WIP. Here's what I'm working on. My original idea was to simulate 3-5 different car HMIs that each represented a diferent era. While gathering references I decided to focus on how speed was represented, what made you feel it. Because I wanted to create a driving simulator webapp where the user could really feel the adrnaline of going fast. With a better idea about the history of HMIs and representation of speed, I wanted to challenge myself a bit more by creating a scenario for a future where only EVs are allowed (so bye-bye cool tachometers!) and where autonomous agentic driving is the new norm. I put myself in the shoes of someone that has nostalgia about the past, the thrill of driving a car yourself and the adrenaline of going fast. Agentic driving (when you choose to take over the autonomous mode) would allow all drivers the ability to go ultra fast, safely, so you can arrive earlier to your target. So I focused on this journey: how to go from autonomous driving mode to manual mode and add a bit of gamification to the driving manually experience. The idea was to design 3 different manual driving modes: Analog Soul (essence of sports 70s and 80s cars), Digital Craze (the frenzy of flashy digital 80s and 90s car clusters) and Smart Drive ( 2030s. How does it look like to drive alongside an AI assistant?). For now, I have the autonomous driving state and the Analog Soul. I'm working on the transition between them. I don't think I'll be able to have the 4 different screens for the end of the challenge, but let's see. I wasted way too much time on the design phase... 🥲 I'll be posting the webapp at the last minute... I'm learning along the way. First time using Rive and, so far, I'm loving it! I don't find it very complicated, the tutorials from their site are great.

Senior Software Engineer & AI Automation

I designed and developed this AI-powered lead automation system as a Senior Software Engineer specializing in AI automation and workflow engineering. The system automatically monitors a lead database and triggers a processing pipeline whenever a new lead appears. It intelligently filters and qualifies leads based on predefined conditions, then uses AI to generate contextual messages and summaries. This automation eliminates manual lead handling, improves response speed, and ensures that only high-quality leads move through the workflow.

After the AI generates the message, the system formats and parses the content before automatically sending notifications to internal teams through communication channels such as Slack and email. The workflow then updates the database with the processed results, keeping all records synchronized. This project demonstrates my ability to build scalable automation systems that integrate databases, AI services, and communication platforms to create efficient, real-time business workflows.