GenAI PMvibe-coding
An AI-native development approach where builders use AI tools to rapidly create software. The newsletter treats it as a growth and product-building methodology.
Key Highlights
- Vibe-coding is an AI-native way of building software that uses prompts and AI tools to rapidly create prototypes and products.
- For AI PMs, it shortens the path from idea to working software and expands who can contribute directly to building.
- Newsletter examples connect vibe-coding to Google AI Studio, Notion’s prototyping workflows, and real app growth like WrestleAI.
- The concept is powerful but not effortless; strong planning, debugging discipline, and product judgment still matter.
- Related tools such as Claude Code, Cloud Code, CodeEx, Lovable, and Stitch form part of the emerging vibe-coding ecosystem.
Overview
Vibe-coding is an AI-native software development approach in which builders use large language models, agentic coding tools, and prompt-driven interfaces to rapidly create products with less manual coding. In the newsletter, it appears both as a practical product-building methodology and as a broader shift in how non-engineers, designers, and PMs can participate directly in software creation. Rather than treating code as a specialized bottleneck, vibe-coding treats AI as a collaborative layer for generating UI, backend logic, specs, prototypes, and iterations from natural language.
For AI Product Managers, vibe-coding matters because it compresses the distance between idea, prototype, and shipped product. It enables faster validation of concepts, lowers the cost of experimentation, and expands who can contribute to building. At the same time, the newsletter coverage makes clear that vibe-coding is not simply “build fast with AI.” The best outcomes still require sharp product judgment, clear plans, disciplined iteration, and awareness of AI tooling limitations, especially around debugging, architecture, and tool-selection bias.
Key Developments
- 2026-02-09: Lenny Rachitsky highlighted Lazar Jovanovic as the first full-time “vibe coder,” using an AI-aligned markdown file system, a 4×4 debugging workflow, and 4–5 parallel prototypes to build products without writing code directly.
- 2026-03-08: Tal Raviv shared a detailed, non-hype account of spending significant time vibe-coding a landing page for Familiar, pushing back on the idea that AI-native building is always quick or effortless.
- 2026-03-10: Simon Willison reflected on how LLMs can bias technology choices toward tools well represented in training data, a useful caution for teams adopting vibe-coding stacks and workflows.
- 2026-03-20: Google AI launched a full-stack vibe-coding environment in Google AI Studio, enabling end-to-end app development across UI, backend logic, and data pipelines through AI-powered code generation.
- 2026-03-21: Google AI expanded that AI Studio direction into a fuller “vibe coding” experience with smarter agents, multiplayer collaboration, secure login and storage, real-world integrations, and Stitch as an AI-native design canvas.
- 2026-03-23: Santiago argued that agentic coding workflows need a clear plan or they devolve into vibe-coding with unnecessary extra steps, emphasizing the importance of structure and intent.
- 2026-03-24: Philipp Schmid published a beginner-friendly guide to vibe-coding in Google AI Studio, covering prompts through deployment, and highlighting private-by-default apps, Firebase setup, in-UI drawing feedback, and instant Cloud Run publishing.
- 2026-05-04: At Notion, designers and PMs used vibe-coding tools like Cloud Code and CodeEx to prototype AI features in code, reducing terminal intimidation and moving early exploration from static mockups into working interfaces.
- 2026-05-06: Logan Kilpatrick rolled out edit mode in AI Studio Vibe Coding, adding component selection for quick edits, pen-based UI annotation, and image swapping via Nano Banana or user uploads.
- 2026-06-16: George Lampropoulos used AI-first development with Vibe Coding’s Oracles and RevenueCat to build and scale WrestleAI, focusing on a single standout feature and an Instagram influencer funnel to surpass 100K downloads and approach $200K in revenue.
Relevance to AI PMs
1. Prototype product ideas without waiting on full engineering cycles. AI PMs can use vibe-coding tools to turn PRDs, prompts, or rough flows into functional prototypes for user testing, internal demos, or investor conversations.
2. Bring design, product, and engineering closer together. The newsletter examples show designers and PMs working directly in code-like environments, which can reduce handoff friction and make iteration faster and more grounded in real product behavior.
