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VS Code 1.115 Ships the Agents App — Run Parallel Agent Sessions Across Multiple Repos
April 11, 2026

VS Code 1.115 Ships the Agents App — Run Parallel Agent Sessions Across Multiple Repos

Released April 8, VS Code 1.115 introduces the VS Code Agents companion app (preview, Insiders only): a dedicated application for running parallel agent sessions across multiple repositories simultaneously, each isolated in its own worktree. It ships alongside a comprehensive GitHub blog post summarizing VS Code releases v1.111 through v1.115 — the full March and early April arc of Copilot agent improvements — making this week both a forward-looking release and a useful retrospective for anything you missed over the past month.

VS Code + GitHub Copilot

4 updates

VS Code 1.115 ships the VS Code Agents companion app (preview), a standalone application that runs alongside VS Code Insiders and is purpose-built for agent-native development. It lets you kick off agent sessions across multiple repositories in parallel, each isolated in its own worktree. A context-switching UI lets you track session progress, view diffs inline, leave feedback, and create pull requests without switching windows. All your existing customizations carry over: custom instructions, prompt files, custom agents, MCP servers, hooks, and plugins. No separate install required — it ships with VS Code Insiders and is accessible from the Command Palette via Chat: Open Agents Application.

Key Takeaway: As a tech lead managing multiple microservices, you can now run a Java API refactoring agent, an Angular UI build agent, and a test-writing agent concurrently across three separate repos — monitoring all of them from one window while you focus on code review.
  1. Install or update to VS Code Insiders.
  2. Open the Command Palette and run Chat: Open Agents Application, or find it in your Start menu / Applications folder.
  3. From the Agents app, start a new session and choose a repository. The app creates an isolated worktree for each session.
  4. Start additional sessions across other repos from the same app window.
  5. Use the context-switching UI to monitor all sessions, review diffs, and create PRs without leaving the app.
Real Example: You need to update a shared API contract across your user-service, payment-service, and Angular frontend simultaneously. Start three parallel agent sessions in the Agents app — one per repo — monitor all three diffs in parallel, and merge when all three are aligned.

Previously, background terminals in agent sessions were read-only — agents could check output via get_terminal_output but could not respond to prompts. VS Code 1.115 adds the send_to_terminal tool, allowing agents to continue interacting with background terminals. Alongside this, an experimental chat.tools.terminal.backgroundNotifications setting automatically notifies the agent when a background terminal finishes or requires input, eliminating the need for the agent to poll manually.

Key Takeaway: Long-running build or deployment scripts that hit an interactive prompt mid-run no longer stall an agent session — the agent can detect the prompt and respond automatically.
  1. Update VS Code to 1.115.
  2. To enable background notifications: add "chat.tools.terminal.backgroundNotifications": true to settings.json (experimental).
  3. Start an agent session and kick off a long-running terminal command (e.g., a Spring Boot integration test suite).
  4. If the command requires input (password prompt, confirmation), the agent is automatically notified and can respond using send_to_terminal.
Real Example: An agent runs a Docker Compose setup that prompts for a registry password mid-run. With send_to_terminal and background notifications, the agent detects the prompt, sends the credential, and continues the setup — no manual intervention needed.

VS Code 1.115 brings three quality-of-life improvements to the integrated browser for agent sessions. The Run Playwright Code tool now handles long-running scripts (over 5 seconds by default) by returning a deferred result for the agent to poll, rather than timing out. Agents are now strongly discouraged from opening duplicate browser tabs — if a tab is already open to the same host, no new tab is opened unless explicitly requested. Tool call labels are now more descriptive with a direct link to the relevant browser tab.

Key Takeaway: Agent sessions driving browser-based test suites or end-to-end Playwright tests no longer fail or produce tab sprawl when a script runs longer than a few seconds.

GitHub published a consolidated summary of all VS Code Copilot changes shipped across March and early April (versions 1.111–1.115). Key items if you missed any: Autopilot for fully autonomous agent sessions (no approval dialogs), configurable thinking effort per session directly from the model picker, integrated browser debugging, image and video attachment support in chat, nested subagents (chat.subagents.allowInvocationsFromSubagents), the unified chat customizations editor (Preview), MCP servers bridged into Copilot CLI sessions, and session forking.

Key Takeaway: If you have been following weekly but missed the impact of any of the March features, this post is the authoritative single-page summary — worth sharing with your team as a Copilot onboarding reference.

