GPT-5.1 Prompting Update: What to Change in Your System Prompts
OpenAI released GPT-5.1 to ChatGPT on November 12, 2025, with dev-facing API access rolling out through November. If you previously wrote prompts for GPT-5 or GPT-4, here's what changed and how to update your system prompts for optimal results.
What Changed in GPT-5.1
1. Refined Instruction Following
GPT-5.1 better distinguishes between hard constraints and soft preferences. The model now:
- Follows explicit constraints more strictly (format, length, scope)
- Interprets implied preferences with less over-eagerness
- Requires clearer signaling when you want creative liberty vs. rigid adherence
2. Tone Control Improvements
Earlier GPT-5 versions occasionally defaulted to overly formal or conversational tones regardless of instructions. GPT-5.1:
- Respects tone keywords (
casual,technical,academic) more consistently - Matches reference examples more accurately
- Reduces tone drift across multi-turn conversations
3. Calibrated Agentic Eagerness
GPT-5 was known for being "over-helpful" - suggesting tool calls, next steps, or alternatives even when not requested. GPT-5.1:
- Only suggests next actions when explicitly asked or when ambiguity is high
- Requires opt-in for multi-step planning (
"think ahead"or"propose next steps") - Stops cleanly after completing the requested task
Why this matters: If you relied on implicit agentic behavior, you'll need to make it explicit.
Migration Checklist: GPT-5 → GPT-5.1
Use this checklist to audit and update existing prompts:
✅ 1. Make Constraints Explicit
Before (GPT-5):
Write a summary of the article.
Keep it short.
After (GPT-5.1):
Write a summary of the article.
CONSTRAINT: Maximum 150 words. No introduction or conclusion.
Lesson: Replace vague directives ("keep it short") with measurable limits.
✅ 2. Specify Tone with Examples
Before (GPT-5):
Explain quantum entanglement in a friendly way.
After (GPT-5.1):
Explain quantum entanglement.
TONE: Conversational, like a science YouTuber. Use analogies. Avoid jargon.
EXAMPLE STYLE: "Imagine two coins that always land on opposite sides..."
Lesson: Provide reference style or example sentences; don't rely solely on adjectives.
✅ 3. Opt Into Agentic Behavior
Before (GPT-5): Model would often suggest next steps unprompted.
After (GPT-5.1): Add explicit instructions:
After completing the task, propose 2 logical next steps or alternatives.
Or, to suppress suggestions:
Complete the task and stop. Do not suggest next steps.
Lesson: Default is now "task-only" - specify if you want planning or alternatives.
✅ 4. Use Role + Scope Pattern
GPT-5.1 benefits from structured system prompts:
ROLE: {{who is the model}}
TASK: {{what to do}}
OUTPUT: {{format, length, structure}}
CONSTRAINTS: {{scope, rules, limits}}
TONE: {{style + example phrase}}
NEXT: {{clarify if agentic behavior is wanted}}
Example:
ROLE: Senior product manager
TASK: Draft a PRD for a mobile onboarding feature
OUTPUT: Markdown with sections: Problem, Goals, Non-Goals, Design, Risks
CONSTRAINTS: 500-800 words. Avoid implementation details.
TONE: Professional, concise. Example: "Users struggle to..."
NEXT: After the PRD, suggest 2 prioritization trade-offs.
Default Templates for Common Use Cases
1. Summarization (Updated for GPT-5.1)
ROLE: Research analyst
TASK: Summarize the following {{document_type}} for {{audience}}
OUTPUT: 5 bullet points (max 30 words each)
CONSTRAINTS: Prioritize findings and data. Omit background.
TONE: Neutral, data-driven
2. Code Generation
ROLE: Senior software engineer
TASK: Write {{language}} code to {{objective}}
OUTPUT: Code block with inline comments
CONSTRAINTS: No external libraries unless specified. Follow {{style_guide}}.
TONE: Clear variable names; explain non-obvious logic
NEXT: After code, list 2 edge cases to test.
3. Creative Writing
ROLE: Novelist
TASK: Write a {{length}} scene where {{scenario}}
OUTPUT: Prose, past tense, third person
CONSTRAINTS: Show, don't tell. Avoid clichés.
TONE: {{literary_style}} (e.g., "Hemingway: terse, sensory")
NEXT: Stop after the scene. Do not suggest sequels.
Do This If You Previously Wrote for GPT-5
- Audit implicit assumptions: If you relied on GPT-5 "guessing" constraints or tone, make them explicit.
- Add CONSTRAINT and TONE blocks: Even if GPT-5 worked without them, GPT-5.1 rewards clarity.
- Control agentic mode: Decide per prompt if you want next-step suggestions or a clean stop.
- Test with small edits: Change one thing at a time; compare outputs side-by-side.
- Snapshot your old prompts: Use PromptBuilder's version control or save to a Git repo before migrating.
Performance Notes
- Context window: Still 128k input (GPT-5.1 standard); 1M for extended caching tier.
- Speed: Slight latency improvement (~5-10%) on typical tasks vs. GPT-5.
- Cost: Same pricing as GPT-5 for now; prompt caching reduces cost on repeated prefixes (see our guide).
FAQ
Do I need to rewrite every prompt? No. If your GPT-5 prompts already had explicit constraints and tone, they'll work fine. Focus on prompts where you saw over-suggestions or tone drift.
What if I want the old "over-helpful" behavior?
Add "Think ahead and suggest logical next steps after every response." to your system prompt.
Does this apply to GPT-5 Turbo? GPT-5 Turbo gets the same instruction-following updates but with faster inference. The migration advice applies equally.
Where can I read the official release notes? OpenAI's GPT-5.1 announcement
Try It Now
Use PromptBuilder's model presets to compare GPT-5 vs. GPT-5.1 side-by-side with the same prompt. Update one constraint at a time and measure improvement.
Next: Learn how Gemini 3 simplified prompting even further.
Summary
GPT-5.1's changes boil down to: be explicit about constraints, tone, and agentic behavior. The model no longer over-infers your intent. In return, you get more predictable, reliable outputs. Audit your prompts using the checklist above, apply the templates, and you'll be optimized for late 2025 prompting best practices.