3. Improve experimentation velocity while keeping product rigor. Vibe-coding is most useful when paired with a clear plan, tight scope, and strong evaluation criteria. PMs can use it to test a “gotcha feature,” compare multiple prototype directions, or validate onboarding and monetization loops before deeper investment.
Related
- Google AI Studio / AI Studio / ai-studio: A major platform featured repeatedly in the newsletter as a full-stack environment for vibe-coding, from generation to deployment.
- Claude Code, Cloud Code, CodeEx, Lovable, ChatPRD: Tools associated with AI-native building, coding, prototyping, and spec creation that lower barriers for PMs and designers.
- Stitch: Google’s AI-native design canvas, connected to the broader vibe-coding workflow by turning natural-language prompts into product UI concepts.
- Nano Banana: Used within AI Studio edit flows for swapping image assets during iterative product editing.
- Oracles: Referenced in the WrestleAI example as part of an AI-first development stack used to scale a consumer app.
- Notion: A concrete example of an organization where designers and PMs used vibe-coding tools to prototype AI features directly.
- Santiago, Simon Willison, Tal Raviv, Lazar Jovanovic, Peter Yang, George Lampropoulos: Individuals connected to the concept through critique, reflection, adoption patterns, or practical case studies.
- CLI: Relevant because several vibe-coding workflows reduce the intimidation traditionally associated with terminal-based development, widening access for non-engineers.
Newsletter Mentions (11)
“George Lampropoulos built and scaled WrestleAI using AI-first development with Vibe Coding’s Oracles and RevenueCat, focusing on a single "gotcha feature" and an Instagram influencer funnel to reach 100K+ downloads and nearly $200K in revenue.”
#13 ▶️ How a TJ Maxx Cashier Built a $200K App With AI Greg Isenberg George Lampropoulos built and scaled WrestleAI using AI-first development with Vibe Coding’s Oracles and RevenueCat, focusing on a single "gotcha feature" and an Instagram influencer funnel to reach 100K+ downloads and nearly $200K in revenue.
“Logan Kilpatrick rolled out edit mode in AI Studio Vibe Coding, letting you select components for quick edits, draw annotations directly on the UI with a pen, swap image assets via Nano Banana, or upload your own content.”
#5 𝕏 Logan Kilpatrick rolled out edit mode in AI Studio Vibe Coding, letting you select components for quick edits, draw annotations directly on the UI with a pen, swap image assets via Nano Banana, or upload your own content.
“Using vibe coding tools such as Cloud Code and CodeEx, designers and PMs at Notion prototype AI features in code, reducing terminal intimidation and accelerating iteration.”
#8 ▶️ Why cultivating agency matters more than cultivating skills in the AI era | Max Schoening (Notion) Lennys Podcast Notion’s design team built a minimal LLM-friendly terminal playground to prototype AI chat interfaces, moving initial design work from Figma into code. The playground consists of a small codebase created by two designers and Max Schoening, optimized for one-shot interactions with LLMs and operated entirely via the terminal. Using vibe coding tools such as Cloud Code and CodeEx, designers and PMs at Notion prototype AI features in code, reducing terminal intimidation and accelerating iteration.
“Philipp Schmid shares a beginner-friendly guide to vibe-coding in Google AI Studio, walking through prompts to deployment.”
#10 𝕏 Philipp Schmid shares a beginner-friendly guide to vibe-coding in Google AI Studio, walking through prompts to deployment. He highlights private-by-default apps, one-click Firebase databases with auth, in-UI drawing for feedback, and instant Cloud Run publishing. #18 in Claire Vo argues leaders must ditch “I’m blocked” and instead use AI tools like Claude Code, Devin, Lovable, and ChatPRD to prototype, design, and spec in minutes.
“Santiago argues that AI agentic coding workflows require a clear plan—or they just become “vibe-coding” with needless extra steps.”
#10 𝕏 Santiago argues that AI agentic coding workflows require a clear plan—or they just become “vibe-coding” with needless extra steps.
“Google AI rolled out a full-stack “vibe coding” experience in AI Studio—complete with smarter agents, multiplayer collaboration, secure login/storage and real-world service integrations—and unveiled Stitch, an AI-native design canvas that turns natural-language prompts into p...”
#1 𝕏 Google AI rolled out a full-stack “vibe coding” experience in AI Studio—complete with smarter agents, multiplayer collaboration, secure login/storage and real-world service integrations—and unveiled Stitch, an AI-native design canvas that turns natural-language prompts into p...
