The August 11, 2026 update to GitHub Copilot for JetBrains introduces two headline capabilities: Copilot Memory, which can carry selected project knowledge and user preferences between agent chat sessions, and Ollama as a bring-your-own-key (BYOK) provider. Memory is in public preview for paid Copilot plans, while the Ollama announcement confirms provider configuration and model selection without publishing a complete setup guide or performance specification.
Those distinctions matter. Memory is not the same as an instruction file, the earlier /memory shortcut, or JetBrains AI Assistant’s local-model feature. Ollama support means you can select Ollama inside the Copilot experience, but the release does not establish which models work, what hardware is required, or how fast they run.
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What changed in the August 11, 2026 JetBrains Copilot release
GitHub’s August 11, 2026 changelog identifies two changes that directly affect how developers use Copilot in JetBrains IDEs:
- Copilot Memory across agent chat sessions: Copilot can retain useful repository facts and personal working preferences so you do not have to restate the same context in later interactions.
- Ollama as a BYOK provider: Ollama can be configured as a provider in GitHub Copilot for JetBrains, and the Copilot experience includes provider configuration and model selection.
GitHub describes the memory benefit as reducing repeated project context. That is a product statement, not an independently measured productivity result; the release provides no benchmark for time saved, response quality, latency, or defect reduction.
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The same changelog reports enterprise controls for plugin availability, MCP server access, permission-bypass behavior, and OpenTelemetry settings. It also reports automatic Copilot CLI installation from integrated terminals on macOS, Linux, and Windows; restored # file and folder references in Copilot, Claude, and Codex chat inputs; account and model-picker refinements; and reliability work involving MCP, terminal output, customizations, cloud agents, and diff editing. These are release items, not separate performance measurements.
How Copilot Memory is organized
Copilot Memory has two distinct scopes. Treating them as separate is essential because they are visible to different people and have different controls.
Repository-level facts
Repository memory covers information about a codebase, such as coding conventions, architectural decisions, build commands, and project rules. GitHub says these facts are available to Copilot Memory users working in that repository. Each stored fact includes citations to supporting code, and Copilot checks the fact against the current branch before using it.
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User-level preferences
User memory contains implied or explicitly stated preferences about how an individual wants to work with Copilot. Those preferences follow the person into later Copilot interactions across repositories rather than belonging to one codebase.
Users can view and delete their own preferences. On Copilot Business and Enterprise plans, administrators can also export or delete preferences. A preference therefore has a broader personal scope than a repository fact, while administrative visibility depends on the plan and organization policy.
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| Memory type | Scope | Examples | Who can manage it |
|---|---|---|---|
| Repository fact | One repository | Coding conventions, architecture choices, build commands, project rules | Repository owners can review and delete |
| User preference | One person across repositories | Stated or inferred ways the user wants to work with Copilot | The user; Business and Enterprise administrators can export or delete |
Availability, policy, and the 28-day expiry rule
Copilot Memory is currently in public preview and available on all paid Copilot plans. GitHub’s documentation states that the feature is subject to change.
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Enablement depends on how the plan is managed:
- Individual plans: Memory is on by default, and the individual user controls whether to opt out.
- Organization- or enterprise-managed plans: An administrator must first enable the Memory policy. After that, individual users can opt out.
The setting is managed through the Copilot Memory toggle in the Copilot settings portal. The toggle controls the feature for the user; it is not a repository setting.
Stored entries also have a lifecycle rule. An unused fact or preference is automatically deleted after 28 days. The timer can reset when Copilot successfully validates and uses that entry. “Unused” therefore does not mean “created 28 days ago”: an entry that is actively validated may remain longer, while an entry that is never used is removed.
What Memory covers—and what it does not
GitHub’s general Memory documentation lists Copilot cloud agent, Copilot code review, Copilot CLI, and agentic autofix as supported surfaces. The JetBrains release separately describes Memory across agent chat sessions. Those statements should not be expanded into a claim that every Copilot interface or every JetBrains chat mode uses identical memory behavior.
In practical terms, a user should expect Memory to help when an eligible Copilot interaction has captured and validated a fact or preference. It is not a universal transcript of every conversation, and it is not a guarantee that Copilot will remember every detail indefinitely.
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Individual users
- Sign in to the GitHub account that owns the paid Copilot plan.
- Open the Copilot settings portal and locate the Copilot Memory toggle.
- Leave the toggle enabled to allow eligible Copilot activity to create and use memory, or disable it to opt out.
- Use the Memory management controls to inspect and delete your saved user preferences.
The release documentation does not specify a separate per-repository activation step. Repository facts are governed by the user’s Memory status and the repository’s eligibility, while repository owners receive review and deletion controls for facts associated with their codebase.
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Organization and enterprise administrators
- Enable the Copilot Memory policy for the organization or enterprise in the applicable administrative settings.
- Tell users that they can opt out individually after the policy is enabled.
- For Business and Enterprise plans, use the available administrative controls to export or delete user preferences when governance or offboarding requires it.
- Ask repository owners to review repository facts and remove entries that are obsolete or inappropriate.
Because the feature is in public preview, administrators should document how their organization handles review, deletion, and user opt-out rather than assuming the preview behavior will remain unchanged.
What Ollama support means in GitHub Copilot for JetBrains
The August release makes a precise claim: “You can now use Ollama as a BYOK provider in GitHub Copilot for JetBrains.” In the Copilot experience, users can configure the provider and select a model. That is enough to establish provider availability, but not enough to publish a complete installation recipe.
The announcement does not specify:
- a minimum Ollama version;
- a list of compatible Ollama models;
- context-window limits or maximum prompt sizes;
- CPU, GPU, memory, or operating-system requirements;
- expected latency, throughput, or response quality;
- whether every Copilot feature supports every selected model; or
- an exact JetBrains menu path for adding the provider.
