Personal

It’s the first day of 2026, and I’ve been thinking a lot about my journey as a software engineer. I’ve been lucky enough to work with some really strong colleagues; be it Engineers, Senior/ Staff Engineers, even my Engineering Manager — the kind who stay calm in complex situations, simplify chaos, and make technical decisions look effortless.

Every time I work with engineers like that, I feel two things at the same time:

admiration, because their clarity and depth are inspiring, and
hunger, because I want to reach that level one day.

I’m a generalist by nature — I’ve worked with JavaScript, TypeScript, Java, Python, backend, web, AI, cloud… a bit of everything. That helped me survive and adapt for nine years, but in 2026 I want to start sharpening that generalist skill into something more senior, more intentional, and more impactful.

To stay relevant — and honestly, to move up — I need to level up in a few strategic areas.

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🚀 AI — Becoming More Than Just an “API Consumer”

My team is venturing deeper into AI, and I don’t want to be the engineer who just calls /v1/chat/completions.
I want to understand how real AI systems are built.

My AI focus areas for 2026:

Making RAG production-grade (chunking strategies, embeddings, evaluation)
Understanding fine-tuning (LoRA basics, when it makes sense, data prep)
Learning agentic workflows (tools, memory, reasoning steps)
Becoming better at AI observability (prompt logs, latency, cost, failure patterns)

The industry is heading toward AI-heavy systems, and I want to be one of the engineers who understand the inner mechanics, not just the surface.

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🟦 Quarkus — Strengthening My Cloud-Native Java Skills

Quarkus recently became part of my day-to-day work, and it’s something I want to get better at. Not just using it, but being confident designing and delivering backend services with it.

My Quarkus goals for 2026:

Understand Quarkus deeply (DI, RESTEasy, configuration, native builds)
Improve testing using Dev Mode and TestContainers
Deploy Quarkus microservices on AWS
Learn reactive patterns where needed
Build services with proper observability and performance considerations

Quarkus is modern, fast, and cloud-friendly — mastering it lines up perfectly with where my team is heading.

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☁️ AWS — Becoming Comfortable, Not Just Familiar

I’m still fairly new to AWS, but in 2026 I want to reach the point where I can not only build but also architect.

The AWS areas that matter most to a backend + AI engineer:

Core compute: Lambda or ECS (choosing one to master deeply)
Messaging: SQS + SNS
Storage: S3, DynamoDB or RDS
API Gateway and EventBridge
Infrastructure as Code using CDK
Basic understanding of Bedrock and ML integrations

I don’t need to know every AWS service — just the ones required to build reliable and scalable systems.

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🧠 Preparing for a Senior Role — Systems, Design, Leadership

Tech skills make you a strong mid-level engineer.
System thinking, decision-making, and leadership push you toward senior.

My senior-prep goals for 2026:

Deepen system design fundamentals: CQRS, event-driven design, sagas, caching, idempotency
Design with scale in mind: throughput, failure modes, SLAs and SLOs
Own services end-to-end: API → deployment → monitoring
Mentor juniors and help improve team engineering culture
Lead small projects independently

This is the layer I want to grow into more intentionally this year.

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🔮 What Software Engineering Will Look Like in 2026 (and Why I Need to Prepare)

2026 is already showing signs of how fast the engineering world is changing.
More companies are integrating AI directly into their products, and AI tools are starting to take over the “easy” parts of software engineering:

boilerplate code
documentation
writing basic tests
generating CRUD services
initial architecture drafts

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That means the value of a software engineer can no longer just be “I can code.”
AI can code too — very well, and very fast.

The real value now comes from:

understanding systems end-to-end
designing scalable architectures
knowing how to integrate AI responsibly
making good tradeoffs
writing code that works reliably in production
knowing AWS, cloud patterns, and distributed systems
collaborating across teams
leading projects and mentoring others

If I don’t prepare for this shift, the role will only get harder.

But if I grow in the right areas — AI, cloud, system design, backend architecture — I think 2026 can be the year I step closer to the engineer I want to be:

someone confident, impactful, and ready for the next level.

Here’s to a challenging but exciting year ahead.
Happy 2026.