vibe-coding
AI-assisted building pattern where products or workflows are created iteratively with models rather than purely through manual coding.
Key Highlights
- Vibe-coding describes iterative product and workflow creation with AI models instead of relying only on manual coding.
- Google AI Studio emerged as a major example, adding full-stack generation, editing, deployment, and collaboration features.
- Notion and Lovable show how PMs, designers, and individual contributors can use AI-assisted building to accelerate experimentation.
- The coverage also warns that vibe-coding needs a clear plan or it can become unstructured iteration with extra steps.
- Examples like WrestleAI connect vibe-coding to measurable outcomes such as downloads, revenue, and faster product validation.
vibe-coding
Overview
Vibe-coding is an AI-assisted building pattern where products, prototypes, features, or workflows are created iteratively with models rather than purely through manual coding. In practice, it often means describing intent in natural language, letting AI generate or modify code and UI, and then refining the result through rapid back-and-forth edits. Across the mentions here, vibe-coding spans full-stack app creation, UI editing, agentic coding workflows, design-to-code experimentation, and lightweight prototyping by PMs, designers, and individual contributors.For AI Product Managers, vibe-coding matters because it compresses the distance between idea, prototype, and shipped experience. The examples in Google AI Studio, Notion, Lovable, and WrestleAI show that non-traditional builders can now participate much more directly in product creation, experimentation, and deployment. At the same time, the coverage also highlights an important caveat: without a clear plan, vibe-coding can become unstructured iteration or “needless extra steps,” especially in more agentic workflows.
Key Developments
- 2026-03-08: Tal Raviv described spending significant time “vibe coding” a landing page for Familiar, pushing back on the idea that AI-forward building is always quick or effortless.
- 2026-03-10: Simon Willison reflected on how LLMs can bias technology choices toward tools that are better represented in training data, a relevant concern for PMs adopting AI-driven building workflows.
- 2026-03-20: Google AI launched a full-stack vibe-coding environment in Google AI Studio for end-to-end app development across UI, back-end logic, and data pipelines through AI-powered code generation.
- 2026-03-21: Google AI expanded the AI Studio experience with smarter agents, multiplayer collaboration, secure login and storage, real-world integrations, and introduced Stitch as an AI-native design canvas connected to this workflow.
- 2026-03-23: Santiago argued that agentic coding workflows need a clear plan, or they risk becoming “vibe-coding” with unnecessary extra steps.
- 2026-03-24: Philipp Schmid shared a beginner-friendly guide to vibe-coding in Google AI Studio, covering prompting through deployment, including private-by-default apps, Firebase setup, in-UI drawing feedback, and Cloud Run publishing.
- 2026-05-04: At Notion, designers and PMs used tools such as Cloud Code and CodeEx to prototype AI features in code, reducing terminal intimidation and speeding iteration.
- 2026-05-06: Logan Kilpatrick rolled out edit mode in AI Studio Vibe Coding, adding component selection for quick edits, pen-based UI annotations, and image asset swapping via Nano Banana or uploads.
- 2026-06-16: George Lampropoulos used AI-first development with Vibe Coding’s Oracles and RevenueCat to build and scale WrestleAI, focusing on one “gotcha feature” and an influencer-led distribution funnel to reach 100K+ downloads and nearly $200K in revenue.
- 2026-09-28: Lenny’s Podcast highlighted Elena Verna’s work at Lovable, where she used Lovable and AI to take pricing and packaging from research and analysis through production deployment as a high-impact individual contributor.
Relevance to AI PMs
1. Prototype product ideas faster and more directly. AI PMs can use vibe-coding tools to move from spec or prompt to working prototype without waiting for a full engineering cycle, especially for AI interfaces, internal tools, and workflow automation.2. Expand who can build inside the product org. The examples from Notion and Lovable suggest PMs, designers, and ICs can contribute directly to coded experiments, reducing handoff friction and making product iteration more cross-functional.
