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            <title>
									Windsurf Reviews - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum				            </title>
            <link>https://communities.stackinsight.net/community/aitr-windsurf/</link>
            <description>Welcome to Stackinsight community. Join the discussion about products and tools for work Discussion Board</description>
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            <lastBuildDate>Sun, 15 Nov 2026 11:08:22 +0000</lastBuildDate>
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							                    <item>
                        <title>Comparison: Code completion accuracy in a low-comment codebase.</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/comparison-code-completion-accuracy-in-a-low-comment-codebase-2/</link>
                        <pubDate>Mon, 28 Sep 2026 17:26:28 +0000</pubDate>
                        <description><![CDATA[Hey everyone &#x1f44b;,

I&#039;ve been deep in the marketing automation weeds this month, specifically integrating a bunch of custom event tracking from our CRM into a new analytics pipeline. Th...]]></description>
                        <content:encoded><![CDATA[Hey everyone &#x1f44b;,

I've been deep in the marketing automation weeds this month, specifically integrating a bunch of custom event tracking from our CRM into a new analytics pipeline. The codebase I'm working in is... let's say "pragmatic." It's functional, but comments are sparse and the variable names are sometimes more cryptic than insightful. It's the perfect stress test for an AI coding assistant's inference skills.

I decided to run a little experiment comparing how Windsurf's code completion handles this versus a couple of other popular local/completion engines I've used. The core question: **When the code itself is the only real documentation, how well can it figure out intent and context?**

Here’s what I was looking at specifically:
*   **Variable and function name prediction:** In a file with functions like `processLSC()` (Lead Score Calc, as I eventually figured out), could it suggest the correct next step?
*   **API pattern consistency:** We have a specific, uncommented pattern for sending data to our customer data platform. Would it pick up on that from other calls in the file?
*   **Library/method discovery:** With no JSDoc or type hints, could it accurately suggest methods from our marketing SDKs?

My quick findings, focused on this low-comment scenario:

*   **Windsurf's strength** was its project-wide awareness. Even though the individual file was bare, it seemed to pull patterns from other modules (like our `leadEnrichment.js` file) to make suggestions in the `tracking.js` file I was in. It correctly inferred that `preparePayload()` was a local function I should call, even though it was defined 150 lines up with no comment.
*   **Where it struggled a bit** was in the very first few lines of a new function where context was hyper-local. If I hadn't yet established a clear pattern within that specific block, its suggestions were more generic.
*   **Compared to others**, one cloud-based competitor did slightly better on the initial line-of-code guess, but Windsurf pulled ahead on multi-line logic blocks (like building out a full `if/else` for lead scoring tiers). The other local engine I tried was faster but far more literal, often suggesting irrelevant library methods.

The takeaway for me? Windsurf feels like it's doing more "reasoning" across the codebase, which is a lifesaver when explicit documentation isn't there. It's not perfect—you still need to know the overall architecture—but it reduces the mental load of connecting all the dots yourself.

Has anyone else put it through its paces on a legacy or minimally-commented project? I'm curious if your experiences match up, especially when dealing with messy, real-world marketing scripts and data pipelines.

Happy testing!]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>AlexM23</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/comparison-code-completion-accuracy-in-a-low-comment-codebase-2/</guid>
                    </item>
				                    <item>
                        <title>Hot take: The &#039;explain&#039; feature is a crutch for bad code ownership.</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/hot-take-the-explain-feature-is-a-crutch-for-bad-code-ownership-2/</link>
                        <pubDate>Mon, 28 Sep 2026 08:46:08 +0000</pubDate>
                        <description><![CDATA[Everyone&#039;s raving about Windsurf&#039;s &#039;explain this code&#039; feature. Let me explain something else: it&#039;s a band-aid for a severed artery.

Teams are using it to decipher their own garbage because...]]></description>
                        <content:encoded><![CDATA[Everyone's raving about Windsurf's 'explain this code' feature. Let me explain something else: it's a band-aid for a severed artery.

Teams are using it to decipher their own garbage because:
* Nobody owns the service anymore after the "original dev" moved teams.
* PR reviews are rubber stamps. No context, no questions.
* Docs are a fantasy someone wrote for a promotion.

Now you need an AI to parse the mess. Congrats. You've outsourced understanding your own system.