GitHub.com Copilot

5 updates

Copilot cloud agent's built-in security and quality checks — CodeQL, GitHub Advisory Database, secret scanning, and Copilot code review — now run in parallel rather than sequentially, reducing total validation time by 20%. These checks fire automatically every time the cloud agent writes code, and the agent attempts to resolve any issues found before completing work and requesting review. A new setting in the Copilot → Cloud agent section of repository settings lets you configure which validation tools run for each repo.

Key Takeaway: Every PR the cloud agent creates now gets security-scanned 20% faster, and you can tune per-repo which checks run — useful for repos where CodeQL would be too slow or advisory checks are redundant.

GitHub Mobile now exposes the full Copilot cloud agent workflow on both iOS and Android: research your codebase, generate an implementation plan before writing code, make changes on a branch without immediately opening a PR, review the diff and iterate, and create a pull request when ready. If you include it in your prompt, the agent will create the PR automatically when the session completes. This extends last week's Mobile Copilot tab refresh with deeper agent action support.

Key Takeaway: You can now start a codebase research session from your phone during your commute, hand off to an implementation plan, approve it, and have a draft PR waiting when you reach your desk.
  1. Update the GitHub app on iOS (App Store) or Android (Google Play) to the latest version.
  2. Open the Copilot tab from the navigation bar.
  3. Tap the compose button and start a new cloud agent session on any repository.
  4. Ask Copilot to research a question, generate a plan, or make a change on a branch.
  5. Review the diff in the session view. Iterate with follow-up messages.
  6. Tap "Create pull request" when satisfied — or include "open a PR when done" in your original prompt for automatic PR creation.
Real Example: On your commute, ask Copilot via Mobile to "research why our Spring Boot app occasionally throws a NullPointerException during startup and propose a fix." By the time you open your laptop, a plan and branch are ready for your review.

Organization admins and security managers can now launch a Copilot chat session directly from secret risk assessment or Code Security risk assessment result pages. Copilot provides contextual explanations of findings and guided remediation steps — no need to copy scan results into a separate chat window and re-explain the context. Available to orgs with GitHub Advanced Security.

Key Takeaway: Security findings now have a "Ask Copilot" entry point built in — a significant reduction in the friction of going from "here is a vulnerability" to "here is how to fix it" for security and DevOps teams.

GitHub is retiring Opus 4.6 Fast for Copilot Pro+ users starting April 10 to streamline model offerings and improve infrastructure reliability. Simultaneously, new usage limits are being rolled out over the next few weeks: a service reliability limit (session-level, wait for reset when hit) and a model/family capacity limit (switch to an alternative or use Auto mode when hit). The changes are driven by high-concurrency patterns straining shared infrastructure.

Key Takeaway: If you rely on Opus 4.6 Fast in Pro+, switch to Opus 4.6 now — similar capability without the quota risk. Enable Auto mode for day-to-day work to avoid hitting model-family limits and to receive the 10% premium request discount.

GitHub has paused new Copilot Pro free trials due to a significant rise in abuse of the free trial system. Existing trials are unaffected. No timeline has been given for when new trials will resume. Paid subscriptions (Pro, Pro+, Business, Enterprise) continue without interruption. This is a service protection measure and not a product change.

Key Takeaway: If you were planning to onboard a new developer to Copilot via a free trial, that path is temporarily unavailable. Direct them to the paid Pro plan or a Business seat instead while trials are paused.

Microsoft Copilot for Enterprise

3 updates

Microsoft 365 Copilot Chat is now accessible across Teams chats, channels, calling, and meetings — expanding beyond its previous limited scope to everywhere users collaborate. Alongside this, Copilot's code interpreter can now analyze files surfaced through enterprise search in Copilot Chat even if they were not manually uploaded, and Declarative Agents can now interpret embedded images in Word, PowerPoint, and PDF files to extract insights from charts, diagrams, and screenshots.

Key Takeaway: Copilot is now present in every Teams context — you no longer need to navigate away to a dedicated Copilot pane to ask a question during a channel discussion or a call. And the code interpreter can now analyze attached reports found via enterprise search, not just files you explicitly upload.

Two new Copilot Studio Wave 1 (April–September) features have entered preview this month: MCP-compliant tools in agent workflows (Preview April, GA October) — allowing agents to call any MCP-compatible external tool — and custom metrics for analytics (Preview April, GA May), letting admins define their own success metrics for agent evaluation. Also newly in preview: configure triggers with end-user credentials, and credentials oversharing detection for safer agent sharing.

