What is your workflow for vibe coding a SaaS app using AI tools like Replit, Cursor, and Cloud Code?

#232 · how to actually land retainers in 2026

What is your workflow for vibe coding a SaaS app using AI tools like Replit, Cursor, and Cloud Code?

My vibe‑coding workflow starts with a voice transcription tool where I state three things: my objective (what the app should do), the context (my business, existing tools, clients), and the constraints (what I can or can't use, like needing N8N or avoiding certain platforms). Then I define what 'done' looks—for example, being able to send a request and get a nicely packaged JSON response within 500 ms. After that I just keep working, using the voice tool to feed the AI my goal, and verify my own work until the definition of done is met. Consistency matters: feeding the same structured prompt (objective, context, constraints, definition of done) yields reliable outputs, so I stick to that pattern rather than constantly changing how I prompt.

vibe codingai workflowprompt framework

Related answers

youtube ↗AI & Automation

How to transition to a SaaS model after building automations, including needed components like auth, storage, DB, billing, and scaling to 1k–10k users.

I think it's a good question, but I'm not a software engineer—I'm okay at it but not the most qualified. Still, I'll answer. First, I'd build a serverless backend using Make.com and Nadn (or similar), meaning you don't manage server infrastructure—you just send/receive events to webhook URLs. Once you have that automation, I'd build a front end with Bolt or Lovable (you get a free year of Bolt in Maker School). You'd vibe‑code the front end and connect it to the backend via webhooks. For authentication/storage/database, I'd use Superbase, which works out of the box with vibe‑coded tools like Bolt and Level. Then I'd add payments via Stripe, again trying to vibe‑code it with Lovable/Bolt, though I'd likely need help. Regarding scale, the hard truth is you shouldn't rely solely on vibe‑coded solutions past about 50 customers; they tend to have foundational security issues unless an actual engineer reviews them. I cited the Cluey hack as an example. So, get it off the ground quickly, but then invest in an engineer to secure customer data and prevent leaks—you have that responsibility when running a SaaS.

saasscalingsecurityengineer

youtube ↗AI & Automation

What's your take on vibe coding — its future, and whether it could become a whole new business model? Which would you recommend between Bolt, Lovable, or Cursor? Also, which is the smarter long-term bet: offering automation services, or building actual software that automates things?

I think vibe coding could genuinely be the next big business model — you can build apps, software, or websites that solve niche problems with enough time invested. Between automation services and building software: I'd favor automation services, because building software means putting a lot of upfront capital and time into something in an era where the value of that knowledge is dropping fast — tools like Bolt, Lovable, and Cursor are increasingly capable of replacing exactly the kind of thing you'd have spent all that time building. On the tools themselves: I've used Bolt and like it (they even invited me to a boat party once, so take that with a grain of salt); I've used Lovable too, a cool product I covered in a video; and I've used Cursor for myself but haven't built anything major with it — it feels a bit different in nature from Bolt/Lovable, and it's hard to firmly recommend just one.

vibe codingboltlovablecursorbusiness model

youtube ↗AI & Automation

What automations and use cases do you use Cloud for in your agency?

One of the big things we're using now is a humanization prompt. I created a statistical model of my tone of voice across all my writing on the internet, then use that model to iteratively produce sentence fragments for content. For each fragment I score the perplexity (statistical deviation) from my own writing and select the lowest‑perplexity options, resulting in content that sounds exactly like me. This lets me generate AI content in my own voice, avoiding the typical AI‑generated feel. You can also use AI to generate drafts and then reformat them to match your tone, which works fairly well despite occasional artifacts that appear only about once every few pages. This dramatically cuts down the time I spend on Q&A and content creation. Beyond that, I'm thinking about more advanced loops to improve existing automations. For example, you could run a Claude code loop that scans your N8N or Claude routines and tries to make them 10 % more time‑ or cost‑efficient, logging results to a shared file. Over time the system can auto‑research, generate hypotheses, test them, and if it reaches the 10 % improvement target it stops. Running this continuously can re‑jig automation components, reduce module count, convert them into code blocks, and eventually offload them to serverless providers like Modal or Trigger, cutting costs by up to 90 % and making the automations run orders of magnitude faster.

automationaihumanizationprompt

youtube ↗AI & Automation

How do you build an AI-based SaaS productized service and validate demand?

He said he’d build the frontend with Lovable and the backend with NADN, connecting them via webhook and a respond‑to‑webhook node, noting most of the work can be done in natural language with drag‑and‑drop for the final steps. To validate demand, he’d package the SaaS, create 10 different pitches and 10 audience segments (100 combos), send about 1,000 cold emails a day, testing 10 per combo daily, and after a month look at the 300 emails per group to see which pitches keep, iterate, and repeat the process for another month or two until the highest‑ROI pitch emerges; he added that the same process yields validated wording for inbound ads (meta/Google) if he ever wants to run them.

ai saasproductized servicevalidationlovable