Really happy to share that I’m one of the 35 builders across 9 sectors selected as finalists in the Decoding Data Science Building an Agentic AI Application Challenge! I’m really proud to have Figuro included among all these amazing projects. The 8-day challenge is officially done, and I’m really happy to see how far Figuro has come. Really excited for what’s next!

Proud to celebrate another milestone in my continuous learning journey — completing the AI Accelerator Bootcamp: AI Curious to AI Builders Training Course, a 10-hour CPD activity through Decoding Data Science (DDS). In AI, the finish line keeps moving — and that’s exactly what makes the journey exciting. Keep learning. Keep building. Keep challenging what you thought you knew. A huge thank you to @Arshad Ahmad and the entire Decoding Data Science (DDS) community for creating a platform where curiosity turns into knowledge, and knowledge turns into action. Every certificate marks an achievement, but more importantly, it reminds me that the best investment we can make is in becoming a better version of ourselves. #ContinuousLearning #ArtificialIntelligence #AIBuilders #AIAccelerator #DecodingDataScience #DDS #ProfessionalDevelopment #FutureOfAI #LifelongLearning #BuildInPublic

Really happy to share that I’ve been selected as one of the Top 35 finalists in the Decoding Data Science community. What makes this exciting for me isn’t just the selection — it’s knowing that the projects, experiments, and learning I’ve been putting in are actually moving somewhere. DDS has pushed me to go beyond just learning concepts and actually build, test, break, and improve AI applications. Now onto the next stage. 🚀 Grateful for the opportunity, and even more motivated to see what I can build from here. Top 35 → next goal: keep going. 🔥 #DecodingDataScience #DDS #AI #LearningByBuilding #AIEngineering

Building an AI application is much bigger than simply choosing an AI model. The more I learn and build, the more I realize that the real engineering happens around the model. I’ve started asking questions like: → What data is the system receiving? → How should that data be processed? → What should AI handle, and what should traditional code handle? → How do we validate the output? → What happens when the model is wrong? This has changed the way I look at AI projects. Instead of thinking: “Which AI model should I use?” I’m learning to think: “What is the best system I can build around the problem?” That shift in thinking is probably one of the most valuable things I’ve taken away so far from Decoding Data Science. Still learning, building, testing, and occasionally breaking things along the way. 😅 #DecodingDataScience #DDS #AI #ArtificialIntelligence #AIEngineering #LearningInPublic #TechCommunity

Today, I had the opportunity to participate in the AI Everything: Building AI Application Challenge – Online Demo Showcase, hosted by Decoding Data Science (DDS). I presented HireSense AI, an AI-powered application I built as part of the challenge, focused on making the hiring process more structured and actionable for candidates. What made today especially valuable was getting to showcase something I had actually built, alongside other builders working on their own AI applications. It was a great experience to see how different people are turning AI concepts into practical solutions. A big thank you to Decoding Data Science for creating a platform where students and aspiring AI builders can experiment, build, and showcase their work. 🙌 This is another step in my journey of learning by building — and definitely not the last. 🚀 #AIEverything #DecodingDataScience #DDS #AI #ArtificialIntelligence #HireSenseAI #AIBuilders #BuildingWithAI #StudentDeveloper #Tech #Innovation