Case Study 02: Building a Vibe Coding Community

How a local developer community embraced and taught vibe coding practices across skill levels

Background

In April 2025, the city of Portland, Oregon, was home to a thriving but fragmented tech community. There were meetup groups for specific programming languages, startup incubators, coding bootcamp alumni networks, and university computer science departments — each operating in its own silo. What Portland did not have was a community centered on AI-assisted development. That changed when three people from very different backgrounds decided to fill the gap.

Tomás Herrera was a senior software engineer at a mid-size fintech company. He had been using GitHub Copilot since its beta and had recently switched to Claude Code for more complex development work. Tomás was convinced that AI-assisted development was fundamentally changing his profession, but he had no one to discuss this with — his colleagues were either enthusiastic but superficial about AI tools, or dismissive and skeptical.

Priya Nair was a UX designer who had started vibe coding six months earlier to prototype ideas faster. She built working prototypes of her designs instead of static mockups, using Claude to generate the front-end code. Her design team was impressed by the fidelity of her prototypes but confused about how she was producing them. Priya wanted to teach her approach to other designers.

Marcus Johnson was a high school computer science teacher who had noticed something surprising: several of his students were building more sophisticated projects than his curriculum covered, using AI tools outside of class. He was wrestling with how to integrate AI-assisted development into his teaching without undermining the fundamentals he believed students needed.

The three of them met at a local tech conference in March 2025. During a panel discussion about AI in software development, they each asked questions from the audience that revealed their shared interests. Over coffee afterward, they hatched a plan: they would start a community dedicated to the practice and pedagogy of vibe coding.

Phase 1: The First Meetup (May 2025)

Tomás, Priya, and Marcus spent a month planning before their first event. They made several deliberate design decisions that would prove critical to the community's success.

Decision 1: Radical inclusivity. The community would welcome everyone from complete beginners to seasoned engineers. This was controversial — Tomás initially wanted to focus on experienced developers, arguing that beginners would slow down discussions. Priya pushed back: "If vibe coding is really about democratizing software development, our community has to reflect that." Marcus agreed: "My students are some of the most creative vibe coders I've seen. Experience with traditional coding doesn't correlate with vibe coding effectiveness as much as you'd think." Tomás conceded the point.

Decision 2: Project-centered, not tool-centered. Meetings would focus on what people were building, not which tools they were using. This prevented the community from becoming a fan club for any specific product and kept discussions grounded in practical outcomes.

Decision 3: Honest culture. Members would share failures and frustrations alongside successes. The organizers modeled this by sharing their own struggles openly — Tomás talked about an AI-generated database migration that nearly destroyed production data, Priya shared a prototype that looked beautiful but had unusable accessibility, and Marcus described a classroom exercise that went completely off the rails.

The first meetup took place on May 14, 2025, at a coworking space in Portland's Pearl District. They expected 15 people. Forty-two showed up. The room was standing-room only.

The format was simple: three lightning talks (5 minutes each) followed by an hour of open working time where people could pair up and build things together. The lightning talks covered: - Tomás: "How I Refactored a 10,000-Line Codebase in a Weekend with AI" - Priya: "From Figma to Functional: Vibe Coding for Designers" - Marcus: "What My Students Taught Me About AI-Assisted Development"

The open working time was chaotic but electric. Complete strangers paired up across skill levels. A marketing director worked with a backend engineer to build a customer survey tool. Two college students helped a retiree build a website for his woodworking hobby. Marcus's high school students, who had tagged along, ended up teaching several adults how to use Claude Code.

Lesson: The energy of the first meetup came from the diversity of the attendees. When people with different skill levels and backgrounds work together on vibe coding projects, the results are often more interesting than when experienced developers work with other experienced developers. Domain knowledge from non-technical participants frequently led to more creative and practical projects.

Phase 2: Growing the Community (June-August 2025)

The success of the first meetup created both opportunity and challenge. The community grew rapidly — within three months, monthly meetups attracted 60-80 people, and a Discord server had over 400 members. Managing this growth required thoughtful structure.

The Four Tracks

The organizers established four parallel tracks within the community, each designed for different experience levels and goals:

Track 1: First Steps. For people who had never written code or used AI tools for development. Sessions followed a structured curriculum loosely based on Chapters 1-7 of this textbook. Each session included a guided project that participants completed with AI assistance. The goal was to get every participant from zero to a functioning personal project in four sessions.

Track 2: Builders. For people with some vibe coding experience who wanted to build more ambitious projects. These sessions were less structured — participants worked on personal projects with mentorship from more experienced members. Prompting techniques (Chapters 8-14) and practical building skills (Chapters 15-23) were the focus.

