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I Asked Claude Sonnet 5.5 to Think Like 10 Different Experts

Sep 30, 2026 Admin
I Asked Claude Sonnet 5.5 to Think Like 10 Different Experts

I Asked Claude Sonnet 5.5 to Think Like 10 Different Experts

What happens when you stop asking an AI to simply “answer a question” and instead give it the mindset of a specialist? I tested Claude Sonnet 5.5 with 10 different expert roles to see how changing the perspective could change the way a problem is approached.

The experiment covered everything from software development and marketing to business strategy, writing, data analysis, UX design, and research.

The goal wasn't to pretend Claude literally becomes a human expert. Instead, the idea was to see whether role-based prompting could make its responses more focused, structured, and useful.

What Is Claude Sonnet 5.5?

Claude Sonnet 5.5 is Anthropic's latest Sonnet model, introduced on September 28, 2026. Anthropic positions it as a fast model for everyday coding, content creation, data analysis, visual understanding, and agentic tool use.

Anthropic says Sonnet 5.5 runs more than 30% faster than Sonnet 5 and costs up to 30% less for most work. It also supports a 1-million-token context window and adaptive thinking.

The idea behind this experiment: Instead of using one generic prompt, I gave Claude Sonnet 5.5 a different professional perspective for each task and compared how the resulting approach changed.

Why Use Expert Personas?

A simple prompt such as “How can I improve my website?” leaves a lot of room for interpretation.

A more specific instruction can give the model a clearer objective:

  • Think like an SEO strategist.
  • Think like a senior software engineer.
  • Think like a conversion-focused marketer.
  • Think like a UX designer.

The difference is not that the model suddenly gains real-world experience. The benefit is that the prompt establishes a specific perspective, priorities, vocabulary, and evaluation criteria.

The 10 Expert Roles I Tested

01. Senior Software Engineer

I asked Claude to approach a coding problem like an experienced software engineer rather than simply generating code.

Prompt: “Act as a senior software engineer. Analyze the problem, identify edge cases, explain the architecture, then provide a clean implementation. Prioritize maintainability and security.”

This approach is useful when you want more than a code snippet. It encourages Claude to think about architecture, testing, errors, and long-term maintenance.

02. SEO Strategist

Next, I gave Claude the role of an SEO strategist and asked it to analyze a topic from a search-intent perspective.

Prompt: “Act as an SEO strategist. Identify the search intent, primary topic, related entities, useful subtopics, FAQs, and content gaps. Build a helpful structure without keyword stuffing.”

This is particularly useful for bloggers who want to turn one keyword into a complete content plan.

03. Marketing Strategist

For the marketing test, Claude had to focus on the customer rather than the product.

Prompt: “Act as a senior marketing strategist. Identify the target audience, their problem, objections, desired outcome, positioning, and strongest messaging angles.”

The result is usually more useful than simply asking an AI to “write marketing copy” because the prompt defines what the copy needs to accomplish.

04. Business Consultant

The business consultant role focused on decisions, risks, resources, and execution.

Prompt: “Act as a business consultant. Break this problem into its major components, identify risks and assumptions, compare possible approaches, and create an actionable plan.”

This kind of prompt is useful for turning a vague business idea into a structured problem-solving exercise.

05. UX Designer

For the UX test, I asked Sonnet 5.5 to think about the experience from the user's perspective.

Prompt: “Act as a senior UX designer. Analyze this experience from the user's perspective. Identify friction points, confusing elements, accessibility issues, and opportunities to simplify the workflow.”

The key change is the evaluation criteria: the question becomes less about what looks good and more about what makes the product easier to use.

06. Data Analyst

The data analyst role focused on evidence, patterns, assumptions, and limitations.

Prompt: “Act as a data analyst. Examine the information carefully, identify meaningful patterns, separate facts from assumptions, explain limitations, and present the findings clearly.”

This is a useful pattern whenever an answer depends on numbers or a dataset rather than opinions.

07. Professional Editor

I then switched from analysis to writing and asked Claude to behave like a professional editor.

Prompt: “Act as a professional editor. Improve clarity, structure, flow, grammar, and readability while preserving the author's original meaning and voice.”

This works particularly well when you already have a draft but don't want the AI to completely rewrite it in a generic style.

08. Researcher

For research-oriented tasks, the prompt emphasized evidence and uncertainty.

Prompt: “Act as a careful researcher. Separate established facts from assumptions, identify information that needs verification, consider alternative explanations, and clearly state uncertainty.”

This is an important distinction because a confident-sounding answer isn't necessarily a verified answer.

09. Product Manager

The product manager persona had to balance users, features, priorities, and constraints.

