From 7134e080ffc17cfec381cf0638853d1bcb4d6b18 Mon Sep 17 00:00:00 2001 From: Tom Wheeler Date: Wed, 16 Sep 2026 17:31:11 -0500 Subject: [PATCH] remove references to now-archived VSCode debugger plugin --- .../typescript/background-check/durable-execution.mdx | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/docs/tutorials/typescript/background-check/durable-execution.mdx b/docs/tutorials/typescript/background-check/durable-execution.mdx index 187dd4d6..a7b04419 100644 --- a/docs/tutorials/typescript/background-check/durable-execution.mdx +++ b/docs/tutorials/typescript/background-check/durable-execution.mdx @@ -16,7 +16,6 @@ keywords: - tests - typescript - typescript sdk - - vscode debugger extension tags: - determinism - durable-execution @@ -28,7 +27,6 @@ tags: - tests - typescript - typescript-sdk - - vscode-debugger-extension --- When it comes to the Temporal Platform's ability to durably execute code, the SDK's ability to [Replay](https://docs.temporal.io/encyclopedia/temporal-sdks#replays) a Workflow Execution is a major aspect of that. @@ -420,14 +418,6 @@ Progress: BinaryChecksum:da7cae1f96abf543ca8b6e7c3f3ab072} ``` -### VSCode Debugger extension {#static-analysis} - -Non-deterministic code can be hard to catch while developing Workflows. -You can leverage the Temporal TypeScript VSCode extenstion to debug your Workflows by their ID or Workflow Event History file. -Use the [Temporal Debugger for VS Code](https://marketplace.visualstudio.com/items?itemName=temporal-technologies.temporalio). - -See the [vscode-debugger-extension README](https://github.com/temporalio/vscode-debugger-extension/blob/main/README.md) for details on how to use it. - ### Does this mean Temporal can't be used for AI? {#temporal-for-ai} No — the opposite. Workflow determinism is exactly what makes Temporal a strong fit for AI applications. LLM calls, tool use, and agent steps are non-deterministic by nature, so you place them in Activities. This separation makes the orchestration dependable even though these individual steps are non-deterministic, so your agent can recover from crashes, retry failed LLM calls, and resume long-running tasks without losing state.