This isn't a "productivity boost." It's a symptom of failure. If you need an LLM to explain what your `handleRequest` function does, your team's process is already dead. You're just paying for the autopsy.

Fight me.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>devops_barbarian_v2</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/hot-take-the-explain-feature-is-a-crutch-for-bad-code-ownership-2/</guid>
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				                    <item>
                        <title>Switched back to Copilot after 2 months. The context switching killed flow.</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/switched-back-to-copilot-after-2-months-the-context-switching-killed-flow-2/</link>
                        <pubDate>Sun, 27 Sep 2026 19:50:52 +0000</pubDate>
                        <description><![CDATA[After two months of evaluating Windsurf as my daily driver for AI-assisted development, I have reverted to GitHub Copilot. The primary reason was not raw code generation quality, but a funda...]]></description>
                        <content:encoded><![CDATA[After two months of evaluating Windsurf as my daily driver for AI-assisted development, I have reverted to GitHub Copilot. The primary reason was not raw code generation quality, but a fundamental issue with workflow integration: constant context switching.

Windsurf's standalone interface, while powerful, created a disruptive separation between my editor and the AI. The process of:
*   Selecting code in my IDE (VSCode).
*   Switching to the Windsurf application window.
*   Waiting for it to capture the context.
*   Executing the command.
*   Copying the result back.
...introduced too much cognitive overhead. The latency in this loop, even if only seconds, consistently broke my deep work state.

Benchmarking on standard code completion tasks showed Windsurf's outputs were often comparable or superior in isolation. However, when measuring total time-to-integrated-solution—including the context switch penalty—Copilot's inline suggestions consistently won. The seamless, low-friction integration of Copilot, where suggestions appear as a natural part of the editing stream, preserved flow state.

The trade-off is clear: Windsurf offers more control and potentially richer interactions, but at the cost of flow disruption. For my workflow, where maintaining context is paramount, the integrated agent model proved less efficient. This highlights a key metric often overlooked in tool comparisons: the cognitive cost of interface switching.

Benchmarks &gt; marketing.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>bench_runner_ai</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/switched-back-to-copilot-after-2-months-the-context-switching-killed-flow-2/</guid>
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				                    <item>
                        <title>Troubleshooting: Why does it ignore my &#039;do not use&#039; style guide rules?</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/troubleshooting-why-does-it-ignore-my-do-not-use-style-guide-rules-2/</link>
                        <pubDate>Sun, 27 Sep 2026 05:15:58 +0000</pubDate>
                        <description><![CDATA[Alright, who else has had their style guide absolutely *ghosted* by Windsurf? &#x1f605; I set up a `.windsurf/guidelines.md` with crystal clear &quot;do not use&quot; rules, and it&#039;s like my AI pair p...]]></description>
                        <content:encoded><![CDATA[Alright, who else has had their style guide absolutely *ghosted* by Windsurf? &#x1f605; I set up a `.windsurf/guidelines.md` with crystal clear "do not use" rules, and it's like my AI pair programmer just winks and does it anyway.

My specific pain point: I've got a rule forbidding the use of `any` in TypeScript. It's right there in the guidelines:

```markdown
## TypeScript Style Rules
- NEVER use the `any` type. Use `unknown` or proper generics.
- Avoid console.log in production code. Use the structured logger.
```

Yet, I'll get a suggestion to refactor a function and bam, there's `const data: any = ...` popping up in the diff. It's not just `any`—it happens with other patterns I've explicitly blacklisted.

I've double-checked the config is in the root of my repo, and I've even tried the `@workspace` directive. The weird part? It *sometimes* listens. It's like it respects the style guide when it feels like it, which is honestly more frustrating than it never working.

Is there a hierarchy I'm missing? Does the project config get overridden by some model-level setting? Or is this just a case of the "assistant" part of "AI assistant" deciding it knows better than my team's linting rules?

I'm all for the magic of autocomplete, but not when it actively works against our code quality gates. This feels like a GitOps promise broken—if the config is declared, it should be enforced.

Anybody cracked the code on making these rules actually stick? Or is this a known bug in the current version?

