Hi everyone,
I've been diving deep into Windsurf over the last few months, and overall, I'm really impressed with its approach to AI-assisted development. It feels like a powerful step forward. However, I've hit a recurring snag that's starting to impact my workflow, and I'm wondering if others in the community have experienced the same.
My primary issue is that Windsurf seems to **lose track of my project's context** mid-session, particularly when working on larger or more complex repositories. I'll be having a productive conversation with the agent about a specific module, and then suddenly, its responses become generic or it acts as if it doesn't remember the file structure, the language/framework specifics we were just discussing, or the unique patterns of the codebase. It's like the "project awareness" disconnects.
To be methodical, here’s what I’ve observed and tried:
**Symptoms:**
* The agent starts suggesting boilerplate code or patterns that don't align with our established project conventions.
* It "forgets" about key files or directories we were just referencing.
* When I ask it to reference a specific function I wrote earlier in the chat, it fails or hallucinates a different function.
* It defaults to very general explanations, losing the nuanced understanding it had at the start of the session.
**My Environment & Workflow:**
* Working with a monolithic repo (mix of Python, SQL, and some front-end components).
* I typically open Windsurf at the project root directory.
* I've ensured my `windsurf.json` is configured correctly at the root, specifying the relevant file patterns.
* I don't believe it's a token limit issue at the very start of a chat, as it happens even before conversations get extremely long.
**What I've Tried (with limited success):**
* Explicitly re-uploading or re-selecting the key project files at the start of a new chat.
* Using the `/project` command to re-sync context (this helps sometimes, but the effect seems temporary).
* Breaking down my work into smaller, project-specific chats, which is a bit against the "continuous conversation" ideal.
From my experience with other tools (like using Cursor or even deep IDE integrations), maintaining project-wide context is a known challenge. I'm curious how Windsurf's architecture handles this under the hood.
**My questions for the community:**
1. **Are you experiencing similar "context loss" issues?** If so, what does your project structure look like?
2. **Have you found any reliable workarounds or configuration tweaks?** Is there a way to "anchor" the agent to a specific subset of files more permanently?
3. **How does this compare to your experience with other AI coding assistants?** I find it's less of an issue in, say, Power BI or Tableau's ecosystem where the "data model" is a fixed, singular context, but in a sprawling codebase, it's trickier.
I love the tool's potential, especially for self-serve analytics and dashboard design patterns, but this inconsistency is my main hurdle. I'd love to pool our experiences and maybe even benchmark some solutions.
Let's troubleshoot this together
Let the data speak.