Career talk 2024 : Balancing AI & Fundamentals in Modern Software Engineering

Are you a software engineer, developer, or tech enthusiast navigating the rapidly evolving world of AI? Wondering how to balance cutting-edge AI tools with timeless engineering fundamentals? This session is for you!

1. Balancing AI & Fundamentals in Modern Software Engineering Career talk 2024

2. AI in a Software Engineer’s Daily Life • Productivity Boost: Autocompletion, code generation, automated testing • Ethical & Privacy Concerns: Data leakage, responsible usage • Verification & Testing: Don’t blindly trust AI outputs—always review and test • Learning Curve: Know basic AI/ML concepts (pipelines, model deployment)

3. Front-End Adaptation • Server-Side Rendering (SSR): Next.js, Remix, Nuxt.js for performance & SEO • Micro-Frontends: Modular approach for large-scale, independent UI components • Standalone Discipline: Dedicated performance metrics, design systems, and DevOps for front-end • Key Trends: Edge computing, design systems, accessibility

4. Backend Evolution (XOps) • Shifting Focus: From microservices to MLOps, LLMOps, DevSecOps, etc. • Automate Everything: CI/CD pipelines with integrated security & compliance checks • Security & Observability: Zero-trust networking, real-time monitoring, distributed tracing • Data & AI: Integrate data pipelines (Kafka, Pulsar) with continuous model deployment

5. Fundamentals Are More Important Than Ever • Long-Term Relevance: Data structures, algorithms, networking, system design • Adaptable Skills: Core concepts apply across languages and frameworks • Deep Problem-Solving: Better architectural decisions, debugging skills • Strategies to Strengthen: Revisit canonical resources, build mini-projects, mentor others

6. Balancing Deep Dives & AI Tools • Opposing Skill Sets: 1. Deep Dive: Mastery of distributed systems, concurrency, architecture 2. AI Tools: Quick prototyping, AI-generated code, “prompt engineering” • Integration Strategies: 1. Scheduled Learning: Separate time for fundamentals & AI experimentation 2. AI for Fundamentals: Use AI to generate examples or “what-if” scenarios 3. Practical Projects: Build end-to-end solutions combining both

7. What was my journey? Started studying about LLM on around January 2024 Getting hands on LLM on around April 2024 Bought GPU around July 2024 Created some small POC from August to October 2024 Built playwithllm v1 on December 2024

8. What is my plan Build a AI driven Ecommerce system on January Create the course by sharing my dev journey in a course Add AI in couple of pet projects (commitstreams, vidigenie) till June

9. Questions? Reach out to me via LinkedIn, Facebook or YouTube comments! Or send email to [email protected]