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Live Session Instructor - Vibe Coding

Ziplines
CompanyZiplines
CategoryUncategorised
LocationSan Carlos
RemoteRemote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted29 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
About Ziplines Ziplines Education is a category-leading education company that partners with universities to deliver industry-focused certificate courses that prepare professionals for today’s digital-first workforce. Each year, we have the opportunity to help thousands of career advancers build the knowledge, skills, and credentials they need to move their careers forward. 92% of learners would recommend our programs, and our net promoter score is consistently in the excellent range. Together, we empower adult learners to confidently pursue the career they’ve always wanted. ABOUT THE COURSE Vibe Coding: Build with AI is a 5-week, hands-on course for non-technical professionals who want to move from using AI for content and productivity to building real, working tools. Designed for product, operations, HR, sales, marketing, finance, and strategy professionals — as well as internal builders, managers, analysts, entrepreneurs, and consultants — this course cuts through the mystery of "vibe coding" and teaches learners how to turn a workplace problem into a shipped, shareable tool using AI. Most learners come to this course blocked by long engineering queues, thin IT budgets, or simply not knowing where to start. They have ideas for tools that could fix a recurring workflow gap, but no path from idea to something real. This course closes that gap by teaching a repeatable five-step framework — problem identification, planning and context setting, execution, validation, and communication and management — so learners can scope a buildable tool, direct an AI build without writing code, troubleshoot when a project stalls, and know when to ship, iterate, or hand off to a technical partner. By the end, learners won't just have experimented with AI tools. They'll have built a working prototype, a business website, an interactive web app, and a dynamic monitoring tool — plus the security review, documentation, and stakeholder communication needed to launch or hand off each one with confidence. By the end of this course, learners will be able to: - Identify a workplace problem that can be addressed with an AI-built tool, and recognize what should not be built with AI. - Scope a tool build — user need, outcome, success criteria, constraints, and MVP — and translate that context into clear AI prompts for planning and development. - Create a working prototype or web application using AI-assisted development tools such as Lovable and Claude Code. - Direct an AI build through execution prompts, review AI outputs, and recover when a build stalls or produces "almost-right" results. - Evaluate a tool build for accuracy, usability, and goal alignment, then iterate using a structured test-and-refine cycle. - Apply basic data privacy, security, and token-usage guardrails throughout an AI-assisted build. - Deploy a working app to a live, shareable URL via GitHub and Vercel, and produce launch or handoff materials covering purpose, usage, limitations, and next steps. ABOUT YOU - 5+ years of experience building or shipping web-based products, tools, or prototypes, ideally with exposure to both technical and non-technical stakeholders - Fluent in AI-assisted development workflows, with hands-on, current experience using tools such as Lovable, Supabase, Claude (Claude Chat, Claude Cowork, and Claude Code), GitHub, and Vercel - Comfortable explaining front-end, back-end, and deployment concepts in plain language to learners with no coding background - Passionate about helping non-technical professionals build real, working tools with judgment — not just enthusiasm - Skilled at diagnosing "almost-right" AI outputs and coaching learners through an iterate-refine-debug cycle rather than solving it for them - Experienced applying basic security and data-handling practices to a build (guardrails, safe data handling, pre-launch security review) - Able to speak to token efficiency and cost m
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