Key Takeaway: MCP tools in Copilot Studio workflows entering preview now means you can start prototyping agents that call your internal Java APIs or data services via MCP — targeting GA in October 2026.

Two M365 Copilot quality-of-life improvements this week. First, Copilot now reduces the number of confirmation prompts shown during read-only actions — operations that do not modify external systems no longer require approval clicks, while safety checks remain intact for write actions. Second, a new option in Windows File Explorer and the OneDrive Activity Center lets you generate a Copilot summary of a file and include it directly in the share dialog, saving the step of summarizing separately before sharing.

Key Takeaway: Agents that do a lot of data-gathering (reading emails, querying SharePoint, fetching calendar data) are now dramatically less interruptive for enterprise users — fewer clicks to get to the output that matters.

Community Picks

3 picks
GitHub Blog · April 8, 2026

The GitHub-published summary of VS Code releases v1.111–1.115 reads like the most useful onboarding document for Copilot agent mode produced so far. Developers on Reddit and X are circulating it as the definitive "catch-up" for anyone who missed the rapid weekly cadence. Among the most-shared takeaways: agent-scoped hooks (define pre and post hooks in YAML frontmatter of .agent.md files without affecting other agents) and monorepo customization discovery (parent folder traversal to the Git root).

Key Takeaway: Agent-scoped hooks let you define pre- and post-processing logic per custom agent — for example, auto-run a linter before every file edit the Java API agent makes, without affecting your Angular UI agent.
YouTube · March 2026

A detailed walkthrough of using Copilot Agent Mode and Plan Mode in IntelliJ IDEA covering the three modes (Chat, Edits, Agent), how Agent Mode researches your existing controllers, database models, service layers, and repository patterns before writing code, and how Plan Mode generates a high-level architecture review before implementation. Covers model selection (GPT-4o, Claude Sonnet, Gemini) and how context management works at the IntelliJ level.

Key Takeaway: Start every large Agent Mode task in IntelliJ by switching to Plan Mode first. The generated plan surfaces missing context (missing service layers, unresolved dependencies) before any code is written — catching scope gaps that would otherwise waste premium requests mid-implementation.
GitHub Changelog · April 10, 2026

Two metrics changes landed this week that enterprise admins and team leads managing Copilot rollouts will care about. First, CLI activity is now integrated into the top-level Copilot usage metrics API totals, including code generation activity, acceptance counts, lines added/deleted, and dimensional breakdowns by feature, model, and language. Second, cloud agent active user counts (daily, weekly, monthly) are now aggregated into enterprise and organization reports, reflecting the rename from "coding agent" to "cloud agent."

Key Takeaway: If you manage Copilot adoption metrics for your team, your usage dashboards now finally show a single unified number that includes CLI sessions — no more manually stitching together separate reports to justify ROI.
Phani's Pick of the Week

VS Code Agents App — Parallelize Agent Work Across Your Microservices

The VS Code Agents companion app (available now in VS Code Insiders) is the highest-leverage item this week for a Java fullstack tech lead managing multiple repos. The ability to run three or four agent sessions simultaneously — one per microservice — each in its own isolated worktree, while monitoring all diffs from one window, fundamentally changes how agentic work scales across a service-oriented codebase. Enable it in Insiders today, run it alongside your stable VS Code for a week, and identify which repetitive cross-service tasks (dependency updates, API contract changes, test scaffolding) benefit most from parallel delegation.

— End of April 11, 2026 edition —
Archive
Copilot SDK Goes Public Preview in Java, Python, Go, .NET and Node.js
April 4, 2026

Copilot SDK Goes Public Preview in Java, Python, Go, .NET and Node.js

The GitHub Copilot SDK is now publicly available in five languages including, for the first time, Java via Maven. It exposes the same production agent runtime that powers Copilot CLI and the cloud agent — giving any application or internal tool the ability to embed planning, tool invocation, streaming, and multi-turn sessions without building a custom AI orchestration layer. Combined with BYOK support for OpenAI, Azure AI Foundry, and Anthropic, this is the most significant extensibility milestone since Copilot CLI went GA in February.

VS Code + GitHub Copilot

4 updates

Released April 1, VS Code 1.114 focuses on reducing friction in the chat workflow. The standout additions are a "Copy Final Response" command that strips out agent thinking and tool call noise before copying to clipboard, unified codebase indexing that removes the local-vs-remote split, and the ability to reference any previous chat session inside /troubleshoot for after-the-fact diagnosis.