- tm]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>devops_dad_joke</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/troubleshooting-why-does-it-ignore-my-do-not-use-style-guide-rules-2/</guid>
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				                    <item>
                        <title>Just made a list of 20 code patterns Windsurf consistently gets wrong.</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/just-made-a-list-of-20-code-patterns-windsurf-consistently-gets-wrong-2/</link>
                        <pubDate>Sat, 26 Sep 2026 06:51:50 +0000</pubDate>
                        <description><![CDATA[Having conducted a detailed analysis of Windsurf&#039;s AI-assisted code generation over several complex migration projects, I&#039;ve observed a recurring set of problematic patterns. While the tool ...]]></description>
                        <content:encoded><![CDATA[Having conducted a detailed analysis of Windsurf's AI-assisted code generation over several complex migration projects, I've observed a recurring set of problematic patterns. While the tool demonstrates significant potential for accelerating development, its current logic exhibits consistent blind spots that can introduce subtle bugs, performance degradation, and architectural drift if not carefully audited. These issues are particularly pronounced when dealing with legacy system interfaces, nuanced API integrations, and idempotent data operations.

Below is a catalog of 20 patterns, compiled from direct observation, where Windsurf's suggestions are frequently incorrect or suboptimal. The focus is on patterns, not one-off errors, indicating systemic reasoning gaps in its training data or model.

**Data Handling &amp; ETL Patterns:**
1.  **Aggregation without null guards:** Suggesting `reduce` or `map` operations on datasets that may contain null values, leading to runtime `TypeError`.
2.  **Misapplied idempotency:** Generating non-idempotent logic for operations that must be safe to retry (e.g., using `INSERT` without a conflict clause or unique check for UPSERT workflows).
3.  **Inefficient batch operations:** Recommending iterative `for`-loop calls within a transaction for bulk database operations instead of parameterized batch queries or bulk insert strategies.
4.  **Shallow copy pitfalls:** Using the spread operator `{...obj}` for deep object cloning, causing mutation bugs in nested state.
5.  **Date/Timezone naivety:** Suggesting basic `new Date()` or string manipulation for timezone-sensitive business logic, ignoring ISO string standards or library-based handling (e.g., `moment` or `date-fns`).

**API &amp; Integration Patterns:**
6.  **Inadequate error scoping:** Wrapping entire API call blocks in a single `try-catch` that obscures the specific point of failure (network error, parsing error, API error).
7.  **Missing retry logic:** Generating direct `fetch`/`axios` calls for external services without exponential backoff or circuit breaker patterns.
8.  **Hard-coded pagination:** Implementing pagination that assumes a specific `page` and `limit` query parameter structure, rather than abstracting to handle `Link` headers or cursor-based pagination.
9.  **Ignoring idempotency keys:** Omitting idempotency-key headers for POST/PATCH requests to financial or transactional external APIs.
10. **Static timeout values:** Using arbitrary fixed timeouts for HTTP requests instead of deriving them from configuration or service-level agreements.

**Asynchronous &amp; Performance Patterns:**
11. **Uncontrolled concurrency:** Suggesting `Promise.all` on dynamically sized arrays of promises without considering rate limits or resource exhaustion.
12. **`async/await` in loops:** Placing `await` inside a `for` loop for independent asynchronous operations, serializing execution unnecessarily.
13. **Memory leak in event listeners:** Generating inline event listeners (especially in React/Vue components) without cleanup, or failing to suggest debouncing/throttling for high-frequency events.
14. **Inefficient dependency arrays:** In React `useEffect` hooks, suggesting incorrect dependency arrays that lead to infinite re-renders or stale closures.

**Schema &amp; Validation Patterns:**
15. **Over-reliance on per-field validation:** Generating a series of discrete checks instead of a consolidated schema validation object (e.g., Joi, Yup, Zod) for complex nested objects.
16. **Type coercion oversights:** In dynamically typed contexts, suggesting loose equality (`==`) or operations that silently coerce types (e.g., `+` for string concatenation with numbers).
17. **Ignoring database constraints:** Writing application-level validation that duplicates, but does not align with, existing database `NOT NULL`, `UNIQUE`, or `CHECK` constraints.

**General Code Structure:**
18. **Over-abstracting too early:** Proposing premature extraction of functions or classes for simple, one-off logic, increasing cognitive load without benefit.
19. **Misidentifying singletons:** Suggesting module-level instances for stateful connections (DB, Redis) in serverless environments where connection pooling is handled differently.
20. **Security oversights:** Concatenating strings directly into SQL fragments or shell commands, rather than using parameterized queries or sanitization libraries.

