GPT-5: what 62 developers actually say.

62 Hacker News opinions from 58 developers, Nov 2025 – Nov 2026. 54 come from people who say they use it. Here is what they praise, what they complain about, and who switched.

62 opinions58 developersNov 2025 – Nov 2026Methodology
Approval
57%
±10.3 at 90% confidence
Last 90 days
–
No recent data
Rank
#36
of 45 models · CI-adjusted
Opinions
62
54 first-hand
Developers
58
1.1 opinions each
The short version

The case for GPT-5, in one paragraph.

GPT-5 earns 57% approval across 62 opinions. Developers are divided on it, while code quality is the recurring complaint.

Pick it if you

  • Want dependable JSON output under strict constraints
  • Want an agent that explores codebases through git
  • Value reliable tool use with some autonomy

Look elsewhere if you

  • Need consistent design intent on large projects
  • Work mainly in Lisp or niche languages
  • Need long context and stable behavior over many turns

Where it wins and loses.

Mentions across 62 opinions. Bars are counts, not votes; a tool can be both praised and criticized on the same topic.

TopicComplaints ← → PraiseMentions
Reliability 13 mentions
58
Code quality 27 mentions
1413
PraiseComplaint
2 topics shown · sorted by net sentiment · source: 62 opinions
View data table
TopicPraiseComplaintsMentions
Reliability8513
Code quality131427

How opinion has moved.

Monthly approval, Nov 2025 – Jul 2026. Bars show opinion volume; low-volume months are still included but faded.

52% Nov 202520% Jul 2026 low20% Jul 2026– last 90 days
0255075100APPROVAL57% all-time52%20%Nov '25Dec '25Jan '26May '26Jul '26
Monthly approval, 0–100. Bars show opinion volume. Months with fewer than 3 opinions are left out.
View data table
MonthApprovalOpinions
Nov 202552%24
Dec 202594%8
Jan 202669%8
May 202640%5
Jul 202620%5

What developers say.

Summaries are paraphrased. Each links to the original Hacker News comment.

Praise

4 selected
Autonomy

The original GPT-5 adhered closely to prompts, which they praise.

HN comment · Oct 4, 2026Read on HN ↗
Reliability

GPT-5 and its early post-trained releases were excellent at following task instructions.

HN comment · Sep 17, 2026Read on HN ↗
Reliability

Reports GPT-5 and later never erred filling structured JSON under many constraints across hundreds of runs.

HN comment · Jul 6, 2026Read on HN ↗

Mid-tier GPT-5 is about as competitive as Sonnet for their workflow.

HN comment · Jun 2, 2026Read on HN ↗

Complaints

4 selected
Reliability

GPT-5 kept running wrong uv commands or using pip despite AGENTS.md instructions.

HN comment · Sep 9, 2026Read on HN ↗
Code quality

GPT-5 handled R coding terribly a year ago, which led them to switch to Gemini.

HN comment · Aug 19, 2026Read on HN ↗
Code quality

Found early GPT-5 added flashy, overwrought frontend styling and needed heavy prompting to stop it.

HN comment · Jul 10, 2026Read on HN ↗
Code quality

Finds GPT-5 models nitpicky and over-defensive in code, though useful for review and math.

HN comment · Jul 2, 2026Read on HN ↗

Questions developers ask.

Is GPT-5 worth it for coding?
The data has no pricing, but opinions are mixed: approval is 57% across 62 opinions and code quality is 13 positive to 14 negative. Reliability is stronger at 8 positive to 5 negative.
Is GPT-5 better than Claude Sonnet 4.5?
Head-to-head preference is thin: one developer preferred GPT-5 over Claude Sonnet 4.5, while two preferred Sonnet 4.5 instead. Overall approval is 57%, so the data does not show a clear winner.
What are GPT-5's main weaknesses?
Code quality is the main area of concern at 13 positive and 14 negative. Developers also cite drift, lost design intent on larger work, and weaker Lisp performance. Long context and stable instruction following over many turns also draw complaints.

The data behind this page.

GPT-5 has 57% approval across 62 opinions from 58 authors; 54 opinions are firsthand. Code quality is the main point of disagreement at 13 positive and 14 negative, while reliability is 8 positive to 5 negative and autonomy is 3 to 0. Recent monthly approval is volatile and based on small samples: 20% in July, 0% in August, 50% in September and 100% in October, on 1 to 5 opinions per month. Those recent samples are too small to show a stable direction.

Every number comes from public Hacker News comments collected through the HN Search API. A language model tagged each comment for sentiment, first-hand use, topic and switches; a human spot-checks samples. No vendor can pay for placement.

20,064 comments screened62 about GPT-554 first-hand

Read the full methodology →