Key Takeaway: Copying a Copilot response to paste into a PR description or doc no longer drags along internal agent logs — Copy Final Response gives you clean Markdown output every time.
  1. Copy Final Response: Right-click any chat response and choose "Copy Final Response" to get only the last Markdown section after all tool calls have run.
  2. Simplified #codebase search: No more local vs remote index management. One state: semantically indexed or not. Copilot builds the index on demand. Workspaces previously using a local non-semantic index will need reindexing.
  3. /troubleshoot with session picker: Use /troubleshoot #session to trigger a session picker and investigate past sessions after the fact, without reproducing the issue.
  4. Video support in image carousel: imageCarousel.chat.enabled now supports video playback in addition to images.
  5. Edit Mode officially deprecated: Removed in 1.125. Temporarily re-enable with chat.editMode.hidden until then.
Real Example: You had a Copilot session last Tuesday where custom instructions were ignored. In today's session, type /troubleshoot #session, pick last Tuesday's session from the picker, and Copilot reads the debug logs and tells you what went wrong — no need to reproduce it.

A new proposed API in 1.114 lets tool authors scope approval flows to a specific combination of tool plus arguments. Previously, approving the "Run VS Code Command" tool meant approving all commands. Now a tool can prompt "Allow running editor.action.formatDocument?" separately from other commands, so users grant narrow, targeted permissions rather than broad blanket approvals for dangerous operations.

Key Takeaway: Teams building internal Copilot tools can now give users precise control — approve safe file reads without also approving destructive writes or shell execution.
  1. Use the approveCombination field on LanguageModelToolConfirmationMessages to label the specific approval.
  2. When set, VS Code displays a button for the user to approve that exact tool+argument combination.
  3. Approvals are scoped — approving "Allow reading foo.txt" does not approve reading other files.
  4. This is a proposed API in 1.114 — enable it for extension development via the VS Code insiders channel.
Real Example: You build an internal Java dependency-checker Copilot tool. With fine-grained approval, the tool can ask "Allow checking pom.xml for vulnerabilities?" and the developer approves just that file — not all file reads.

VS Code 1.114 adds a group policy key Claude3PIntegration that administrators can use to disable the Claude agent integration in Copilot Chat org-wide. When applied, the github.copilot.chat.claudeAgent.enabled setting is managed by the organization and users cannot override it. Aimed at enterprises with data residency or model-approval requirements.

Key Takeaway: Enterprise admins can now lock out Claude models from Copilot Chat via device management policy without requiring users to change settings manually — critical for regulated environments.

Visual Studio 2026's latest release notes surface three Copilot additions: custom agents via .agent.md files with full workspace awareness and MCP connections; a "Profile with Copilot" command in Test Explorer that runs a chosen test, analyzes CPU and instrumentation data, and delivers actionable insights; and automatic NuGet vulnerability detection and resolution directly from Solution Explorer.

Key Takeaway: VS 2026 users can now build custom Copilot agents tailored to team workflows — define tools, instructions, and MCP connections in an .agent.md file and they appear in the agent picker automatically.

GitHub.com Copilot

4 updates

The GitHub Copilot SDK is now in public preview across Node.js/TypeScript, Python, Go, .NET, and — newly — Java via Maven. It exposes the same agent runtime that powers Copilot CLI and the cloud agent, providing tool invocation, streaming, multi-turn sessions, blob attachments, OpenTelemetry tracing, and a permission framework out of the box. BYOK support lets enterprises use their own OpenAI, Azure AI Foundry, or Anthropic keys. Available to all subscribers including Copilot Free.

Key Takeaway: Java developers can now embed Copilot's full agent runtime directly into Spring Boot apps or internal tooling via Maven — without building a custom orchestration layer.
  1. Install (Java): Add the GitHub Copilot SDK dependency via Maven to your pom.xml.
  2. Install (Node.js): npm install @github/copilot-sdk
  3. Install (Python): pip install github-copilot-sdk
  4. Define custom tools with handlers — the agent decides when to invoke them.
  5. Use replace, append, or prepend callbacks to customize the Copilot system prompt without rewriting it entirely.
  6. Gate sensitive operations with approval handlers; mark read-only tools to skip approvals.
  7. Each prompt counts toward your premium request quota for paid Copilot subscribers.
Real Example: Build an internal Java microservice that, when given a failing test name, uses the Copilot SDK to analyze the test, trace the stack, and produce a structured fix report — delivered as an API response with full streaming support.

