Conversation with Claude (Anthropic), advanced prompts, Artifacts, Projects.
Before starting, we run a 1-minute tech check — microphone, ambient noise, connection. If your setup isn't good enough, the test is fully refunded.
Show — don't just claim — that you know Claude inside out: system prompts, Artifacts, Projects, and the Constitutional AI principles that make Anthropic's model behave differently from the rest.
The Plume Claude badge certifies your hands-on ability to use Claude beyond basic chat. In a 15-minute AI-led oral exam, the examiner probes your understanding of the Claude 3 model family (Haiku, Sonnet, Opus), your command of system prompts and role instructions, your use of Artifacts to generate and iterate on code or documents, and your ability to structure Projects for persistent, long-term context. The examiner also digs into Anthropic-specific knowledge: Constitutional AI, responsible use policies, and the concrete behavioral differences between Claude and other frontier models.
A "Generative AI" line on a resume means nothing in 2025. The Plume Claude badge is different: it's earned through a live oral exam where an AI examiner pushes back, reframes questions, and probes your blind spots. The full transcript is then scored by Claude Opus itself, producing a 0-100 score, a certified level (Novice / Proficient / Advanced / Expert), and a detailed report broken down by skill dimension. The result is a verifiable, shareable credential that can't be faked with a quick Google search.
This badge is built for developers integrating the Claude API, product managers scoping AI features, AI consultants advising enterprise clients, writers who rely on Claude for complex content workflows, and anyone building a career around generative AI who needs proof that their skills are real — not just self-assessed.
Here are the concrete dimensions the AI examines during the 15-minute oral.
Knowing when to reach for Haiku, Sonnet, or Opus based on cost, latency, context window (up to 200k tokens), and task complexity — and being able to justify that choice in a professional setting.
Writing tight system prompts that reliably constrain Claude's tone, output format, persona, and refusal behavior across an entire Projects session without drift.
Using Artifacts to generate, display, and revise code snippets, Markdown documents, or SVGs directly in the interface — and chaining revisions without losing context.
Configuring a Project with reference files, standing instructions, and multiple conversations to maintain consistent, business-specific context over time.
Understanding why Claude declines certain requests, how to rephrase a legitimately refused prompt, and the principles behind Anthropic's constitutional approach to model alignment.
Breaking complex tasks into structured reasoning steps, applying chain-of-thought techniques, and leveraging Claude's large context window for deep document analysis.
Working with the Claude API: temperature, top_p, max_tokens, system vs. human turns, multi-turn conversations, and tool use / function calling for agentic workflows.
Articulating when Claude outperforms GPT-4o or Gemini — writing style fidelity, instruction-following on long prompts, calibrated refusals, context window, and Anthropic's privacy stance.
Final scoring is performed by Claude (Anthropic), which reads back the full transcript and applies this weighted criteria grid.
Quality and precision of system prompts, role instructions, and prompt chaining techniques demonstrated during the exam. The examiner assesses your ability to produce reliable, repeatable outputs from Claude.
Hands-on knowledge of Artifacts, Projects, extended context windows, and the practical differences between Haiku, Sonnet, and Opus — not just definitions, but real usage decisions.
Your ability to break a complex task into clear reasoning steps, identify the model's limits, and adapt your prompting strategy based on the outputs you get during the session.
Understanding of Constitutional AI, Anthropic's usage policies, and how Claude's behavioral guardrails differ from other LLMs — with practical implications for real-world deployments.
How clearly you explain your reasoning, structure your answers, and defend your prompting choices under the examiner's follow-up questions. Fluency matters; jargon for its own sake does not.
A Plume session takes about 20 minutes, from tech check to badge delivery.
Quick microphone and connection test before the exam starts. Everything runs in your browser — no downloads, no installs. The AI examiner only launches once audio quality is confirmed.
The AI examiner opens with a broad question about how you use Claude day-to-day: which models, which interface or API, and what kind of tasks. This calibrates the depth of the questions that follow.
