately 15 minutes to a couple of hours. The downtime will only occur at the first upgrade to version 5.10 or beyond, and not during any subsequent upgrades.

While Cody's autocomplete and chat functions speed up the inner dev loop, we've consistently heard from engineering leaders that they want more customizable ways to promote code AI best practices across their organization. Organizations that widely adopt code AI tools report better unit test and documentation coverage, not to mention faster issue-to-PR times. One Sourcegraph customer, 1Password, reports that unit tests that used to take a full day to write now take 10 minutes. However, AI coding tools leave much to be desired:

• AI tools today require writing long and cumbersome prompts over and over again, which could have taken longer than writing the code itself
• AI tools require users to go back and forth with the language model and clarify what they want, taking up valuable developer time
• AI tools don't use proper context, so if a developer doesn't use your enterprise's code context or reference best practices, they could end up writing poor quality code

Hey everyone! 👋

We're making our release updates even better! You'll now find more detailed info about what's new between versions in our technical changelog on GitHub.

Cody now supports the updated Claude 3.5 Sonnet and Claude 3.5 Haiku models across all plans.

Anthropic notes that the upgraded version of Claude 3.5 Sonnet has significant gains over its predecessor in coding. Claude 3.5 Haiku matches the performance of Claude 3 Opus on many evaluations at a similar speed to the previous generation of Haiku, meaning that users now get significant reasoning power with snappier responses.

The Prompt Library is a great way for users within an organization to share, discover, and use prompts while working with Cody chat. We've introduced a new concept to Prompts called Promoted Prompts which allows admins to highlight Prompts to users that appear at the top of a Prompt list, directing users to use specific Prompts that encourage best practices within the organization.

Admins can promote a Prompt by checking the Promoted box in the Prompt edit screen.

Perforce allows gating access to individual parts of a depot based on criteria besides username, including by IP address. Previously, Sourcegraph only supported enforcing username-based restrictions to individual files and folders based on the Perforce protections table. In this release, admins can configure their network infrastructure to securely communicate user IP addresses to Sourcegraph, enforcing allow/deny access to individual files and folders based on the user's IP address as well.

Please read our docs for more information.

Announced as part of the 5.6.0 release in August, the new search experience saw significant improvements in speed and simplicity, helping users search, navigate, and find answers about their codebase faster than ever.

Originally available as an opt-in for users, this new experience is now the default in 5.9.0, with the option to opt out back to the old experience.

Hot on the heels of the updates we rolled out to VS Code, the improvements we've made to the Cody sidebar are now available for JetBrains and Cody Enterprise users. Prompt and command use and discovery has been simplified, and we've tidied up the display of draft Prompts so that only drafts you own will appear in the UI.

We are excited to roll out an experimental version of Cody for Visual Studio! This is the first step in the journey to general availability and we'd love to hear your feedback.

This experimental version currently supports chat, and does not support autocomplete or inline editing capabilities.

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.