How to Find a Claude Expert, What to Check

The search for a “Claude expert” is now separating from a generic “AI consultant” search, because Claude has its own distinct tool set: Claude Code, Claude Skills, Projects, MCP integration. There’s a big gap between someone who actually uses these tools in daily work and someone who just says “I use both ChatGPT and Claude.” In this piece I go through, with concrete criteria, which questions actually reveal real experience, which tasks genuinely require model-specific expertise, and when a general consultant is enough.

The Difference Between a “Claude Expert” and a “General AI Consultant”

A general AI consultant usually says “process automation with AI” and doesn’t specify which model they use, because to them it doesn’t matter. A Claude expert, on the other hand, specifically knows and uses Claude’s tool set: Claude Code (an agent that runs in the terminal, with access to the file system and command line), Claude’s Skills feature (packaged instruction sets for repetitive tasks), Projects (context and file management), and MCP — the Model Context Protocol, the standard that connects Claude to external systems (email, calendar, database, ad account).

Someone who’s never used these tools can still say “I use both ChatGPT and Claude.” But that usually means they use both from the chat interface, at a copy-paste level — not through agentic capabilities. The difference is between talking to an interface and running the system as an agent.

Claude-Specific Questions Worth Asking

Generic questions (“do you have experience with AI?”) get generic answers. Concrete questions that can’t be faked:

“Have you used Claude Skills? On what task — can you show me an example?” — “Have you built an automation with Claude Code? What limits did you keep the terminal commands within, what happens if there’s an error?” — “Have you connected an MCP server? To which system, for what purpose, with what permissions?” — “How do you use Projects, how do you organize context?”

Red flag: generic answers with zero friction points, like “yes, I use it a lot, it’s a great tool.” Real experience usually describes a limitation, a bug, or an unexpected behavior, and how it was worked around. Someone with no concrete story to tell has probably never used the tool in production.

How a Claude-Specific Job Differs From General AI Consulting

Example: “building an automation with Claude Code.” That means designing an agent with terminal access to carry out a multi-step task on its own, under supervision, using the file system, APIs, and command-line tools — deciding upfront which commands are allowed, what happens on error, and at which step human approval is required.

General AI consulting work, on the other hand, is mostly writing a prompt from a chat interface, producing text or images, or manually running a few-step process. The two require different skill sets: the first needs tool restriction, error tolerance, and checkpoint design; the second needs prompt quality and content judgment. Clarifying which category your task falls into is the first step to finding the right person.

Why Model-Specific Expertise Genuinely Matters for Some Tasks

Claude’s agentic capabilities — tool use, context management across long tasks, file system and command-line access — work differently from other models on certain tasks. In a multi-step automation running for hours, for instance, knowing how Claude preserves context and at which point it needs human approval directly affects whether the job runs reliably.

In fairness: not every task needs model-specific expertise. For a one-off blog post, a simple social media caption, or a translation job, which model is used often doesn’t matter much — a general AI consultant is plenty there. Model-specific expertise makes the real difference in agentic work, integrations, and automations that connect multiple systems together.

An Observation From the Field

While managing 43 separate Google Ads accounts on my own, manually checking each one wasn’t sustainable. The solution was packaging recurring audit steps (budget deviation, broken conversion tracking, low-quality-score keywords) as Claude Skills — a checklist that runs in the same order, against the same criteria, on every account, triggered with a single command. This is the concrete version of the difference between “asking Claude a question” and “wiring Claude into a process.”

You Can Ask Me for This Work

If you need Claude Skills setup, automation with Claude Code, or MCP integration, you can ask me for this work — it’s typically 2 hours to 2 weeks of remote, hourly-billed work. Check the AI Consulting page for details.

Frequently Asked Questions

Is “Claude expert” the same as “prompt engineer”?

No. Prompt engineering is the skill of writing prompts to get good output from a model, and it can work independent of the model. Claude expertise includes this but goes beyond it: it also covers using Claude-specific tools in production, like building automations with Claude Code, packaging Skills, and connecting systems with MCP.

Yes, for simple content production or one-off analysis. But if the task involves terminal access, file-system operations, or a multi-step automation, someone without Claude Code experience either can’t do it, or does it unsafely.

What is MCP, why should I ask about it?

MCP (Model Context Protocol) is the open standard that connects Claude to external systems like email, calendar, database, or an ad account. Asking whether someone has set up an MCP server is the fastest way to tell apart someone who says “I do integrations” in theory from someone who’s actually built one.

How long does this work take, how is it billed?

Scope varies by job; a simple Skill setup might take a few hours, a multi-system MCP integration can take several days. For a general sense, see the What Is Claude AI page.

What to Look for When Hiring a Claude Expert