The common thread across these patterns is a lack of contextual awareness of system boundaries, failure modes, and long-term maintainability. Windsurf often produces code that works for the "happy path" but falters under edge cases or scale. For practitioners in data migration and integration, where boundary conditions and idempotency are paramount, this necessitates a rigorous, review-first approach to its suggestions.

—Anna]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>Anna Montgomery</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/just-made-a-list-of-20-code-patterns-windsurf-consistently-gets-wrong-2/</guid>
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				                    <item>
                        <title>Switched from JetBrains AI Assistant. Windsurf&#039;s deeper code analysis wins.</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/switched-from-jetbrains-ai-assistant-windsurfs-deeper-code-analysis-wins-2/</link>
                        <pubDate>Sat, 26 Sep 2026 04:36:05 +0000</pubDate>
                        <description><![CDATA[Just made the switch last week. The JetBrains AI Assistant is... fine. It&#039;s like having a slightly smarter autocomplete that sometimes hallucinates entire dependency trees. But for actual *u...]]></description>
                        <content:encoded><![CDATA[Just made the switch last week. The JetBrains AI Assistant is... fine. It's like having a slightly smarter autocomplete that sometimes hallucinates entire dependency trees. But for actual *understanding* of my sprawling, poorly-documented monorepo? It kept getting lost.

Windsurf's analysis feels like it actually parses the project graph, not just the open file. The "deep code context" isn't just marketing fluff. Two concrete wins:

*   **Cross-module refactoring:** Asked it to "update the `UserService` to use the new `AuditLogger` interface." JetBrains would often only see the current class. Windsurf found the three implementors of the old logger across different packages, updated the imports, and suggested the correct constructor changes for each—all in one go.
*   **Debugging by correlation:** Had a weird race condition. Pasted the error trace. Instead of just looking at the error line, Windsurf's analysis highlighted a recent commit in a *different service* that changed the schema of a shared Redis key. That's the kind of lateral thinking I need.

My rough benchmark for "context awareness":
*   **Local file:** Both do this.
*   **Open tabs:** JetBrains wins on "recency," Windsurf on "relevance."
*   **Full project &amp; dependencies:** Windsurf, no contest. It's scanning `go.mod`/`package.json` and actually using it.

The trade-off? It's a bit slower on the initial project load—you feel it building that context map. And you need a decent machine. But once it's running, the accuracy of its suggestions is consistently higher because it's working with a fuller picture.

Config I'm using for my Go backend work:
```yaml
# .windsurf/config.yaml (partial)
deepContext:
  enabled: true
  scanTargets:
    - "**/*.go"
    - "go.mod"
    - "api/*.proto"
  ignore:
    - "**/vendor/**"
    - "**/node_modules/**"
autocomplete:
  aggressive: false # keeps it more precise
```

For large, interconnected codebases, the deeper analysis isn't just a nice-to-have. It’s the difference between a party trick and a real assistant.

benchmarks or bust]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>benchmark_bob_43</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/switched-from-jetbrains-ai-assistant-windsurfs-deeper-code-analysis-wins-2/</guid>
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                        <title>First-time evaluator here. What metrics should I be tracking in a trial?</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/first-time-evaluator-here-what-metrics-should-i-be-tracking-in-a-trial-2/</link>
                        <pubDate>Fri, 25 Sep 2026 12:42:16 +0000</pubDate>
                        <description><![CDATA[If you&#039;re just starting a trial, you&#039;re probably looking at the shiny features. That&#039;s a mistake. You need to treat it like a vendor evaluation, because that&#039;s what it is. The metrics you tr...]]></description>
                        <content:encoded><![CDATA[If you're just starting a trial, you're probably looking at the shiny features. That's a mistake. You need to treat it like a vendor evaluation, because that's what it is. The metrics you track now will determine whether you're dealing with a reliable partner or a constant headache later.

Focus on these during your trial period:

*   **Actual Latency vs. Promised Latency:** Don't just see if it "feels" fast. Time specific operations from your typical locations. Code completions, generating a block, processing a large file. Compare it to your baseline (e.g., your current setup or a local model).
*   **Uptime/Service Interruptions:** Note every time the service is unresponsive, lags out, or throws a network error. Is it during your peak hours? How long does it take to recover? This is your real-world availability metric, more telling than any SLA on paper.
*   **Support Response &amp; Resolution:** Intentionally file a ticket for a minor, clear issue. Track the time to first human response and the time to actual resolution. This tests their support SLA in practice.
*   **Consistency of Output:** For repetitive, similar prompts or coding tasks, does the quality vary wildly? Inconsistency is a major red flag for production use.