Copilot cloud agent (formerly "Copilot coding agent") drops the requirement to always create a pull request. It can now generate code on a branch and let you review the full diff before deciding to open a PR. Added alongside this: a plan mode where Copilot generates and presents an implementation plan for your approval before writing any code, and a deep research mode for broad codebase questions grounded in repository context.

Key Takeaway: You can now ask "how does our auth module handle session expiry?" and get a deep research answer grounded in your actual code — or request a plan and review the approach before a single line is written.
  1. Branch without PR: Start an agent session from the Agents tab. Copilot generates code on a branch. Click "Diff" to review changes. Click "Create pull request" only when ready.
  2. Plan mode: Include "create a plan" or "plan first" in your prompt. Copilot generates a structured plan, waits for your approval, then implements.
  3. Deep research: Ask a broad question like "why does our payment service occasionally timeout?" from a Copilot Chat conversation. Copilot kicks off a research session grounded in your repo.
Real Example: Before starting a complex API migration, ask Copilot to "plan the migration of our REST endpoints to GraphQL." Review the 8-step plan, adjust scope, approve — then let Copilot implement while you attend standup.

GitHub Mobile's Copilot experience gets a major refresh on both iOS and Android. On Android, Copilot moves into the navigation bar as a dedicated tab. A new Home experience shows agent sessions and chat history at a glance, with a session list that filters by state and updates in real time. New in-app actions include viewing full session logs natively, creating a pull request from a completed session, reviewing the PR, and stopping a running session.

Key Takeaway: You can now manage the full Copilot agent lifecycle — monitor progress, review diffs, create PRs — from your phone without opening a browser or laptop.

As reported last week, starting April 24 GitHub will use Copilot Free, Pro, and Pro+ interaction data — including accepted completions, code snippets, cursor context, file names, and chat content — to train AI models unless users opt out. Community reaction has been strongly negative, with developers calling the opt-in-by-default approach a dark pattern. Importantly: users who are members of or outside collaborators with a paid GitHub organization are excluded regardless of their personal subscription tier.

Action Required: If you are on a personal Pro or Pro+ plan and are not a member of a paid organization, go to GitHub Settings > Privacy > "Allow GitHub to use my data to improve GitHub Copilot" and disable it before April 24.

Microsoft Copilot for Enterprise

3 updates

Microsoft's 2026 transformation of M365 Copilot is now in full rollout. Copilot Cowork enables delegating multi-step background tasks with checkpoint reviews — drafting, sending, scheduling, organizing across apps. Work IQ gives Copilot organizational memory: it understands roles, communication patterns, past decisions, and task histories to produce contextually relevant assistance. Agent Mode is rolling out in Word, Excel, Outlook, and PowerPoint, enabling continuous refinement rather than one-shot generation.

Key Takeaway: With Work IQ, Copilot in Teams or Outlook now understands how your team works — it can prioritize tasks by urgency, recall past decisions, and make multi-step workflow suggestions grounded in your organization's actual patterns.

Microsoft's 2026 Wave 1 release plan is published, covering new Copilot features from April through September 2026. General availability began April 1. Highlights include richer Sales Chat and Sales Home experiences in Copilot for Sales, configurable record summaries for deals and accounts, new governance and extensibility controls for scaling AI responsibly, and improved email and meeting intelligence in Teams and Outlook.

Key Takeaway: If your organization is evaluating M365 Copilot rollout for the next two quarters, the Wave 1 plan is the definitive roadmap — it lists GA dates and milestone commitments through September 2026.

Microsoft's Azure Dev Community published a model selection guide mapping development tasks to the right Copilot model tier. Key framework: lightweight models (Claude Haiku 4.5, Gemini 3 Flash) for quick edits; general-purpose coding models (GPT-4.1, GPT-5-mini, Claude Sonnet) for daily work; deep reasoning models (GPT-5.1, Gemini 3 Pro, Claude Opus 4.5) for architecture and debugging; agentic models (GPT-5.2-Codex) for repo-wide multi-step changes. Auto mode also gets a 10% premium request discount in Copilot Chat.

Key Takeaway: Use Auto mode for day-to-day work to get the 10% discount and avoid manual model management. Switch to a deep reasoning model explicitly only when doing architecture design, complex debugging, or repo-wide refactoring.