The core of the exam. The examiner covers Artifacts, Projects, system prompts, context window management, refusal handling, and model selection tradeoffs. It pushes back, offers alternative scenarios, and surfaces edge cases to test real depth rather than memorized answers.
A concrete professional scenario is presented — for example: "How would you configure a Claude Project for a legal team processing 50 contracts a week?" — to see whether you can combine multiple features under real constraints.
The transcript is analyzed by Claude Opus, which produces a 0-100 score, a certified level, and a detailed report highlighting strengths and specific areas for improvement. Your shareable badge URL is ready in under 10 minutes.
Your score out of 100 translates into a level a recruiter can grasp at a glance.
You use Claude like a smarter search engine or a one-click writing tool. Your prompts are short and unstructured, you haven't touched Artifacts or Projects yet, and you're not sure what the difference between Haiku and Opus actually means in practice.
You write prompts with clear context and output instructions, you've used Artifacts to generate code or documents, and you've started experimenting with Projects. You know Claude's broad approach differs from other models but haven't dug into system prompts or the API yet.
You write complex system prompts, configure Projects with reference files and persistent instructions, chain prompts across multi-step tasks, and make deliberate choices between Haiku, Sonnet, and Opus based on cost and performance requirements.
You use the Claude API with fine-grained parameters (temperature, tool use, multi-turn architectures), build automated workflows that combine Projects, Artifacts, and external integrations, and have a solid enough understanding of Constitutional AI to anticipate model behavior and design robust production systems.
No degree or years of experience required to take the badge. Here are the profiles it makes the most sense for.
You spec features that rely on Claude via API and need to speak your engineering team's language — context windows, tool use, refusal handling, model selection — with confidence.
You're building Claude-powered applications and want a certified proof of your API expertise — multi-turn, function calling, parameter tuning — to show clients and hiring managers.
You use Claude daily to produce long-form content, briefs, and scripts, and you want to prove your workflow goes well beyond "write me a blog post" — with Artifacts, Projects, and iterative prompting.
You recommend Claude to enterprise clients and need to be credible on its real capabilities, limitations, and differentiation from GPT-4o or Gemini in regulated or high-stakes environments.
You're building a new professional profile centered on generative AI and the Claude badge gives you a concrete, verifiable credential to stand out in a market flooded with self-declared AI experts.
Where and how your Claude badge will help you day to day.
A recruiter asks you to prove your AI tooling skills. You drop your Claude badge URL — Advanced level, detailed report attached — and the conversation moves on before any technical test is even scheduled.
You're pitching a Claude deployment project to an enterprise client. Your certified badge signals credibility instantly, especially compared to competitors whose only proof is a LinkedIn self-endorsement.
A team lead has the whole department take the badge to get an honest picture of actual Claude proficiency, identify knowledge gaps, and decide where to invest in training — without relying on self-reports.
You offer Claude workflow optimization services to small businesses. An Expert badge on your Upwork or LinkedIn profile justifies your rate and reduces the friction of landing that first project.
You've spent six months experimenting with Claude on your own. The badge gives you an objective measure of where you actually stand, and the report tells you exactly what to study next.
A master's student in AI or data science adds the Claude badge to their portfolio as concrete evidence of LLM proficiency — something that stands out next to coursework and side projects.
A few minutes to check you have everything you need.
At the end of your session you don't just get a score — here's everything that awaits you.
Get a precise 0-100 score and an official level (Novice / Proficient / Advanced / Expert) reflecting your real Claude mastery — evaluated by Claude Opus on the full transcript of your oral exam.
A structured report breaks down your performance across prompting, Artifacts, Projects, Constitutional AI knowledge, and more — with specific observations drawn from what you actually said during the exam.
Your exam audio is stored securely and stays under your control. You decide whether to share it — it's never made public without your explicit consent.
Get a unique, verifiable link to paste on your resume, LinkedIn, or portfolio. Anyone who opens it sees your score, level, and exam date — tamper-proof and no Plume account required to view.
Discover related skills you can validate with Plume.
A 15-min oral exam with an AI, a shareable badge for your recruiters.
Choose this badge · €19.99