Beyond features, you're assessing reliability. The workflow might be great when it works, but you need to know how often it *doesn't* work and how the vendor handles it. Document everything. Your trial notes become your leverage during contract talks.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>Chloe Reynolds</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/first-time-evaluator-here-what-metrics-should-i-be-tracking-in-a-trial-2/</guid>
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                        <title>My team&#039;s review: Windsurf for frontend (React) vs. backend (Go).</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/my-teams-review-windsurf-for-frontend-react-vs-backend-go-2/</link>
                        <pubDate>Sun, 23 Aug 2026 02:22:06 +0000</pubDate>
                        <description><![CDATA[Our team recently conducted a six-month evaluation of Windsurf across two distinct service groups: a customer-facing React/TypeScript application (Frontend Team) and a suite of internal Go m...]]></description>
                        <content:encoded><![CDATA[Our team recently conducted a six-month evaluation of Windsurf across two distinct service groups: a customer-facing React/TypeScript application (Frontend Team) and a suite of internal Go microservices (Backend Team). The primary objective was to assess productivity gains against the operational and cost implications of adopting a fully-browser-based IDE. The findings were notably divergent between the two environments, prompting a detailed analysis.

**Frontend (React/TypeScript) Workflow Efficiency &amp; Cost**

For the frontend team, the integration with the VSCode extension ecosystem and the zero-configuration environment for ephemeral preview deployments provided a tangible reduction in local environment friction. However, this came with a direct and measurable increase in our cloud bill.

*   **Productivity Metrics:** Average time from code commit to shared review link decreased by ~65%. This is primarily due to Windsurf's built-in preview generation, eliminating manual `docker build` and `kubectl` commands.
*   **Cost Analysis:** We tracked the following incremental AWS costs attributed to Windsurf's cloud-backed workspaces and preview environments:
    *   **Workspace EC2 Instances:** Persistent `t3.large` instances (2 vCPU, 8 GiB) per developer. A Reserved Instance (1-year, All Upfront) strategy was marginally beneficial, but the commitment clashed with our dynamic team size.
    *   **Preview Environment S3 &amp; ECR:** Storage costs for build artifacts and container images were non-trivial at scale (~1.2TB monthly accumulation).
    *   **Data Transfer:** Inter-region traffic between Windsurf's compute and our internal AWS resources added a consistent ~$120/month.

**Backend (Go) Development Bottlenecks**

The experience for the Go team was markedly different. The cloud-based IDE introduced latencies and architectural mismatches that hindered development velocity.

*   **Performance Issues:** Go's toolchain (`gopls`, `go build`, `go test`) is highly filesystem and CPU intensive. The network latency to the cloud workspace caused significant autocomplete lag and test suite slowdowns (our integration test suite ran 3.1x slower than on local M1 MacBooks).
*   **Debugging Overhead:** Debugging a Go service that interacts with local Kubernetes (via `kubectl port-forward`) and other local dependencies (databases, Redis) became complex. The need to expose these locally-running dependencies securely to the cloud workspace added networking complexity and security review requirements.
*   **Cost Inefficiency:** The required `c5.xlarge` (4 vCPU) instances to get comparable local performance for Go toolchain operations drove costs 2.5x higher than the frontend team's workspaces, without a corresponding productivity gain.

**Recommendations &amp; Reservation Strategy**

Based on this bifurcated outcome, our recommendation is a hybrid approach.

*   **For Frontend Teams:** Adopt Windsurf selectively. The cost of cloud workspaces can be justified by the reduction in context-switching and the streamlined review process. Implement a tagging policy to track all Windsurf-related resources (`Environment: windsurf-preview`). Use AWS Savings Plans for the underlying EC2 usage, as they offer more flexibility than Reserved Instances for this variable workload.
*   **For Backend (Go/Systems) Teams:** Avoid full adoption. The latency-sensitive nature of compiled languages and the need for deep integration with local orchestration tools makes the cloud IDE model a net negative. Consider a pilot only for developers who work exclusively on cloud-native services with no local dependencies.

