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Why I Stopped Calling Myself a Full-Stack Developer
I spent 20+ years building web apps, dashboards, and SaaS products. I called myself a full-stack developer. But the clients who actually valued me weren't hiring me for React or Node.js — they were hiring me to automate the work their team was doing manually.
That shift changed everything for me.
This year I built RankAsAnswer — a GEO/SaaS platform that helps brands get cited in AI search results (ChatGPT, Perplexity, Claude, Gemini). Not a client project. My own product. And it taught me something the freelance grind never did: the people paying the most aren't looking for code. They're looking for outcomes that save time, reduce manual work, and make them visible in the next generation of search.
Now I focus on 3 things only:
AI workflow automation (n8n, Make, Zapier + APIs)
AI agents that handle real business tasks (OpenAI/Claude)
GEO — making brands findable in AI-generated answers
If you're a founder or team lead and you're still doing things manually that a workflow could handle.
Tags: #AI #Automation #GEO #AIWorkflow #Startup
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Hey Contra 👋 I've been heads-down building Promptly, and I'd love your eyes on it before our launch.
From my time delivering over 20 software projects as a tech lead, I realized the biggest bottleneck in building an app isn't the code itself. It is communication. Founders speak in ideas, and developers speak in strict logic.
Here is how Promptly works. You just describe your app idea in plain English. The AI actually pushes back, asks the hard questions, catches the vague bits, and automatically writes a developer-ready blueprint as you chat.
The goal is simple. When you hand this document to a developer, the next thing you get back is an accurate, fixed-price quote. No more wasting days trying to draft technical specifications and sitting through endless rounds of discovery calls just to get on the same page.
Instead of staring at a blank document, you get three tools that update in real-time:
The Pushback Chat: It refuses to just nod along. If you say "make it fast and secure," it helps you define exactly what that means. It hunts down edge cases before you ever pay someone to fix them.
The Visual Map: A live, interactive diagram showing exactly how your features connect. It catches logic flaws and missing steps before any code is written.
The Living Blueprint: An auto-generated, professional project spec that exports straight to Notion, Linear, or PDF.
Plus, it gives your idea a "Developer-Readiness Score" out of 100 so you know if it is actually ready to build. It even recommends the best tech stack based on your specific budget and complexity.
The core engine and all of these interactive features are fully functional right now, but I am still smoothing out the final rough edges. I am aiming for a public launch in about three weeks.
Where I need your help. I have three quick questions:
Where would you want to export your project blueprint, beyond Notion, Linear, or PDF?
What is the biggest headache you face right now when trying to explain your ideas to developers?
What feels missing? The blind spots are the most valuable to me right now.
Any feedback on new features, improvements, or things I should kill entirely would be hugely appreciated. Drop a comment below.
Thank you for taking a look 🙏
building solo, in public
Product ManagementFull Stack DevelopmentSoftware DevelopmentWeb DevelopmentAI DevelopmentClaudeNext.jsFigma
This is a very interesting concept! Where did you design the UI/UX? I feel like a better choice of font is still out there. Overall good work and clean UI. 🔥
Content management shouldn’t slow down product growth.
I build high-performance web platforms using Next.js + Headless CMS + AI integrations that give businesses speed, flexibility, and smarter content workflows.
Perfect for startups, SaaS platforms, marketplaces, blogs, documentation portals, and enterprise websites.
🚀 What I can help with:
• Next.js (App Router / SSR / SSG / ISR)
• Headless CMS integration (Contentful, Strapi, Sanity, Directus)
• AI-powered content workflows & automation
• OpenAI / Claude / Gemini integrations
• Smart search, recommendations & chatbot experiences
• GraphQL / REST API integrations
• CMS migration & performance optimization
• Scalable full-stack architecture
Imagine this:
✍️ AI-assisted content creation
🔍 AI-powered site search
🤖 Smart chat support
⚡ Lightning-fast SEO-friendly frontend
📈 Content workflows that scale with your business
If you’re building a modern content-driven platform, let’s make it faster, smarter, and future-ready.
Open for new projects on Contra 🚀
#NextJS #HeadlessCMS #Contentful #Strapi #Sanity #Directus #AIIntegration #OpenAI #AIDevelopment #FullStackDeveloper #WebDevelopment #SaaSDevelopment #CMSDevelopment #GraphQL #PerformanceOptimization #ContraCreator
Automated Multi-Agent AI Support & Lead Triage Pipeline
Are your high-ticket clients waiting hours for an email response? This intelligent multi-agent n8n workflow instantly screens, analyzes, and responds to customer emails in real-time, utilizing advanced RAG (Retrieval-Augmented Generation) to deliver human-like support instantly.
Project Overview:
This is an enterprise-grade AI automation system designed to eliminate manual customer support queues. Instead of simple auto-replies, it uses a multi-agent routing structure combined with a dynamic knowledge base to handle complex inquiries autonomously.
How It Works (Under the Hood):
Instant Inbound Triage: A Gmail Trigger catches incoming emails instantly, extracting raw content for processing.
AI Intent Classification: An initial OpenAI model acts as a gatekeeper, analyzing the email to determine if it is a valid customer support request or irrelevant noise.
Conditional Routing: An advanced router splits the path: non-support emails receive a polite automated Telegram update, while actual support tickets are routed to the main AI engine.
Context-Aware AI Agent: The core Customer Support Agent is equipped with an OpenAI Chat Model, conversational memory, and a custom Vector Store Tool.
Pinecone RAG Integration: The agent queries a Pinecone Vector Database (powered by OpenAI Text Embeddings) to fetch real-time, accurate company documentation and context, eliminating hallucinations.
Automated Action & Response: Once the resolution is drafted, the system automatically creates a draft in Gmail for review and sends an instant internal notification via Telegram.
Why This Wins Clients (The Value Pitch):
Zero Hallucinations: Connected to a live vector database (Pinecone) so the AI only speaks from approved company data.
Reduced Overhead: Cuts down customer support response times from hours to under 60 seconds.
Production-Ready Architecture: Designed with modern n8n AI sub-nodes, structured tools, and modular scaling capabilities.
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