Visual scenarios: modules, routers, aggregators, iterators, error handling.
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 the world you actually know Make: complex multi-module scenarios, advanced error handling, iterators, aggregators — a 15-min AI oral exam that goes way beyond a self-declared LinkedIn skill.
The Plume Make (Integromat) badge validates your ability to design, optimize, and debug visual automation scenarios in Make. A 15-minute oral exam with a real-time AI examiner probes you on the things that actually matter: architecting complex scenarios with routers and filters, using iterators and aggregators to transform nested JSON structures, implementing advanced error handling with Resume/Rollback/Commit/Break handlers, managing operations and cycles to stay within your plan's quota, and knowing when Make is the right tool versus Zapier, n8n, or custom code.
Unlike a self-declared LinkedIn skill or an online course certificate, the Plume badge is backed by a structured oral exam analyzed by Claude Opus, which reads the full transcript and produces a 0-100 score with a certified level (Novice, Proficient, Advanced, or Expert). Every answer is evaluated on technical accuracy, depth of reasoning, and your ability to make grounded trade-off decisions — exactly what a client or a technical recruiter would probe in a real interview.
This badge is built for freelancers who want to justify their rates with proof, automation consultants pitching projects to new clients, ops managers and growth hackers who have shipped complex internal workflows, and anyone who wants to turn an invisible day-to-day skill into a shareable, verifiable credential. If you connect Airtable, Notion, Slack, custom webhooks, or third-party APIs in Make on a regular basis, this exam was designed for you.
Here are the concrete dimensions the AI examines during the 15-minute oral.
Designing multi-module scenarios with routers, conditional filters, nested sub-scenarios, and parallel flow management to handle advanced business logic in a maintainable way.
Combining iterators and aggregators (Array Aggregator, Text Aggregator) to transform nested JSON arrays, including common pitfalls around data type mapping and bundle handling.
Configuring error handlers (Resume, Rollback, Commit, Break) in combination with Data Stores to build scenarios that recover gracefully or roll back cleanly when something goes wrong in production.
Controlling cycle counts, eliminating unnecessary operations with upstream filters, and architecting scenarios to stay within your Make plan's quota without sacrificing business logic.
Using Data Stores as persistent memory between scenario runs to store state, counters, deduplication keys, or reference data — and knowing when a Data Store is the wrong abstraction.
Reading and interpreting Make execution logs, pinpointing failing modules, reproducing edge cases in test mode, and setting up monitoring to catch silent failures before they affect production data.
Knowing when to recommend Make over Zapier, n8n, or custom code — and when to advise the opposite. Weighing data volume, maintainability, operations cost, team skills, and scalability needs.
Understanding Make's recent AI capabilities (AI Agents, native OpenAI modules, Make Grid) and integrating them into hybrid workflows that combine classical automation with AI-powered steps.
Final scoring is performed by Claude (Anthropic), which reads back the full transcript and applies this weighted criteria grid.
Precision in using modules, routers, filters, iterators, aggregators, Data Stores, and webhooks. The candidate demonstrates knowledge of the platform's internal mechanics, not just its visual interface.
Ability to walk through real debugging situations, cycle optimization decisions, or error handling implementations with justified technical choices and measurable outcomes on actual scenarios.
Quality of trade-offs presented: explaining why Resume beats Rollback in a given context, why filtering before iterating matters, or why a scenario warrants a move to n8n or a proper backend.
Understanding Make's role in a broader automation stack: native integrations (Airtable, Notion, Slack, Google Workspace), third-party APIs via HTTP/JSON module, and an honest comparison with competing tools.
Ability to explain complex technical concepts clearly and concisely, as you would to a client or a non-technical stakeholder who needs to approve a solution — without jargon overload.
A Plume session takes about 20 minutes, from tech check to badge delivery.
The AI checks your audio quality and confirms the exam rules: 15 minutes, open-ended answers, no visual support needed. We make sure you're set up before anything starts.
