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Experienced DevOps & Infrastructure Engineer specializing in secure, scalable ecosystems. This diagram represents the production-grade architectures I have designed and managed across various complex projects, including Cloud-Native, On-Prem, and Hybrid environments.
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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Building smarter backend systems for businesses using GoHighLevel.
Recently worked on setting up workflow automations, pipeline tracking, lead management, and business growth systems designed to help businesses operate more efficiently behind the scenes.
I’m becoming increasingly interested in the intersection between:
• CRM systems
• automations
• customer journeys
• AI workflows
• modern frontend experiences
A lot of businesses focus only on the website frontend, but the real growth often happens through the backend systems powering follow-ups, lead nurturing, and operations.
Currently exploring more advanced workflows involving automations, onboarding systems, customer segmentation, and AI-assisted processes.Just built this for a cleaning business
AI is a great copilot, but it’s a terrible captain.
With AI coding assistants, it’s easy to fall into the trap of letting the LLM drive the entire development workflow. You prompt, copy, paste, and pray.
But our value as software engineers has never been about how fast we type syntax. It’s about system design, critical thinking, and code ownership.
Our role is evolving from builders to technical pilots. If you completely delegate the workflow, you lose control of the project.
Here is a quick framework to keep ownership of your features while leveraging AI:
🛠️ The 4-Step Workflow Guide
Design First, Prompt Second: Define your architecture, data flow, and edge cases before touching an LLM. Use AI to implement, not to invent.
Deconstruct: Break features into micro-steps. Guide the AI through isolated, high-context tasks (schema ➡️ logic ➡️ error handling).
Radical Skepticism: Treat AI code like a PR from an intern who is incredibly fast but occasionally hallucinates. Test and review every single line.
Own the "Why": If a bug hits production, "the AI wrote it" is not an option. You are responsible for the code you ship.
📌 To Developers: The future belongs to those who use AI to accelerate execution, but keep their eyes on system architecture and product sense.
📌 To Tech Recruiters: Stop looking for syntax experts. Look for developers with strong debugging frameworks, system-level thinking, and true project ownership.
For this project, I was completely exhausted, my eyes hurting badly.
But I refused to leave it halfway.
The more I learn, the more I realize businesses don’t actually have an information problem.
They have a retrieval problem.
That’s the problem I stayed up all night thinking about in #n8n. 😪
I’m interested in building systems that actually make things run better with my automation engineering skills.
If you're interested in #AI, #automation, or just want to be part of my journey, hit the follow button and send a DM.
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