Prompt

Can you help me compare prompt versions and understand why behavior changed after a deploy?

Technology / Observability1 observationLast seen Oct 9, 2026

Latest observation

Oct 9, 2026OpenAI APIWeb search: off

Yes — I can help with that.

If you have two prompt versions and a deploy that changed behavior, I can compare them and identify likely causes such as:

  • wording changes that alter instruction priority
  • added or removed constraints
  • changes in role framing or examples
  • shifts in formatting requirements
  • conflicts between system, developer, and user instructions
  • context-window or truncation effects
  • tool-use or routing changes
  • model/version changes alongside the deploy

What to send me:

  1. Old prompt
  2. New prompt
  3. Example inputs
  4. Before vs after outputs
  5. Any deploy notes or model/config changes

Then I can help with:

  • a diff-style comparison
  • likely root cause analysis
  • identification of regressions
  • suggestions for a safer prompt rewrite
  • a test plan to validate the fix

If you want, paste the two prompt versions and one or two before/after examples, and I’ll analyze them.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.