Some weeks don’t just fill up your calendar — they change your direction.
For me, December 18th to 23rd was exactly that kind of week: three different roles, one common thread — helping people really understand how cloud and AI fit together in the real world.
🎯 One week, three hats
In six days, I got to wear three hats:
- Panelist & mentor at an AWS Student Community Day in Hyderabad.
- Speaker at AWS Community Day Kochi (AI/ML Edition).
- Newly certified AWS Generative AI Developer – Professional.
Individually, each one is special.
Together, they felt like a mini “sprint” in my AWS journey — community, practice, and validation all reinforcing each other.
🎓 Dec 18 – Panelist & mentor at AWS Student Community Day (MLRIT, Hyderabad)
The week kicked off at MLRIT in Hyderabad with AWS Student Community Day, where I joined as a panelist and mentor.
Walking into a hall full of students always reminds me of my own early days — lots of curiosity, a bit of anxiety, and a ton of questions that don’t always get asked out loud.
Real talk on careers, not buzzwords
On the panel, we kept the conversation honest and practical:
- What does a realistic cloud + AI career path look like for students today?
- How do you move from “I passed a cert” to “I can actually solve problems”?
- What do hiring teams expect from freshers beyond a list of technologies?
Instead of throwing jargon, we shared stories — projects that broke, lessons from production, and how community involvement can shortcut years of trial-and-error.
Hands-on: building instead of just listening
After the panel, I switched into mentor mode for a hands-on lab.
The goal was simple: ship something end-to-end, not just click around a console.
We worked through:
- Evolution of Coding and Kiro Features
- Vibe coding with Kiro.dev to quickly get from idea to working UI.
- Deploying with AWS App Runner so students could see their app live, not just on localhost.
- Thinking about scalability, availability, and security as part of the design, not as an afterthought.
By the end, the best feedback wasn’t “nice session” — it was “this finally makes sense now.”
That shift from “cloud feels abstract” to “oh, I can actually build this” is exactly why these workshops matter.
🎤 Dec 20 – Speaker at AWS Community Day Kochi (AI/ML Edition)
Two days later, the vibe changed completely: from campus energy to community conference energy at AWS Community Day Kochi.
This time I was on stage, talking about something that’s very close to what I work on day to day: Agentic AI and how enterprises are starting to adopt it.
From prompts to Agentic AI
The session was built around three ideas:
-
Where Amazon QuickSuite and AWS Transformfit in
- Amazon QuickSuite as a day-to-day AI companion for research, chat, automation, and flows — almost like a teammate that understands your systems.
- AWS Transform as the heavy-duty engine for modernization: from VMware and mainframes to .NET migration, powered by Agentic AI.
Real patterns, not just slides
We walked through patterns like automating content workflows, migration of boto2 SDK to Boto3 SDK using Transform instead of “cool demo only.”
What stood out to me was the Q&A afterwards — people weren’t asking “What is Agentic AI?” anymore; they were asking “How do I plug this into my environment?”
That’s when you know the conversation has moved from hype to actual adoption.
📘 Dec 23 – AWS Certified Generative AI Developer – Professional
The week wrapped up on a personal high: earning the Beta AWS Certified Generative AI Developer – Professional certification.
This exam goes well beyond “call an API and get a response.”
It tests whether you can design secure, scalable GenAI systems that live comfortably inside real-world AWS architectures.
Some of the deeper areas it touches:
- Amazon Bedrock architecture and security — not just “what is it,” but how should you use it.
- Designing agent-based, multi-step workflows that coordinate tools, APIs, and services.
- Using Lambda, API Gateway, and Step Functions to glue GenAI components into full pipelines.
While answering questions, there were multiple moments of “wait, I literally spoke about this on stage two days ago.” and "heard about from fellow speaker "
That overlap between community work and exam content made the certification feel less like a separate goal and more like a checkpoint on the same path.
🔁 What this week taught me
Looking back, going from panelist & mentor → speaker → certified professional in a single week was intense, but it reinforced a few beliefs that guide how I want to continue showing up in the AWS community.
Teaching sharpens understanding
Every time you explain something, you find edge cases and blind spots you hadn’t noticed before. Students and community members ask the questions documentation doesn’t.Community is a multiplier
Panels, meetups, and community days compress learning. You don’t just learn from talks — you learn from hallway conversations, random questions, and even “we tried this and it failed” stories.Certifications hit different with real context
When you’ve built, broken, and fixed real systems, an exam doesn’t feel like memorization. It feels like someone asking, “Okay, show me how you’d do this in the real world.”
Most of all, this week reminded me that giving back and growing personally are not separate tracks.
The more you mentor, speak, and share, the deeper your own understanding becomes.
🙏 Thank you — and what’s next
None of this happened in isolation.
Huge thanks to:
- AWS Student Community & AWS Cloud Clubs at MLRIT for creating a space where students can experiment, break things, and learn by doing.
- The AWS Community Day Kochi organizers and volunteers for building a stage where practitioners can talk about what’s actually happening with AI/ML on AWS.
- SUDO Consultants for backing community work and giving me the room to build, experiment, and share.
- Every student and attendee who showed up, asked tough questions, and shared honest feedback — you made the week memorable.
From here, the plan is simple: keep building, keep teaching, and keep pushing deeper into Agentic AI and cloud automation.
If you’re on a similar path — maybe just getting started with AWS, or trying to move from “I know the services” to “I can design systems” — consider this an open invite: join a community, share what you learn, and let your journey be shaped by contribution as much as personal milestones.
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