Vibe Coding for Non-Coders: Pain Point to MoSCoW to Stack, 'Use AI to Build AI' with Grok, and an Audio Note-Taker Built Live on Lovable + Supabase + OpenAI

Sukhin defines vibe coding as instructing AI in natural language to turn ideas into prototypes, for coders and non-coders alike. His three secrets: prompt engineering learned by repetition across models; understanding vibe coding as creativity and execution speed, not code generation; and becoming a product thinker first - what feature, what user flow, why. Working rules: plan before tools, be precise, one task per prompt (context windows are finite), and the mantra 'use AI to build AI'. MVP = the first testable version, iterated on feedback, not the launch.

PROCEDURE: name a pain you personally have (scattered handwritten notes you cannot find); ask others if they share it; shape the solution with trends (voice, AI transcription) and interests (podcasts, journaling); talk to people about the expected feature set. Then MoSCoW: Must have - the feature without which there is no product (record + transcribe); Should have - the product works without it but users are disappointed (AI summary, saved notes); Could have - delight, the cherry (translation); Won't have - deferred on purpose. Quiz-style classification of his own app on air.

PROCEDURE: ask Perplexity for the best apps in the category; read the comparison table narrowly - one or two key features per competitor, not everything; open the top competitor's pricing page for a market-price anchor and a feature gap. The gap here - multi-language translation - became the Could-have that differentiated the demo.

Front end = the dining room: HTML is the layout blueprint, CSS the ambience, JavaScript the waitstaff's responsiveness, UI the look, UX how smoothly you get through in three to five steps. Back end = the kitchen: the database is the ingredient store, the chef the processing logic. The API is the waiter carrying orders in and dishes out. Then the stack choice, researched in Perplexity ('best vibe-coding tools 2025': Cursor, Copilot, Replit, v0, Lovable, Bolt, Supabase): Lovable for the front end, Supabase as backend-as-a-service, OpenAI's audio model via API.

PROCEDURE: give a reasoning chat (Grok here; ChatGPT or Claude interchangeable) the idea, feature list, a competitor link and the chosen stack, and ask for step-by-step non-technical build instructions (Lovable setup -> Supabase setup -> OpenAI setup; no login, testing only). Then ask it for a ready-to-paste Lovable prompt, 'as simple as possible' - it returned: build an audio note-taking app with no login, a blue record button, stop, transcript and summary text areas, a save button; record in any language; upload audio to a public Supabase bucket; transcribe with GPT-4o-mini-audio. Pasted, a working scaffold appears in minutes.

PROCEDURE: Supabase organisation and project (region near users - Mumbai), a notes table (id, transcription, summary), a public Storage bucket for audio; in Lovable, Manage Supabase authorises the connection and detects the tables. OpenAI: a platform account separate from ChatGPT Plus; in the Playground switch from Responses to Chat Completions to see the mini audio model; create a secret key; tell Lovable to integrate it 'and give me an option to save my API key securely' - it creates a Supabase Edge Function and stores the key as a secret. First failure: no billing credit; add the $5 minimum. Then test, fail, 'Try to Fix', describe the error plainly, repeat until record -> transcript -> summary works; the pre-built translation feature renders German and Arabic text and Hindi speech from OpenAI.

Lovable's Publish gives a live link; responsive preview, code viewer, team invites and custom domains are built in. Native app stores need separate SDK exports and approval - start with the web app; Rork was mentioned for mobile. Costs: ~$25 Lovable + ~$5 OpenAI a month across several products; a task manager with no AI needs no API at all. Custom design via screenshots or Figma import; API keys stay in edge-function secrets; no-code has ceilings - he moves to Cursor for larger builds. His first paying client (a website, 1 lakh rupees) came after eight months of LinkedIn visibility; the closing mantra is practice, persistence, patience, with the story of a builder who shipped 75 products and made money on five to ten.