Community Picks

3 picks
YouTube · March 27, 2026

A deep-dive tutorial evolving a basic M365 Copilot agent into a full autonomous workplace automation agent using VS Code, GitHub Copilot, Copilot Studio, and Work IQ. The agent detects and replies to emails, saves attachments to OneDrive, edits documents based on email instructions, and sends Teams notifications — all generated from a single natural language plan in VS Code agent mode. Demonstrates how to move agents from Copilot Agent Builder into Copilot Studio and add MCP tools for Teams, Outlook, Word, and OneDrive.

Key Takeaway: You can describe a multi-app automation workflow in plain English inside VS Code agent mode, and Copilot generates the entire Copilot Studio agent configuration — a pattern directly applicable to any enterprise workflow automation.
DEV.to · March 2, 2026

A detailed breakdown of the Copilot CLI GA milestone, covering what GA actually means for stability and SLAs, the six versions shipped that week, and practical workflow patterns. Key features highlighted: Plan mode (Shift+Tab), Autopilot mode, background delegation with & prefix, specialized built-in agents (Explore, Task, Code Review, Plan), auto-updates via Homebrew/WinGet, and cross-session repository memory. The article frames it as a shift from tool to infrastructure.

Key Takeaway: Prefix any prompt with & to delegate a task to the cloud Copilot coding agent while your terminal stays free for other work — use /resume to switch between local and cloud sessions.
YouTube · VS 2026

Real-world lessons from extensive use of GitHub Copilot Agent Mode in Visual Studio 2026. Practical findings: Claude Haiku 4.5 offers the best speed-to-cost ratio for C#/.NET; use free models to read specs and premium models to write code; tasks creating 70+ entities can take 3+ hours so interrupt and use PowerShell scripts instead; always confirm what Copilot can "see" before starting large tasks; old and new solutions must share a parent folder for rewrites.

Key Takeaway: Ask Copilot to generate scaffolding PowerShell scripts, then run them manually for speed — for repetitive structural tasks this is 10x faster than letting Agent Mode do it file by file.
Phani's Pick of the Week

Copilot SDK via Maven — Embed Agent Intelligence into Your Java Services

The Copilot SDK going public preview with Java support via Maven is the most directly actionable item this week for a Java fullstack tech lead. You can now add the SDK to any Spring Boot service and embed Copilot's full agent runtime: define custom tools, stream responses, attach binary data, and gate sensitive operations with approval handlers — all without building your own LLM orchestration. Start with a single internal tool (e.g., an automated code-review summary service or a dependency vulnerability reporter), test with BYOK using your own API key, and measure the reduction in manual review time before expanding to the team.

— End of April 4, 2026 edition —
Archive
VS Code 1.113 Ships — Nested Subagents, MCP in CLI, and Configurable Thinking Effort
March 28, 2026

VS Code 1.113 Ships — Nested Subagents, MCP in CLI, and Configurable Thinking Effort

Released March 25, VS Code 1.113 is the most agent-focused release yet: subagents can now invoke other subagents for multi-step workflows, MCP servers you configure in VS Code are bridged directly into Copilot CLI and Claude agents, and reasoning effort (low/medium/high) is now controllable from the model picker UI. This release, combined with the Copilot CLI having six point releases this week alone, signals the terminal and editor are converging into a single agentic platform.

VS Code + GitHub Copilot

6 updates

VS Code 1.113 introduces chat.subagents.allowInvocationsFromSubagents, enabling subagents to call other subagents. Previously blocked to prevent infinite recursion, this unlocks genuinely complex multi-step agentic workflows where a coordinator agent delegates specialized tasks to role-specific subagents — all within a single chat session.

Key Takeaway: Build an orchestration layer where a "Project Manager" agent delegates code tasks to a "Java API Agent" and UI tasks to an "Angular Agent" — no manual switching required.
  1. Update VS Code to 1.113 (March 25, 2026 release).
  2. Enable the setting: "chat.subagents.allowInvocationsFromSubagents": true.
  3. Create a coordinator agent file that references your role-specific subagents.
  4. Start a chat session with the coordinator — it will delegate subtasks to specialized agents automatically.
Real Example: A "Full-Stack Feature Agent" receives a feature description, invokes the "Java API Agent" to create the backend endpoint, then invokes the "Angular UI Agent" to scaffold the component — one prompt, two specialized agents, full feature delivered.

MCP servers you configure in VS Code are now bridged into Copilot CLI and Claude agent sessions. Both user-defined servers and workspace mcp.json servers are included. Previously MCP was only available to local agents running inside the editor — now your terminal agent sessions have the same rich tool access as your chat panel sessions.