Do not infer those details from unrelated Ollama integrations. Model compatibility and hardware needs can vary by model and by Copilot capability, and the August announcement does not publish a matrix.
What general local BYOK documentation adds
GitHub’s general BYOK documentation says local BYOK is supported in JetBrains and other clients. It also says local keys are handled client-side and stored locally. Those are general local-BYOK behaviors; they should not be presented as an Ollama-specific data-flow guarantee beyond what GitHub documents for the local BYOK mechanism.
For Copilot Business and Enterprise users, an organization or enterprise policy can disable local BYOK. If Ollama does not appear for a managed account, an administrator policy is one possible explanation, alongside account, client, or provider configuration issues.
Copilot’s Ollama integration versus JetBrains AI Assistant
JetBrains AI Assistant separately documents using local models through Ollama. That documentation belongs to a different product and a different configuration path. Installing or configuring Ollama for AI Assistant does not prove that the same model list, endpoint settings, permissions, or feature coverage apply to GitHub Copilot.
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| Question | GitHub Copilot for JetBrains | JetBrains AI Assistant |
|---|---|---|
| Product involved | GitHub Copilot | JetBrains AI Assistant |
| Ollama status in the cited documentation | Ollama is announced as a BYOK provider with provider configuration and model selection | Local models through Ollama have their own documented setup |
| Can one setup guide be assumed to apply to the other? | No | No |
Choose the configuration instructions for the product you are actually using. A local model configured in AI Assistant is not automatically a Copilot provider, and a Copilot BYOK selection does not configure AI Assistant.
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Copilot Memory versus instruction files
Memory is captured from eligible Copilot activity and then validated according to GitHub’s documented rules. Instruction files are authored guidance that a team or user maintains deliberately. They solve related but different problems.
| Approach | How content is created | Typical scope | Best use |
|---|---|---|---|
| Copilot Memory | Copilot captures repository facts or user preferences and validates them before use | Repository facts or one user’s cross-repository preferences | Reducing repeated context that emerges during normal Copilot work |
| Repository instruction file | A developer or team writes and maintains the guidance | Repository-wide | Stable project rules that should be reviewed like other project configuration |
| Global instruction file | A user writes and maintains the guidance locally | The user’s Copilot sessions | Consistent personal conventions across projects |
GitHub’s JetBrains documentation identifies .github/copilot-instructions.md for repository-wide instructions and global-copilot-instructions.md for global instructions. These files remain under the author’s control and can be reviewed in the normal way. Memory should not be treated as a hidden replacement for a rule that every contributor must see.
Do not confuse /memory with Copilot Memory
A March 11, 2026 JetBrains Copilot update introduced /memory as a shortcut to instruction-file settings and announced support for files including AGENTS.md and CLAUDE.md. That shortcut concerns instruction settings. The August feature named Copilot Memory is the separate persistent-memory system for repository facts and user preferences.
Choosing the right mechanism for a project
Use an instruction file for non-negotiable rules
Put requirements such as formatting conventions, mandatory build commands, architectural boundaries, or review procedures in an authored instruction file when every Copilot user should receive the same guidance. A file can be changed through the repository’s normal review process and is visible to collaborators.
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Repository Memory is useful for facts Copilot can support with citations to the code and verify against the current branch. Examples include an established module relationship, a project-specific build invocation, or a convention that appears consistently in the repository.
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Use user preferences for personal workflow choices
A preference about how one developer wants Copilot to format explanations or structure interactions belongs at user scope rather than in a shared repository rule. Remember that user preferences can apply across repositories and are subject to the user’s and, on managed plans, administrators’ controls.
Administration and governance questions
- Who can turn Memory on? Individual-plan users receive it enabled by default; organization and enterprise administrators must enable the policy before users can use it.
- Who can delete repository facts? Repository owners can review and manually delete them.
- Who can delete user preferences? Users can delete their own preferences. Business and Enterprise administrators can export or delete preferences.
- How long does an unused entry remain? It is automatically deleted after 28 days, although successful validation and use may reset the timer.
- Can managed accounts use local BYOK? They can only do so if the organization or enterprise policy permits local BYOK.
These controls make Memory manageable, but they do not turn preview functionality into a permanent retention contract. Organizations should account for the 28-day cleanup rule and the possibility that preview behavior or policy controls will change.
How to evaluate the Ollama update without overclaiming
If you are deciding whether to try Ollama in Copilot, separate the confirmed capability from the questions you still need to answer in your own environment:
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- Confirm that your Copilot account and JetBrains client expose Ollama as a provider.
- Check which model choices the provider picker actually presents to your account.
- Verify that the selected model supports the Copilot workflow you intend to use, such as chat or agent operations.
- Measure response time and output quality on your own codebase rather than relying on a release announcement.
- Ask an administrator whether local BYOK is disabled for a Business or Enterprise organization.
- Review local key handling and organizational data policies before connecting a provider.
The current official announcement does not establish a universal hardware recommendation, a preferred model, or a performance winner. Any such conclusion would require separate, documented testing.
Bottom line
For JetBrains developers, the August 11, 2026 Copilot update adds persistent Memory with repository and user scopes, plus Ollama as a selectable BYOK provider. Memory is a public-preview feature with policy-dependent enablement, owner and administrator controls, and a 28-day unused-entry cleanup rule. Ollama support confirms provider configuration and model selection, but leaves compatibility, hardware, setup details, and performance to be determined rather than promised. Keep Memory distinct from authored instruction files, the /memory shortcut, and JetBrains AI Assistant’s separate Ollama integration.
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