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I’m excited to share that I’ve successfully completed the “Generative AI: Introduction and Applications” course on Coursera, authorized by IBM! 🎉 This learning experience helped me build a strong foundation in Generative AI—one of the most transformative areas in technology today. 🔍 What I learned: • The difference between generative and discriminative AI • Real-world capabilities and use cases of generative AI • Applications across industries and sectors • An overview of tools and models for generating text, code, images, audio, and video 🛠️ Skills gained: Artificial Intelligence & Machine Learning (AI/ML) | Generative AI | ChatGPT | AI Personalization | Real-Time Data I’m looking forward to applying these skills in practical projects and continuing my journey in AI. 🚀
https://www.coursera.org/account/accomplishments/verify/MPZFM01DJJF5
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IBM | 18,861,151 followers on LinkedIn. At IBM, we do more than work. We create. We create as technologists, developers, and engineers.
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How I Actually Build Websites — From Inspiration to Final Build.
I don’t start with a blank screen. I usually start by exploring Pinterest to find visual references, layouts, interactions, and design ideas. Then I bring the reference into ChatGPT, explain what I want to build, and use it to turn the rough idea into a much clearer development prompt.
From there:
Pinterest → Reference → ChatGPT → Refined Prompt → Antigravity → Manual Refinement → Final Website
I give Antigravity the reference image + refined prompt, let it handle the first implementation, and then take over manually to fix the details that AI doesn't get right — spacing, responsiveness, interactions, typography, animations, and overall polish. AI speeds up the process.
But the final quality still comes from the decisions and corrections I make.
This is how I combine design inspiration, AI-assisted development, and manual frontend work to turn an idea into a real website.
I like the deliberate handoff between reference, refined prompt, and manual refinement—especially the note that the final quality comes from your corrections. That balance is what keeps AI-assisted builds feeling intentional.
I created this short AI film using detailed prompting 😍
An AI engineer should make the path from input to output inspectable. In Tenderseal, I shaped an AI-assisted workflow where users READ source material, ASK focused questions, and DRAFT a response while keeping the underlying material close to the work. I build with approvals around consequential actions, read-back after integrations, and a clear boundary between model output and human judgment. If your AI feature needs a dependable workflow, message me.
Great Design :)