Key Takeaway: If you have an internal code-analysis MCP server set up in VS Code, your Copilot CLI sessions can now call it directly — no separate CLI configuration needed.
  1. Ensure VS Code 1.113 and the latest Copilot CLI (1.0.13) are installed.
  2. Configure an MCP server in VS Code via your mcp.json or user settings.
  3. Open a Copilot CLI session in the terminal.
  4. Run /mcp show in the CLI — you should see your VS Code-configured servers listed.
Real Example: You have an internal Java dependency-checker MCP server registered in VS Code. Open a Copilot CLI session and ask it to "audit my project's Spring Boot dependencies for vulnerabilities" — it now calls your MCP server to pull the data.

Reasoning models like Claude Sonnet 4.6 and GPT-5.4 now show a Thinking Effort submenu in the model picker — choose Low, Medium, or High without going into settings. The picker label shows the active level (e.g. "GPT-5.4 · Medium"). Note: the old github.copilot.chat.anthropic.thinking.effort setting is now deprecated in favor of this UI control.

Key Takeaway: Use Low effort for quick completions and boilerplate, High effort for complex architecture decisions — switch per-task without leaving the chat panel.

VS Code 1.113 introduces the Chat Customizations editor (Preview) — a single UI for managing all chat customizations: custom instructions, prompt files, custom agents, and agent skills. Includes a built-in code editor with syntax highlighting, AI-generated initial content, and direct browsing of MCP server and plugin marketplaces. Open via the gear icon in the Chat view or Chat: Open Chat Customizations in the Command Palette.

Key Takeaway: No more hunting across separate settings files for instructions, agents, and plugins — everything is in one tabbed editor with validation built in.

You can now fork a Copilot CLI or Claude agent session at any point in conversation history — creating a copy to explore a different approach without losing the original. Enable via github.copilot.chat.cli.forkSessions.enabled. Previously only available for local editor agent sessions, now extended to the full terminal workflow.

Key Takeaway: Stuck at a design decision mid-session? Fork and explore both paths simultaneously instead of losing your work or starting over.

Images in chat — whether you attached screenshots or the agent generated them via tool calls — now open in a full image viewer with navigation, zoom, pan, and conversation-turn grouping. The viewer is also available from the Explorer right-click menu for image files. Both imageCarousel.chat.enabled and imageCarousel.explorerContextMenu.enabled are on by default in 1.113.

Key Takeaway: Review agent-generated UI screenshots at full resolution directly in VS Code — no more downloading and opening files externally.

GitHub.com Copilot

4 updates

GitHub announced on March 25 that from April 24 onward, interaction data from Copilot Free, Pro, and Pro+ users will be used to train AI models unless users opt out. Data includes accepted outputs, code snippets shown to the model, cursor context, comments, file names, and chat interactions. Copilot Business and Enterprise users are not affected.

Key Takeaway: If you are on Copilot Pro or Pro+ and do not want your interaction data used for training, go to your GitHub settings under Privacy and opt out before April 24. Previous opt-outs are honored automatically.

The March 27 CLI release adds a timeline picker to /rewind and double-Esc — you can now roll back to any point in conversation history, not just the previous snapshot. CLI startup is also faster due to V8 compile cache reducing parse and compile time on repeated invocations. MCP registry lookups are more reliable with automatic retries and request timeouts.

Key Takeaway: Accidentally went too far down a refactoring path? Use /rewind and select exactly the conversation checkpoint you want to return to — surgical rollback, not just one step back.

Released March 26, this update opens the model picker in full-screen view with inline reasoning effort adjustment using arrow keys. The model display header shows the active reasoning effort level (e.g. "high") next to the model name. /allow-all (/yolo) now supports on, off, and show subcommands. MCP servers defined in .mcp.json at the git root now start correctly.

Key Takeaway: Adjust model and reasoning effort from inside the CLI picker with arrow keys — no more interrupting your flow to change settings in VS Code or a config file.

Also in the March 27 release: MCP servers can now request LLM inference (model sampling) with user approval via a new review prompt. This allows MCP tools to use Copilot's AI capabilities directly inside their own workflows, unlocking a new class of tool-driven AI interactions where external tools can ask the model questions as part of their operation.

Key Takeaway: An MCP tool that runs your test suite can now ask Copilot to summarize the failure patterns and suggest fixes — AI-in-the-loop tooling, not just AI-adjacent.