Prompt: “Act as an experienced product manager. Define the user problem, prioritize features, identify constraints, propose an MVP, and explain how success should be measured.”

This can be especially useful when you have too many ideas and need a structured way to decide what belongs in the first version.

10. Critical Thinker

Finally, I asked Sonnet 5.5 to challenge an idea instead of simply supporting it.

Prompt: “Act as a critical thinker. Challenge the assumptions behind this idea, identify weaknesses, consider opposing arguments, and explain what evidence would change the conclusion.”

This may be one of the most useful expert-persona prompts because it encourages the model to look for problems rather than automatically agreeing with the user.

What Did the Experiment Show?

The biggest lesson is that the quality of an AI response depends heavily on the instructions surrounding the task.

Simply changing the phrase “act as an expert” isn't a magic switch. The stronger prompts also explained what the expert should prioritize and what the final answer should contain.

For example, “Act as an SEO expert” is relatively vague. A stronger version specifies search intent, entities, content gaps, internal linking, FAQs, and reader usefulness.

The Better Formula for Expert Prompts

Instead of using only a job title, try this five-part structure:

  1. Role: Define the perspective.
  2. Goal: Explain what needs to be accomplished.
  3. Context: Give the relevant background.
  4. Criteria: Explain what a good answer should prioritize.
  5. Output: Specify the format you want.
Simple formula:
“Act as a [ROLE]. Your goal is to [OBJECTIVE]. Consider [CONTEXT]. Prioritize [CRITERIA]. Return the result as [FORMAT].”

Does Claude Really Become an Expert?

No. An expert persona is a prompting technique, not a replacement for professional experience or independent verification.

The role tells Claude how to approach the problem. It does not guarantee that every answer is correct or that the model possesses the real-world judgment of someone who has spent years working in that profession.

For important decisions, the output should be checked against authoritative information and qualified professionals where appropriate.

Why Sonnet 5.5 Is Interesting for This Experiment

Anthropic describes Sonnet 5.5 as a model designed for everyday coding, data analysis, content creation, visual understanding, and agentic tool use. That makes role-based prompts particularly relevant to the kinds of multi-purpose workflows tested here.

Its adaptive thinking also lets users adjust the effort level depending on the workload. Anthropic recommends different effort levels depending on whether the task is routine, latency-sensitive, agentic, or more difficult.

10 Expert Prompts You Can Copy

  • Developer: “Act as a senior software engineer and review this code for bugs, security issues, edge cases, and maintainability.”
  • SEO: “Act as an SEO strategist and create a search-intent-focused content plan for this keyword.”
  • Marketing: “Act as a marketing strategist and identify the audience, pain points, objections, positioning, and messaging.”
  • Business: “Act as a business consultant and turn this problem into an actionable strategy.”
  • UX: “Act as a UX designer and identify friction points and ways to simplify this user journey.”
  • Data: “Act as a data analyst and identify patterns, anomalies, assumptions, and limitations.”
  • Editor: “Act as a professional editor and improve this writing while preserving its original voice.”
  • Researcher: “Act as a careful researcher and separate verified facts from assumptions and uncertainty.”
  • Product Manager: “Act as a product manager and prioritize these ideas into a realistic MVP.”
  • Critical Thinker: “Act as a critical thinker and challenge the assumptions behind this proposal.”

Frequently Asked Questions

What is Sonnet 5.5?

Claude Sonnet 5.5 is Anthropic's current Sonnet model, introduced on September 28, 2026. Anthropic describes it as a fast model for everyday coding, analysis, content creation, and related workloads.

Can Claude Sonnet 5.5 act like different experts?

Yes. You can use role-based prompting to ask Claude to approach a task from different professional perspectives, although this does not mean the model literally becomes a human expert.

What are expert prompts?

Expert prompts give an AI a defined professional perspective, objective, criteria, context, and output format to make the requested task more focused.

What is the best expert persona for Claude?

There isn't one universal expert persona. The useful role depends on the task. A developer role makes sense for code, an SEO strategist for search content, and a UX designer for product usability.

Does role prompting guarantee better answers?

No. A detailed role can make the task clearer, but accuracy still depends on the prompt, available information, reasoning, and verification.

Final Thoughts

Asking Claude Sonnet 5.5 to “be an expert” is only the beginning. The real improvement comes from defining how that expert should think about the problem.

Give Claude a role, a clear objective, useful context, evaluation criteria, and a specific output format. That turns a generic AI request into a much more structured workflow.

The most useful takeaway from this experiment is simple: don't just tell Claude who to be. Tell it what that expert should prioritize.

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