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Engineered a custom AI workflow from the ground up, fine-tuning Llama 3.2 via LoRA to generate rule-compliant mechanics, and directly deployed the model into a real-time Unity environment. Executed rigorous version control and continuous testing workflows, balancing algorithmic optimization with
pragmatic deployment thresholds to meet production deadlines.
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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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Built a complete multi-page digital experience using Google Stitch.
For this project, I designed and prototyped Eternal Maven, a modern AI and technology agency website focused on communicating technical expertise, credibility, and premium brand positioning.
What I created:
• Homepage with a bold, future-focused visual identity
• AI Development, Web Development, and Solutions pages
• Case Study section featuring project outcomes and impact metrics
• Industry-specific expertise showcase
• Technology Stack page highlighting modern tools and platforms
• Portfolio gallery for featured work
• Blog & Insights hub for thought leadership content
• Contact and conversion-focused lead generation experience
How I used Google Stitch:
I leveraged Stitch to rapidly generate, refine, and prototype high-fidelity screens while maintaining a consistent design system across the entire experience. The platform made it easy to explore ideas, iterate quickly, and build a cohesive multi-page user journey.
Design Direction:
Dark immersive UI, electric blue accents, glassmorphic elements, modern typography, and premium visual storytelling designed for a 2026-ready digital presence.
#GoogleStitch #WebDesign #UIDesign #UXDesign #AI #ProductDesign #Prototype #DigitalExperience #Contra
People keep comparing AI tools like they’re all built for the same thing.
They’re not.
The creatives who figure that out early are going to have a massive advantage.
The conversation around AI is still so focused on aesthetics that people ignore the operational side of creativity.
We need to stop talking only about which tool makes the prettiest image, and start talking more about workflow, scalability, and execution.
I don’t think the advantage will come from using one AI tool for everything.
It’ll come from understanding which tools belong in which part of the process.
And honestly, that shift is waaaay more interesting than the usual “this one is better” debate.
I’m curious: what part of your creative process are you actually trying to improve, and what tools are you using for it?
I'm trying to improve on my ui/ux design and i guess claude can also help better on that.
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.
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