---
type: "post"
id: "this-concern-shows-up-in-developer-surveys-too-019ab4"
slug: "this-concern-shows-up-in-developer-surveys-too-019ab4"
title: "This concern shows up in developer surveys too."
description: "The Stack Overflow 2025 Developer Survey reports that 66% of respondents to its AI-frustrations question encountered answers that were “almost right.” This is a signal about users’ reported experience, not a measured error rate for AI-generated code."
retrieval_nugget: "The Stack Overflow 2025 Developer Survey reports that 66% of respondents to its AI-frustrations question encountered answers that were “almost right.” This is a signal about users’ reported experience, not a measured error rate for AI-generated code."
published_at: "2026-10-13"
updated_at: "2026-10-13"
record_date: "2026-10-13"
date_kind: "published_at"
topics: []
source_urls: ["https://survey.stackoverflow.co/2025/ai"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "post:this-concern-shows-up-in-developer-surveys-too-019ab4"
status: "published"
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editorial_provenance: {"schema_version":"newruntime-editorial-copy-v1","content_status":"source_grounded_final","final_copy_sha256":"sha256:4dd628978cf87081db691cd9bb476f8c0b355c11143cac2626839b7d99bb28b4","reviewed_at":"2026-10-13T21:01:24.821Z","source_evidence_count":1,"verified_claim_count":3,"site_analysis_schema_version":"newruntime-site-analysis-v1","site_object_kind":"field_note","observed_fact_count":3,"implication_count":2,"watch_condition_count":1,"related_record_count":0}
analysis: {"schema_version":"newruntime-site-analysis-v1","object_kind":"field_note","thesis":"The survey points to verification work as a practical friction in AI-assisted development, without quantifying the underlying code-error rate.","observed_facts":[{"text":"Stack Overflow reports that 84% of respondents use or plan to use AI tools in development.","source_urls":["https://survey.stackoverflow.co/2025/ai"]},{"text":"The survey says 51% of professional developers use AI tools daily.","source_urls":["https://survey.stackoverflow.co/2025/ai"]},{"text":"66% of respondents to the AI-frustrations question reported dealing with answers that were almost right.","source_urls":["https://survey.stackoverflow.co/2025/ai"]}],"mechanism":"An answer that appears plausible but is subtly wrong can shift effort from producing a first draft to checking assumptions, edge cases, and integration.","why_now":"Reported daily use among professional developers makes the cost of reviewing AI output relevant to ordinary workflow design, not just experimentation.","implications":["Teams should evaluate AI assistance alongside the review and testing work needed to trust its output.","Perceived friction is not equivalent to an observed code-error rate."],"evidence_boundary":"These are survey responses, not an independent code-quality benchmark, and the excerpt provides no error-rate measurement.","watch_conditions":["Watch for future evaluations that pair adoption data with task-level correctness and review effort."],"related_records":[],"new_branch_reason":"No prior New Runtime record is supplied for this survey finding, so this begins a distinct record grounded in the primary survey."}
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
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---

# This concern shows up in developer surveys too.

## Retrieval answer

The Stack Overflow 2025 Developer Survey reports that 66% of respondents to its AI-frustrations question encountered answers that were “almost right.” This is a signal about users’ reported experience, not a measured error rate for AI-generated code.

The Stack Overflow 2025 Developer Survey reports that 66% of respondents to its AI-frustrations question encountered answers that were “almost right.” This is a signal about users’ reported experience, not a measured error rate for AI-generated code. Thesis: The survey points to verification work as a practical friction in AI-assisted development, without quantifying the underlying code-error rate.

Observed facts: The survey says 84% of respondents use or plan to use AI tools in development, and 51% of professional developers use them daily. It also reports that 66% of respondents to the AI-frustrations question dealt with almost-correct answers. Mechanism: An answer that appears plausible but is subtly wrong can shift effort from producing a first draft to checking assumptions, edge cases, and integration. The survey records reported frustration; it does not measure how often generated code is wrong. Why now: Reported daily use among professional developers makes the cost of reviewing AI output relevant to ordinary workflow design, not just experimentation.

Implications: Teams should evaluate AI assistance alongside the review and testing work needed to trust its output. The figures do not establish that AI tools caused the reported frustration or that almost-correct answers dominate all generated code. Evidence boundary: These are survey responses, not an independent code-quality benchmark, and the excerpt provides no error-rate measurement. First watch condition: Watch for future evaluations that pair adoption data with task-level correctness and review effort. The survey is a useful indicator of perceived verification burden, but stronger evidence would require observed outcomes.

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

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