3. Use it for validation, not just generation. The strongest use cases in these mentions tie vibe-coding to deployment, experiments, and measurable outcomes. PMs should pair fast AI-generated builds with clear plans, guardrails, and success metrics so the workflow does not devolve into unstructured exploration.
Related
- Google AI Studio / AI Studio: A major platform example of full-stack vibe-coding, covering generation, editing, deployment, and integrations.
- Claude Code, Cloud Code, CodeEx: Coding-oriented tools mentioned alongside vibe-coding workflows for prototyping and iteration.
- Lovable: A product environment associated with AI-assisted building and production-oriented experimentation.
- Stitch: Google AI’s design canvas that connects natural-language prompting to product and UI creation.
- ChatPRD: Relevant as a companion workflow for quickly generating product specs before or alongside building.
- Oracles: Referenced in the WrestleAI example as part of an AI-first development stack.
- Notion: Example of designers and PMs using vibe-coding-adjacent tools to prototype AI features in code.
- Simon Willison, Tal Raviv, Santiago, George Lampropoulos, Elena Verna: People who either critiqued, documented, or demonstrated practical vibe-coding workflows.
- AI agents / CLI: Closely related interaction modes, especially where natural-language direction and terminal-based execution meet.
Frequently asked questions
What is vibe-coding?
AI-assisted building pattern where products or workflows are created iteratively with models rather than purely through manual coding.
What should AI product managers know about vibe-coding?
Vibe-coding describes iterative product and workflow creation with AI models instead of relying only on manual coding. Google AI Studio emerged as a major example, adding full-stack generation, editing, deployment, and collaboration features. Notion and Lovable show how PMs, designers, and individual contributors can use AI-assisted building to accelerate experimentation.
Explore this topic
Newsletter Mentions (12)
“Lennys Podcast commented on Elena Verna’s work as a high-impact individual contributor at Lovable, where she uses Lovable and AI to take pricing and packaging from research and analysis through production deployment.”
#8 ▶️ The rise of HI-ICs | Elena Verna (Lovable) Lennys Podcast **Lennys Podcast** commented on Elena Verna’s work as a high-impact individual contributor at Lovable, where she uses Lovable and AI to take pricing and packaging from research and analysis through production deployment. Verna reported that 42 of 51 surveyed people managers wanted to return to an IC role; she retained her pay grade after becoming a high-impact IC and has run experiments that cost Lovable many millions of dollars.
“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.
Related
Anthropic’s coding agent/environment used here to control physical tools in a long-running home experiment.
A product-focused creator who demonstrates AI builds and critiques product UX/packaging. In this issue he showcases Tabi and discusses simplifying product surfaces.
A prominent AI blogger and commentator referenced in connection with an article on token reselling and fraud. He is cited as the source of the newsletter item discussing the marketplace and API-key abuse.
A newsletter-mentioned author who shared an article on converged databases. The mention is brief and does not provide a full role or company beyond the post context.
Google’s AI application builder and workflow environment. Here it is noted for GitHub repository import and bidirectional sync, which matters for AI product workflows and developer experience.
An AI experimenter who shared a long-running Claude Code hardware workflow and open-sourced transcripts/filesystem artifacts.
Autonomous or semi-autonomous workflows that perform tasks, coordinate tools, and execute actions on behalf of users.
Notion is a workspace tool commonly used as a knowledge base for teams. Here it is used as a connected data source for an internal command overview.
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.
Google’s environment for building and testing AI features, mentioned in the context of developer program redemption. It is relevant for AI prototyping and developer onboarding.
AI product company mentioned both as Elena Verna’s employer and as a product she uses in her pricing and packaging work.
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 coding and research tool used here for optimizing order execution latency. Relevant to PMs as part of an AI-assisted quantitative workflow.
An image asset swapping tool or capability referenced in AI Studio editing workflows. Useful for PMs building multimodal UI-editing experiences.
An offline, local, open-source, free, model-agnostic screen-history tool. In this newsletter it is presented as the comparison point for OpenAI’s Computer History.
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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