Track 3: Professionals. For working developers and technical professionals who wanted to integrate AI tools into their professional practice. Discussions focused on architecture (Chapter 24), security (Chapter 27), deployment (Chapter 29), and team workflows (Chapter 32). This track also addressed organizational adoption — how to introduce vibe coding practices into a workplace.

Track 4: Educators. For teachers, trainers, and mentors. Marcus led this track, which focused on pedagogy: how to teach vibe coding effectively, how to assess AI-assisted work fairly, and how to balance AI tool usage with foundational learning. This track drew participants from K-12 schools, universities, coding bootcamps, and corporate training departments.

The Mentorship Pairs

One of the community's most successful innovations was a structured mentorship program. Each month, interested members were paired: one more experienced, one less experienced. Pairs committed to meeting weekly for an hour, either in person or virtually, to work on the mentee's project. The program had three rules:

  1. The mentee chooses the project. The project must be something the mentee genuinely wants to build, not an academic exercise.
  2. The mentor guides, not codes. The mentor helps with strategy, evaluation, and debugging, but the mentee does all the prompting and decision-making.
  3. Both reflect. At the end of each session, both mentor and mentee write a brief reflection on what they learned. Mentors frequently reported learning as much as mentees.

By August, the mentorship program had produced remarkable results. A bakery owner built an inventory management system. A social worker created a resource referral tool for her clients. A retired engineer built a weather station data visualization for his neighborhood. Each project was practical, personal, and genuinely useful.

Lesson: The mentorship program's success rested on two principles: learner autonomy (choosing their own projects) and guided judgment (mentors teaching evaluation and decision-making rather than writing prompts for the mentee). These mirror the teaching principles described in Section 42.7.

Phase 3: Community Projects (September-November 2025)

In September, the community attempted something new: a collaborative project. The idea came from a Track 1 participant named Diana, a retired librarian who had been volunteering at a local food bank. She described the problem during an open discussion:

"The food bank tracks everything on paper. Donations come in, we write them on a clipboard. Volunteers sign up by calling or emailing. Clients come in, we check names off a printed list. There has to be a better way."

The community voted to take this on as a group project. Twenty-three members volunteered to contribute, ranging from complete beginners to senior engineers. Tomás organized them into small teams, each responsible for a different component:

  • Team Inventory: A system for tracking food donations, inventory levels, and expiration dates
  • Team Volunteers: A volunteer scheduling and coordination system
  • Team Clients: A client registration and visit tracking system
  • Team Dashboard: An administrative dashboard combining data from all three systems

Each team used the specification-driven approach from Chapter 10: they wrote detailed specifications before generating any code. Diana participated in every team's specification process, providing the domain knowledge that none of the developers had. Her understanding of how the food bank actually operated — the workflows, the edge cases, the human dynamics — was invaluable.

The project took ten weeks. It was messy. Teams made different technology choices that had to be reconciled. The integration between systems was harder than anyone expected. A security review revealed that the client tracking system — which handled personal information about food-insecure families — needed significant hardening. Several volunteers dropped off partway through, and their work had to be redistributed.

But the result was a functional system that the food bank began using in December 2025. Diana cried at the launch event. "I have been volunteering here for seven years," she said. "I never thought I could help build something like this."

The food bank project became a template for future community projects. Over the following months, the community built tools for a community garden cooperative, a tutoring center, and a neighborhood emergency preparedness group.

Lesson: Community projects serve multiple purposes simultaneously: they produce useful software for organizations that cannot afford custom development, they provide real-world learning experiences for community members at all levels, and they strengthen the community itself through shared purpose and collaborative accomplishment.

Phase 4: Scaling and Sustainability (December 2025 - Ongoing)

By late 2025, Portland Vibe Coders (as the community had informally named itself) faced the challenge of sustainability. The initial burst of volunteer energy from the organizers was not sustainable long-term. They needed structure, funding, and distributed leadership.

Organizational Structure

The community formalized its governance with a simple structure: - A rotating leadership team of five people, each serving six-month terms - Track leads for each of the four tracks, responsible for session planning - A community manager (a part-time paid role funded by corporate sponsorships) handling logistics - An advisory board of local tech leaders and educators providing strategic guidance

Funding Model

The community adopted a hybrid funding model: - Monthly meetups remained free and open to all - Intensive workshops (full-day or multi-day) charged modest fees on a sliding scale - Corporate sponsorships provided the majority of operating funds, with clear guidelines preventing sponsors from controlling content - A small grant from a local foundation supported the community projects program

Knowledge Repository

Marcus championed the creation of a community knowledge base — a publicly accessible collection of: - Prompt templates organized by project type and difficulty level - Case studies of community projects with honest assessments of what worked and what did not - Curriculum materials for the First Steps track - Video recordings of lightning talks and workshops - A curated reading list, updated monthly

This knowledge base became one of the community's most valuable assets. Other cities referenced it when starting their own vibe coding communities.