Microsoft Copilot for Enterprise

3 updates

The March 2026 Power Platform update brings Microsoft 365 Copilot directly into model-driven Power Apps via a side pane. Developers and users can ask Copilot to summarize table data, visualize what is active, recap record history, and reference related content — all from within the app. Copilot can also invoke specialized agents (including custom org agents) from the same pane and take actions like drafting documents or scheduling meetings.

Key Takeaway: If your team uses Power Apps for project tracking or data management, Copilot can now answer "what is happening with this record" questions and hand off to custom agents without leaving the app.

Copilot Studio's ability to connect agents to external data via custom MCP servers — currently in public preview — reaches general availability in April 2026. Organizations can connect any Copilot Studio agent to external databases, APIs, and internal tools without writing custom connectors. The companion feature allowing MCP-compliant tools in agent workflows reaches preview in April and GA in October.

Key Takeaway: If you are planning an enterprise Copilot Studio agent that needs to call internal Java microservices or a proprietary data store, the custom MCP server path is the production-ready route from April onward.

For enterprise teams on IntelliJ and JetBrains IDEs: custom agents, sub-agents, and plan agent are now generally available. Agent hooks — which run custom commands at key agent lifecycle events like userPromptSubmitted, preToolUse, and postToolUse — are in public preview. Auto-approve for MCP tools is now configurable at both server and tool level. Requires enabling "Editor preview features" in Copilot Business or Enterprise admin settings.

Key Takeaway: Use agent hooks to enforce code quality policies automatically — for example, trigger a linting run via preToolUse before every file edit the agent makes.

Community Picks

3 picks
Reddit · r/GithubCopilot

The community crossed 50,000 members this week, with GitHub and Microsoft engineers joining a live AMA. Key clarification from the team: the Copilot SDK is MIT-licensed and you can bundle the CLI for personal use, internal tools, or basic web projects without commercial licensing. Commercial products require contacting GitHub. The premium request model is staying for now, with no current plans for per-token billing.

Key Takeaway: The SDK is MIT-licensed — you can build internal tooling on top of Copilot SDK without commercial concerns. Only building a product you sell requires a formal agreement with GitHub.
GitHub Gist · burke holland

A detailed work log showing a developer who built a personal AI assistant daemon ("Max") running 24/7 on their local machine using the GitHub Copilot SDK. The assistant handles coding tasks, file management, and orchestrates worker sessions. Key engineering challenge: worker sessions were never being destroyed (~400 MB RSS each), causing overnight out-of-memory crashes — fixed by adding explicit session lifecycle management.

Key Takeaway: The Copilot SDK is production-capable for personal automation tooling, but long-running worker sessions must be explicitly destroyed — the SDK does not clean them up automatically.
  1. Copilot SDK powers the conversational layer and can run coding tasks, manage files, and orchestrate worker sessions.
  2. Each worker session consumes ~400 MB RSS — must be explicitly destroyed when done.
  3. Session resumption is limited by the SDK; the workaround is context injection into new sessions.
  4. See the Gist for the full architecture and lessons learned from running this 24/7.
Real Example for automation builders: if you spawn Copilot SDK worker sessions in a Make.com or similar automation pipeline, ensure each session is explicitly terminated after the task completes to prevent memory accumulation.
YouTube · GitHub

A hands-on session showing how to use Copilot agent mode inside VS Code to generate and refactor GitHub Actions workflows for a .NET app, deploy to Azure with OpenID Connect, and use MCP to bring GitHub issue and PR context into the dev flow. Demonstrates creating custom DevOps agents specialized for workflow optimization and best practices.

Key Takeaway: You can use Copilot agent mode to write, explain, troubleshoot, and refactor YAML pipelines — including multi-step refactors that introduce reusable workflow patterns across your entire CI/CD setup.
Phani's Pick of the Week

Act Now: Opt Out of Copilot Data Training Before April 24

The single most time-sensitive action this week is checking your data policy settings. If you are on Copilot Pro or Pro+, GitHub will begin using your interaction data — including code snippets, accepted completions, and chat inputs — to train models starting April 24, unless you opt out. Go to your GitHub account settings, navigate to Privacy, and disable "Allow GitHub to use my data to improve GitHub Copilot." Takes 30 seconds and protects your codebase from being part of the training corpus. Copilot Business and Enterprise users are not affected.

— End of March 28, 2026 edition —