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Stop Writing Tests Manually — This AI Does It For You!
Everyone's shipping code with Cursor, v0, and AI tools — but how many of you are actually writing tests? Yeah, that's what I thought. Testing is the biggest gap in AI-assisted development right now. You can vibe-code an entire app in a weekend, but if you're not testing it, you're just shipping bugs faster. KaneAI by LambdaTest is an AI-first testing platform that lets you generate full end-to-end test suites from a PDF document, natural language, or even Jira/Linear tickets — no code required. It spins up multiple AI agents that run your tests in parallel across 3,000+ browser and OS combinations. I'll walk you through the entire workflow — from dropping in a PDF test plan to watching AI agents navigate a live e-commerce site, generate test cases, and export the code for your own test suite. We'll cover: ✅ Why most developers skip testing (and why that's a problem) ✅ Generating test scenarios from a PDF in under 19 seconds ✅ Running 5 concurrent AI agents on parallel test sessions ✅ Watching AI navigate a website with zero selectors or instructions ✅ Exporting test code (Playwright, Cypress, Selenium) — no vendor lock-in ✅ Jira & GitHub integration — tag @KaneAI on a PR to auto-generate tests ✅ Creating test runs with HyperExecute (70% faster than traditional cloud grids) ✅ OTP authentication testing and dynamic data population
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Stop Building Stripe From Scratch — Use This Instead (1 Line of Code)
Raise your hand if you've ever spent DAYS setting up Stripe webhooks just to know if a user is on the free plan or the pro plan 🙋‍♂️ I just dropped a new video showing how I added full subscriptions to a SaaS app with literally ONE component. No webhooks. No Stripe SDK. No database syncing. Clerk Billing is built on top of Stripe (same fees) but handles everything — pricing tables, checkout flows, feature gating, plan switching — all tied to your users automatically. Go watch it and let me know — what's YOUR biggest headache when adding subscriptions? 👇
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🟢 Let's Vibe Code an Indeed Clone the RIGHT Way | AI Beginner Series #1 (Multi Tenant, Cursor, Next)
We’re evolving the series. What started as “🔴 Let’s Build a ___ Clone” has now grown into Let’s Vibe Code the Right Way — a more intentional, AI-first approach to how we build today. Same energy. Same real-world projects. But now with structured workflows, smarter prompting, and modern dev systems guiding every decision. Episode 1 kicks off with an Indeed clone — not just to replicate it, but to show how we design, think, and ship in 2026 and beyond! 🚀 Build a full-stack Indeed Clone (Jobly) from scratch using Next.js 16, Convex, Clerk, and Tailwind CSS v4! This is a multi-tenant, hybrid B2C/B2B SaaS app — job seekers get a consumer-grade experience while employers operate in fully isolated company workspaces powered by Clerk Organizations. Real-time data flows via Convex mean zero polling, instant UI updates, and a reactive architecture that scales. 🎯 What You’ll Learn: ✅ Next.js 16 App Router with Server/Client Components & proxy.ts middleware ✅ Multi-tenant architecture — isolated company workspaces via Clerk Organizations ✅ Hybrid B2C + B2B model in a single codebase (consumer job seekers + business employer dashboards) ✅ Clerk authentication, organizations & billing for subscriptions & feature gating ✅ Convex real-time reactive database — no polling, instant updates across all clients ✅ Role-based access control (Admin, Recruiter, Member) per organization ✅ Plan-based feature gating (Free / Starter / Growth tiers) with Clerk Billing ✅ Clerk webhook sync to Convex via Svix verification ✅ Full-text search powered by Convex search indexes ✅ Convex file storage for resume uploads with signed URLs ✅ shadcn/ui + Tailwind CSS v4 for a modern, responsive UI ✅ Mobile-responsive design with sidebar & bottom nav layouts ✅ Tiptap rich text editor for rich job descriptions ✅ Zod + React Hook Form for type-safe form validation ✅ Full hiring pipeline with real-time notifications at every step ✅ Database seeding script for realistic dev data + SO MUCH MORE!
🚀 Why LLM Orchestration Expertise Matters
In today’s AI-driven world, having access to an LLM isn’t enough. The real value comes from orchestrating LLMs within complex systems—making sure they operate safely, reliably, and in alignment with real-world rules. I’ve had the privilege of working on projects like IOUBI, where the challenge isn’t just generating text, but enforcing economic invariants, reconciling distributed ledgers, and handling edge-case conflicts in real-time systems. This kind of work requires: Turning multi-document specifications into deterministic, operational rules for AI Coordinating AI reasoning across layers (local, L3, L2) in distributed systems Ensuring outputs respect both client intent and real-world feasibility Bridging human expertise and AI to produce actionable, verifiable results Please feel free to let me know anytime if you need help.
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🚀 Why LLM Orchestration Expertise Matters
For the future
I am looking for someone to collaborate with. I do not care where you live. I build AI systems using LLM orchestration, RAG pipeline, multi-modal models, and multi-agent architecture combined full-stack development and automation integration. If you need my help, I will gladly assist for our collaboration. My Discord ID is @ur_sa. Let's further develop our collaboration here.
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For the future
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