Spreading the Model

By early 2026, the Portland Vibe Coders model had inspired similar communities in Seattle, Denver, Austin, and Minneapolis. The organizers created a "community starter kit" — a set of templates, guidelines, and lessons learned that new communities could adapt. The kit included: - A facilitator guide for the first three meetups - Track descriptions and curriculum outlines - Mentorship program guidelines - Community project selection and management frameworks - A code of conduct template

Tomás, Priya, and Marcus each spoke at conferences about the community model. Their message was consistent: vibe coding communities thrive when they are inclusive, project-centered, honest about failures, and grounded in genuine service to their members and their city.

Outcomes and Impact

Eighteen months after the first meetup, the Portland Vibe Coders community could point to measurable outcomes:

  • 500+ active members across all four tracks
  • 120+ mentorship pairs completed, with a 78% completion rate
  • 12 community projects deployed for local nonprofits and community organizations
  • 85% of Track 1 participants completed at least one functioning personal project
  • 3 members transitioned to technology careers, citing the community as a primary factor
  • 15 members integrated vibe coding practices into their non-technical jobs
  • 8 other cities launched communities using the Portland model

But the numbers only told part of the story. The qualitative impact was harder to measure but equally important: - A food bank operating more efficiently because a retired librarian knew what they needed - A high school teacher integrating AI tools into his curriculum with confidence and thoughtfulness - A UX designer mentoring a social worker who now builds tools for her clients - A senior engineer who found renewed excitement in his career by teaching beginners - Dozens of people who discovered that the barrier between "technical" and "non-technical" was thinner than they had believed

Lessons for Building Your Own Community

What Worked

  1. Radical inclusivity from day one. Welcoming all skill levels created richer interactions and prevented the community from becoming an echo chamber of experienced developers.

  2. Project-centered culture. Focusing on what people build rather than which tools they use kept discussions practical and prevented tribal tool loyalty from fragmenting the community.

  3. Honest failure sharing. When organizers modeled vulnerability by sharing their own failures, it created psychological safety for everyone to learn openly.

  4. Structured mentorship. The mentorship program's three rules (learner chooses the project, mentor guides rather than codes, both reflect) produced deep, lasting learning.

  5. Community service projects. Building software for local organizations gave the community purpose beyond self-improvement and created tangible evidence of vibe coding's value.

  6. Formalized sustainability. Transitioning from volunteer-driven to structured governance was painful but necessary. Communities that rely on founding energy alone rarely survive past the first year.

What Was Difficult

  1. Managing skill-level diversity. Even with four tracks, sessions sometimes frustrated beginners (too fast) and experienced developers (too slow) simultaneously. The mentorship program partially addressed this.

  2. Maintaining quality in community projects. Software built by volunteers with varying skill levels required rigorous review. Two early community projects had to be significantly reworked after deployment.

  3. Preventing burnout. The three founders each experienced burnout at different points. Distributing leadership and formalizing the community manager role were essential responses.

  4. Navigating corporate sponsorship. Two potential sponsors wanted to make their products the community's "official" tools. Declining these sponsorships was financially costly but preserved the community's independence and tool-agnostic culture.

  5. Balancing online and in-person. The Discord server grew faster than in-person attendance. Maintaining the value of physical meetups required intentional programming that could not be replicated online.

Discussion Questions

  1. The Portland Vibe Coders made a deliberate decision to be tool-agnostic rather than focusing on a specific AI coding assistant. What are the advantages and disadvantages of this approach? How might the community have been different if it had centered on a single tool?

  2. The food bank project revealed that domain knowledge (Diana's understanding of food bank operations) was as valuable as technical skill. How should communities structure projects to ensure domain experts are meaningfully involved, not just consulted?

  3. Marcus initially struggled with how to reconcile AI-assisted development with teaching programming fundamentals. How would you approach this tension in an educational setting? What does the Portland community's experience suggest about the relationship between vibe coding and foundational knowledge?

  4. The community's mentorship program had a 78% completion rate, meaning 22% of pairs did not finish. What factors might contribute to incomplete mentorships, and how would you design the program to improve completion rates?

  5. Several cities started their own communities using the Portland model. What aspects of the model are likely transferable to different contexts, and what aspects might need significant adaptation for communities in different cities, countries, or cultural contexts?