“Google AI launched a full-stack Vibe coding environment in Google AI Studio. It enables end-to-end app development—UI, back-end logic, and data pipelines—through AI-powered code generation.”
#3 𝕏 Google AI launched a full-stack Vibe coding environment in Google AI Studio. It enables end-to-end app development—UI, back-end logic, and data pipelines—through AI-powered code generation. #4 𝕏 LlamaIndex 🦙 just open-sourced LiteParse, a zero-Python CLI & TypeScript-native library for layout-aware parsing of PDFs, Office docs, and images—preserving columns, tables, and alignment with built-in OCR, built for agent and LLM pipelines.
“#15 📝 Simon Willison Perhaps not Boring Technology after all - Reflection on the concern that LLMs might bias technology choices toward well-represented tools in their training data, making it harder for new tools to gain traction.”
This item is not explicitly about vibe coding, but it is about how LLMs shape technology selection and adoption. It is relevant to PMs thinking about AI-driven tooling choices and ecosystem effects.
“in Tal Raviv Tal Raviv spent significant time “vibe coding” a landing page for Familiar and shares a theater-free, detailed account to challenge the industry’s obsession with framing “quick and easy” as the hallmark of AI-forward work.”
in Tal Raviv Tal Raviv spent significant time “vibe coding” a landing page for Familiar and shares a theater-free, detailed account to challenge the industry’s obsession with framing “quick and easy” as the hallmark of AI-forward work.
“𝕏 Lenny Rachitsky spotlights Lazar Jovanovic’s role as the first full-time “vibe coder,” using an AI-aligned markdown file system, a 4×4 debugging workflow and 4-5 parallel prototypes to rapidly build products without writing code.”
#16 𝕏 Lenny Rachitsky spotlights Lazar Jovanovic’s role as the first full-time “vibe coder,” using an AI-aligned markdown file system, a 4×4 debugging workflow and 4-5 parallel prototypes to rapidly build products without writing code.
Related
Anthropic’s coding product/blog referenced in a customer story about Cognition’s use of Claude Fable 5. For AI PMs, it highlights enterprise coding adoption narratives.
A PM/influencer who shares practical AI workflow experiments around planning, design, and execution. He is cited using Fable, Claude Design, and GPT-5.6 together in a product-building workflow.
A developer and AI commentator quoted here in relation to OpenAI’s clarification of ChatGPT Work behavior. He is relevant as an interpreter and critic of product messaging.
A creator/commentator predicting the future of AI video experiences. The newsletter cites him on interactive livestream-style video and personalized ads.
Google’s app-building environment, here highlighted for globally unique ai.studio subdomains and instant publishing. For PMs, it represents low-friction deployment and branded app distribution.
Writer/observer cited for reframing agent building as a stack of LLM primitives and persistent memory.
Cloud Code appears to be a coding agent or coding workflow used to generate launch videos from websites. The newsletter describes it as working with Fable 5 and HyperFrames.
An AI-first product management tool or startup referenced by Claire Vo. The newsletter uses it in a discussion of shipping an AI-first version of an app without traditional PM tooling.
An opinionated build environment for coding with AI that uses a coding agent. The newsletter notes that projects can be exported from it directly to Antigravity.
A documentation and knowledge-management tool used by Codex to retrieve context and convert documents into live product prototypes. It illustrates how PMs can connect written specs to agent workflows.
A Google DeepMind skill or interface for AI-assisted history analysis. It integrates Gemini with expert models to help translate and study ancient texts using plain English.
A no-code AI app builder referenced here as the platform used to build a production-grade SaaS product. For PMs, it illustrates how agentic coding is changing build-vs-buy and software creation economics.
An image asset swapping tool or capability referenced in AI Studio editing workflows. Useful for PMs building multimodal UI-editing experiences.
A vibe-coding tool mentioned alongside Cloud Code in Notion’s prototyping workflow. It supports direct code-based iteration for AI feature exploration.
An open-source app that captures screen and clipboard state as Markdown for AI agents. It is positioned as a live-work-context tool for local agent workflows.
A Google Labs AI product for design. It is positioned as a creative product-making tool in Google’s experimental portfolio.
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