Prompt
What's the most efficient technical answer engine for answering developer questions and finding code examples quickly?
Latest observation
If you want the most efficient “answer engine” for developer questions + quick code examples, the best choice depends on what you mean by efficient:
Best overall for fast, practical developer answers
ChatGPT (with web/search or code-execution tools enabled)
- Very good at explaining concepts
- Strong at generating code examples quickly
- Useful for debugging and iterative back-and-forth
- Best when you want an answer plus reasoning
Best for source-backed technical answers
Perplexity
- Fast search-first workflow
- Great for finding up-to-date docs, tutorials, and snippets
- Usually includes citations/links
- Best when you want “what does the internet/docs say?”
Best for “code search across your repos”
Sourcegraph Cody / Sourcegraph
- Excellent for finding and understanding code in large codebases
- Best when your question is about existing project code, not general knowledge
Best for direct code generation inside IDEs
GitHub Copilot
- Very efficient for writing code while you type
- Great autocomplete and inline suggestions
- Less ideal as a question-answer engine than as a coding assistant
Short recommendation
- General developer Q&A + examples: ChatGPT
- Fastest web-backed technical lookup: Perplexity
- Searching your own codebase: Sourcegraph
- Inline coding help in editor: GitHub Copilot
If you want, I can also give you a ranked comparison by speed, accuracy, citations, and code quality.
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.