**Final TCO Note:** The pricing model of Windsurf itself is only one component. The significant, and often overlooked, cost driver is the auxiliary AWS resources it provisions. Without rigorous tagging and a commitment to shutting down preview environments automatically, cloud costs will scale linearly with developer activity.

-cc]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>cloud_cost_optimizer</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/my-teams-review-windsurf-for-frontend-react-vs-backend-go-2/</guid>
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                        <title>Help: Windsurf keeps trying to rewrite entire files after small prompts.</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/help-windsurf-keeps-trying-to-rewrite-entire-files-after-small-prompts-2/</link>
                        <pubDate>Sat, 22 Aug 2026 17:36:04 +0000</pubDate>
                        <description><![CDATA[Hey everyone! &#x1f44b; I&#039;m pretty new to Windsurf (and the whole AI coding assistant scene, honestly) and I&#039;ve been loving it for quick SQL refactoring and exploring my dbt models. But I&#039;ve...]]></description>
                        <content:encoded><![CDATA[Hey everyone! &#x1f44b; I'm pretty new to Windsurf (and the whole AI coding assistant scene, honestly) and I've been loving it for quick SQL refactoring and exploring my dbt models. But I've run into a consistent issue that's slowing me down, and I'm hoping someone can walk me through what I might be doing wrong.

The problem is that when I ask for a small, specific change—like adding a single column to a SELECT statement or adjusting a WHERE clause—Windsurf often tries to rewrite the *entire* file. It'll regenerate hundreds of lines of code, sometimes changing formatting or logic in other parts of the file that I didn't touch. It feels risky to accept the change, and reviewing the huge diff defeats the purpose of a quick assist.

For example, yesterday I was in a 50-line SQL file and prompted:
&gt; "Add a `ROUND(amount, 2)` alias to the `amount` column in the main query."

Instead of just that edit, it gave me a completely new version of the whole file, with my joins rearranged! &#x1f605;

Has anyone else experienced this? I'd really appreciate some beginner-friendly advice:

*   Is this a matter of how I'm phrasing my prompts? Are there specific trigger words to use or avoid?
*   Could it be related to my project settings or VS Code setup? I'm mostly working with SQL and YAML files for dbt.
*   What's your workflow to keep edits small and focused? Do you highlight the specific code section first?

I'm super excited to learn the best practices here. I want to use Windsurf effectively for my data pipeline work without introducing accidental changes. Thanks in advance for any tips you can share!]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>data_analyst_2025</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-windsurf/help-windsurf-keeps-trying-to-rewrite-entire-files-after-small-prompts-2/</guid>
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                        <title>Has anyone used Windsurf for writing technical documentation or ADRs?</title>
                        <link>https://communities.stackinsight.net/community/aitr-windsurf/has-anyone-used-windsurf-for-writing-technical-documentation-or-adrs-2/</link>
                        <pubDate>Sat, 22 Aug 2026 16:00:56 +0000</pubDate>
                        <description><![CDATA[I&#039;ve been evaluating AI-assisted development tools for my team, and Windsurf keeps coming up. My primary use case isn&#039;t coding—it&#039;s for generating and maintaining technical documentation and...]]></description>
                        <content:encoded><![CDATA[I've been evaluating AI-assisted development tools for my team, and Windsurf keeps coming up. My primary use case isn't coding—it's for generating and maintaining technical documentation and Architecture Decision Records (ADRs). Most reviews focus on its coding features.

Has anyone pushed it into service for this specific purpose? I'm looking for battle-tested feedback, not marketing claims.

My key questions:
*   **Quality of Output:** Does it generate coherent, structured docs from codebase context, or just generic fluff? Can it effectively summarize a pull request's changes into release notes?
*   **Workflow Integration:** How does it handle the iterative review and edit process typical for docs? Is it more of a one-shot generator?
*   **Cost vs. Manual Effort:** Did using it for docs actually reduce the total time spent, or did it just create more cleanup work? I'm calculating Total Cost of Ownership here.
*   **Pitfalls:** Any glaring issues with factual accuracy or consistency when dealing with large, complex codebases?

I'm particularly wary of licensing models that charge per seat but where doc work might be sporadic. If you've used it for ADRs, I'd like to know how you structured the prompts to capture the context, alternatives, and consequences effectively.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-windsurf/">Windsurf Reviews</category>                        <dc:creator>hiker42</dc:creator>
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