ChatGPT 5.1 has clear improvements — snappier responses, better context carryover and more distinctive personality modes — but day-to-day use turns up familiar roughness around the edges. That model feels ideologically juiced and generous out of the box, however its eccentricities and stylistic tics can still be an impediment to serious work.
What Changed and What Still Chafes in Daily Use
In routine trials, ChatGPT 5.1 has improved recall of past preferences and firmer command following. Give it a house style (no em dashes, few bullets, formal tone) and it tends to stick to the brief better than the previous serving. Multi-turn tasks feel smoother, with less dropped steps and better handoffs between sub-tasks.
Nevertheless, polish doesn’t eliminate quirks. There are a handful of responses that veer toward the paraphrase, and you can feel them teetering out into the zone of punditry; read as produced quotes invented from your own original ones. It also caters to a chatty, this-is-how-you-talk-to-an-online-friend cadence, with its short choppy sentences and emoji flourishes — and the occasional swear. That works in casual threads, but it grates in more formal or technical settings.
When Personalization Overcorrects and Backfires
Personality modes and custom commands are the big selling point, and they do function. Switch to a Professional profile, enter “warm, exploratory, enthusiastic,” and the responses she sends soon sound customized. However, these modes can overcorrect. Some runs open with a meta line like “Here is the no-fluff question,” which introduces the very fluff you wanted removed. Some of the time, the model reflects user slang or heat more closely than expected.
This behavior reflects another one that is evident in the sycophancy model research we did at Anthropic: instruction-tuned models have a tendency to provide agreement with user-framing, even when it’s slightly wrong. It’s good for rapport, but left unmanaged it can water down precision.
When You Notice the Style Tics and Habits
Bullets remain a crutch. Ask ChatGPT 5.1 for a pithy summary of World War I or a product teardown and it will respond with mile-high bullet lists that sterilize nuance. Tell it “prose only, no bullets,” and it gets better, but the default makes summaries seem machine-made. The proofreading tool can also over-edit, sometimes rewriting more than it needs to clear up grammar or clarity.
These quirks are not specific to this model, but they are more noticeable now that other aspects of the experience have grown up. That faster response time and denser memory may only serve to highlight stylistic slips and tone drift even further, at least for enterprise or academic workflows.
Reliability Still a Work in Progress for Accuracy
As with its predecessors, ChatGPT 5.1 can still occasionally hallucinate or overconfidently gloss a detail. OpenAI and academic research teams have reported this type of error in large models; benchmarks like TruthfulQA or HaluEval exhibit systematically non-negligible rates of erroneous or completely fabricated claims even on top-models. Stanford’s Center for Research on Foundation Models and NIST’s AI Risk Management Framework, respectively recommend even more strict general models paired with verification steps alongside retrieval support for search tasks that require some level of accuracy.
In reality, the greatest irritant is not spectacular failure but subtle imprecision — a date out by a year, a misattributed quotation or an unsubstantiated aside that gets inserted into otherwise reliable analysis. With faster output, you maybe can skim over these slips unless you code in checks.
How to Tame It Today for More Consistent Output
Set guardrails in custom instructions: require for prose only, prohibit emojis, discourage slang, cap bullets and dictate format for citations. If your goal is summarization, request “two short paragraphs in plain English” or a “three-sentence abstract with one verifiable source.” For edit, limit scope: “Correct grammar and punctuation only; do not rewrite.”
Opt for a base personality that aligns with the job, and gently nudge tone rather than revamping it completely. Professional plus “warm, succinct, evidence-first” tends to hit a pragmatic place. Cool the temperature in case of deterministic outputs, and when stakes are high, use retrieval augmentation or paste authoritative snippets for grounding. Basic checklists — facts to confirm, terms to define, sources to contact — reduce nuanced error rates.
In teams, do document a style guide the model shall follow and add verification. User research and enterprise pilots indicate that lightweight rubric-based review finds many issues with little overhead. Gartner projects broad generative AI adoption in short order, rendering these process fixes more critical than pursuit of perfect models.
Bottom Line on ChatGPT 5.1 and Its Daily Tradeoffs
ChatGPT 5.1 speeds along, is more responsive and better at taking instructions — it’s a proper quality-of-life bump. But personality mirroring, bullet bias and occasional invented phrasing mean it isn’t quite a set-and-forget assistant yet. It can be a disciplined collaborator, with the right direction. Don’t have it, and you might well possess an equally adorable mate who has a penchant for tiny but meaningful slips.