You introduce yourself briefly and walk through the most complex Make scenario you've built recently: module count, connected services, and the business problem it solved. The AI calibrates the rest of the exam to your profile.
The AI examiner digs into your real skills: advanced error handling with specific handlers, iterators and aggregators on nested JSON, operations optimization, production incident diagnosis, and how you position Make against its alternatives.
The AI asks when you'd advise a client against Make, what you see as its real limits, and how you choose between Make and custom code or a proper backend — probing your architectural maturity and honest self-awareness.
Claude Opus analyzes the full transcript and delivers a 0-100 score with a certified level (Novice, Proficient, Advanced, Expert), a detailed point-by-point report, and a shareable badge with a unique public URL.
Your score out of 100 translates into a level a recruiter can grasp at a glance.
You use Make for simple 5-10 module scenarios, mainly with native apps like Gmail, Google Sheets, or Slack. You can trigger scenarios via webhooks or schedules, but you haven't yet worked with iterators, aggregators, or any structured error handling strategy.
You build scenarios with routers, filters, and basic iterators. You've connected at least one third-party API via the HTTP/JSON module and can read execution history to debug issues. You understand operations costs and are starting to optimize cycles, but advanced error handling is still limited.
You handle iterators and aggregators confidently for complex JSON transformations, use Data Stores to persist state between runs, and have deployed error handlers (Resume, Rollback, Commit) on production scenarios. You can make informed decisions about when Make is the right tool for the job.
You design multi-scenario automation architectures with sub-scenarios, transactional Data Stores, and multi-level error handling. You push the platform's limits, integrate native AI features (AI Agents, Make Grid), and know exactly when Make is no longer the right choice and what to use instead.
No degree or years of experience required to take the badge. Here are the profiles it makes the most sense for.
You sell Make projects to clients and want a credible signal to justify your rates and stand out from the flood of self-declared automation experts on freelance platforms.
You've automated internal processes (onboarding, reporting, CRM sync) with Make and want to document that skill beyond your current role — on a resume, a public profile, or a portfolio.
You pitch no-code solutions to clients and need a factual credential to include in your proposals, client deliverables, or independent consultant profile to build trust from day one.
You learned Make through courses or personal projects and need an external, credible validation to break into the automation job market without traditional professional experience on your CV.
You work alongside developers and ops teams and want to certify that your Make skills are technical enough to autonomously own automation projects and make sound architectural decisions.
Where and how your Make (Integromat) badge will help you day to day.
A Make freelancer adds the Expert badge to their Malt or Upwork profile. Faced with two otherwise similar candidates, a client picks the one who has verifiable proof of skill level — not just a LinkedIn endorsement.
A candidate applying for a No-Code Ops Lead role shares their Advanced badge URL before the interview. The recruiter reads the detailed report and arrives with specific follow-up questions instead of testing basics.
A no-code agency attaches their consultants' Make badges to an RFP response, objectively demonstrating the team's skill level instead of listing years of experience that can't be independently verified.
An ops manager scores at the Proficient level. The report flags advanced error handling as a gap. They know exactly what to study before retaking the exam to reach the Advanced level.
A RevOps team of five each takes the badge. The manager compares scores to identify who can be the internal Make expert and who needs extra support on complex scenario design before taking on high-stakes automation projects.
A career switcher adds the badge alongside screenshots of their Make scenarios in a no-code portfolio. The badge provides the verbal and analytical dimension that screenshots alone can never prove.
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.
You get a precise score and a certified level (Novice, Proficient, Advanced, or Expert) on your Make skills, generated by Claude Opus after a full analysis of your oral exam transcript.
A point-by-point breakdown of your answers: what you nailed (complex scenarios, error handling, operations optimization) and specific improvement areas to focus on before your next project or re-exam.
Your oral recording is stored securely and stays private. You can choose to share it with a recruiter or client to prove the authenticity of your session and your reasoning process.
A public link to your Make badge, ready to embed on LinkedIn, Upwork, your no-code portfolio, or a client proposal. Every visitor sees your level, your score, and the certification date.
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
