Skip to main content

Posts

GitHub Copilot SDK Deep Dive: Session Memory

The GitHub Copilot SDK just shipped a new feature: optional memory configuration on session create and resume. Here is what it does, and how it is different from persisted sessions. The wrong mental model first When I heared "session memory" my first thought was "persisted sessions" — the ResumeSessionAsync flow that lets you reload an existing session by ID and continue where you left off. That is not what this is. Persisted sessions are about durability of the conversation itself: close the app, reopen it, pick up the thread. Memory configuration is something different. What memory configuration actually does Memory is a feature of the Copilot runtime that lets the agent read and write facts across turns — a kind of long-running knowledge store that the agent can consult and update during a session. Think of it as the agent's notepad, not the conversation log. The new MemoryConfiguration type exposes a single Enabled flag today. You opt in per se...
Recent posts

Scheduling actions in the GitHub Copilot CLI

The GitHub Copilot CLI keeps getting more capable. One of the newer additions is the ability to schedule prompts, either on a repeating interval or as a one-shot delayed action. Let me walk you through both approaches. Two ways to schedule The /every command schedules a prompt to run repeatedly at a specified interval, while /after schedules a one-shot prompt to run once after a specified delay. Both commands are still experimental. They are only available if you have used the /experimental on slash command, or the --experimental command-line option first. Use the following slash command to enable experimental mode in your session: /experimental on Recurring prompts with /every Use /every when you want Copilot to repeat a task on a cadence during your session. /every 10m Run the test suite and summarize any new failures /every 1h Check for new comments on my open pull requests A number with no suffix is interpreted as minutes — so /every 30 remind me to check for...

Configuring Copilot CLI Isolation via the GitHub Copilot SDK

In the previous post, we walked through local sandboxing in the Copilot CLI: enable it with /sandbox enable , tune filesystem and network rules through the TUI, and your agent's shell execution is isolated by Microsoft MXC. Simple, useful, done. But if you're building with the Copilot SDK, embedding the agent runtime into your own .NET application, you can't type /sandbox enable into a session you're programmatically orchestrating. So the question becomes: how do you get the same isolation guarantees when you own the host? The good news: sandbox support is coming to the SDK as a preview feature. The entry point is Session.Rpc.Options.UpdateAsync , and it lets you push a sandbox configuration into a running session from code. Preview caveat : this API is behind the experimental surface of the SDK. It's real, it works, but the shape may change before it stabilises. Treat it as preview-quality and don't build production contracts on top of it just yet. Wha...

Local sandboxing in the GitHub Copilot CLI

There's a moment in every agentic workflow where you pause and think: wait, what exactly is Copilot allowed to touch right now? For a long time the answer was: pretty much everything under your working directory and whatever shell commands it decides to run to get the job done. That was fine when Copilot was mostly suggesting code. It's a different story when it's running tools, executing scripts, and modifying files on your behalf. As of June 2026, GitHub has an answer: local sandboxing , now in public preview. It doesn't replace good judgment about what you ask Copilot to do, but it does put a real isolation boundary between the agent's tool execution and the rest of your machine. Let’s explore this feature… Why do we need this? The Copilot CLI has evolved significantly since GA. What started as a smart terminal assistant now has Autopilot mode, /plan , fleet parallelism, rubber duck, and a full agentic harness underneath. When you run Copilot in Autopil...

Why my Azure DevOps scheduled pipeline never ran

I set up a scheduled pipeline in Azure DevOps. The YAML was valid. No errors on save. I waited patiently for the cron to fire. Nothing happened… The culprit turned out to be a single line I'd added for a completely legitimate reason trigger: none . The setup The pipeline looked roughly like this: trigger: none schedules: - cron: "0 2 * * 1-5" displayName: Nightly weekday build branches: include: - main always: true The intent was straightforward: I didn't want CI runs on every push, so I explicitly disabled that with trigger: none . And I wanted the pipeline to run on a schedule. Seems fine, right? Except it never ran. What's actually happening Here's the thing that isn't obvious until you read the docs carefully (or waste an afternoon debugging): in Azure DevOps YAML pipelines, trigger is specifically the CI trigger — the thing that fires on code pushes. schedules is a completely separate concept. So whe...

GitHub Copilot SDK Deep Dive: CopilotClientMode

By default, the CopilotClient starts in CopilotCli mode. That means the full Copilot CLI persona is active — which includes a lot: All built-in tools available (subject to the ToolSet filtering you do per session) Host integration enabled: the CLI picks up your local ~/.copilot/ config, agents directory, plugins, and AGENTS.md files if they exist The default system prompt with the full Copilot identity Co-author trailers added to git commits Storage backed by the local filesystem at the default path For a developer using the SDK on their own machine to automate their own workflows, this is perfect. The agent behaves exactly like Copilot CLI would interactively. Context flows in from their environment, their local agent configs are respected, their Copilot persona is preserved. The multi-tenant problem The moment you start running the SDK as a service — where one process handles sessions for multiple users or tenants — default mode becomes a liability. ...

Shining a light on .NET versions across our organisation with OpenTelemetry – The Azure Monitor edition

In a previous post I showed how to add the .NET runtime version as an OpenTelemetry resource attribute: ResourceBuilder.CreateEmpty() .AddService($"{_sofaSettings.ApplicationName}-{_sofaSettings.EnvironmentName}") .AddAttributes(new Dictionary<string, object> { ["deployment.environment"] = _sofaSettings.EnvironmentName, ["service.name"] = _sofaSettings.ApplicationName, ["runtime.dotnet.version"] = Environment.Version.ToString() }) .Build(); The idea was clean: attach facts about what is running directly to the resource, and let OpenTelemetry carry them along with every trace, metric, and log automatically. Unfortunately, there is a catch. The problem Azure Monitor's OpenTelemetry exporter only maps a fixed set of well-known resource attributes onto Application Insights fields. service.name and service.namespace become Cloud Role Name, service.instance.id becomes Cloud Role Insta...