What 2025 taught me

2025 stretched me in many ways and pushed me far outside my comfort zone. It was messy, imperfect, and intense at times, but when looking back, the dominant feeling is gratitude for everyone who encouraged, challenged, and supported me.

AI and hackathon wins

Felt proud that this hackathon project won an internal award, and now exploring how to get it funded and move it toward production.

Created a full-stack game (UI, graphics, backend, APIs, monitoring, database, and interactive API docs) in just a few days something that would usually take weeks or months. It honestly felt a bit magical when everything worked together.

Received multiple “level-up” recognitions coins from my company for growing myself, my projects, and my team through innovative work.

Certifications and leveling up

Became AWS Certified AI Practitioner this year.

Grateful to my company’s Level Up program for sponsoring the training and exam, and for giving me the nudge to keep raising my own bar.

Continued to deepen skills in AI, full-stack engineering, cloud, and product thinking, with more focus on impact and less on just “cool tech.”

Work highlights and trust

Was trusted by leadership to design and implement the integration between my company’s identity system and the gaming identity platforms of Netflix Games and Amazon Luna, under a tight timeline.

This project was a big growth moment and a reminder of how much can happen when people believe in you.

Very grateful to my directors, VP, and tech leadership for backing me and giving me room to learn and execute on such a big integration.

Content, podcast, and community

Finally launched my long-time dream podcast “Tech and Wisdom” in May 2025, thanks to a push from my mentor and former CTO, who is now CEO at TLEX Mind Matters (https://tlexmindmatters.com/). I very grateful to Raghu for believing in the idea and supporting the first steps.Felt a lot of love from my network for my AI education content, which motivates me to keep sharing what I learn in a simple and honest way.

For 2026, committing to at least two meaningful, educational AI posts every month for this community.

Balancing ambition and health

In trying to juggle many things in 2025, my health definitely took a hit.
In 2026, planning to be much more intentional about physical and mental health, and to use AI as a quiet assistant 🙂

Wishing you and your loved ones a very happy and prosperous New Year 2026 — may you grow in your career, finances, relationships, physical health, and mental well-being. 🌟

#AI #AWS #Hackathon #FullStack #GameDev #CloudComputing #Podcast #CareerGrowth #MentalHealth #NewYear2026

AWS Certified AI Practitioner

Issued by Amazon Web Services – June 2025. Validation Link

This certification reflects my dedication to building real-world AI tools and understanding how to deploy machine learning at scale. I’m currently exploring opportunities to apply these skills across Identity, tooling, and AI-driven automation systems.

Artificial Intelligence Without Machine Learning? It’s Just Artificially Dumb! 🤖💡

Artificial Intelligence (AI) is often associated with Machine Learning (ML)—and for good reason. ML is the beating heart of AI, enabling systems to learn from data, adapt to patterns, and evolve over time.

But what happens when you remove ML from AI? It becomes an artificially dumb system. 😲

Why Machine Learning is Essential for AI

When we talk about intelligence, we mean the ability to learn from experience and improve over time. Just like a human learns from mistakes, ML helps AI refine its decisions based on feedback and real-world interactions.

Without ML, an AI system would:

✅ Remain static—no learning, no evolution.

✅ Lack adaptability—unable to improve based on new information.

✅ Miss out on real intelligence—it would simply be an advanced rule-based system.

If you remove ML from AI, the system would be as “smart” on Day 100 as it was on Day 1—which means no progress, no updates, and no self-improvement.

The Role of Machine Learning in AI Systems

Machine Learning allows AI to:

🔹 Identify patterns and predict future outcomes.

🔹 Improve decision-making based on past data.

🔹 Continuously update itself to remain effective.

This means AI without ML is like a car without an engine—it may look smart, but it won’t go anywhere. 🚗💨

Can AI Exist Without Machine Learning?

Some AI applications, like rule-based systems and expert systems, don’t use ML. But these are limited in capability and cannot learn or evolve. True artificial intelligence requires ML to continuously enhance its performance.

Final Thoughts: AI Needs ML to Stay Smart

On a side note, even humans sometimes fail to learn from their mistakes. 😆 But unlike AI without ML, at least we have the ability to improve.

💡 What do you think?

Can AI be truly intelligent without ML? Or would it just be an artificially dumb system? Let’s discuss in the comments! 👇