Archive · 6 Jan 2026
Future Engineers Embrace Breadth Over Brilliance in AI World
Aishwarya Babu, an experienced engineering manager, is changing how engineers work in a world where artificial intelligence is very important.
She believes that engineers should not just be really good at coding, but also be able to understand what customers want and work well with others.
She teaches engineers to use AI tools not just for writing code, but also for designing, testing, and writing about their work.
This helps them do their jobs faster and better.
She also thinks that engineers should be curious, able to handle uncertainty, and think in new ways.
Her goal is to make sure that engineers are not just good at their technical skills, but also good at understanding products and working with AI to make better products for customers.
Aishwarya Babu advocates for engineers to balance technical depth with product understanding and cross-functional teamwork.
She promotes the use of generative AI tools for prototyping, design critiques, and documentation to enhance productivity.
Her leadership includes performance reviews that assess AI fluency, product knowledge, and ambiguity navigation.
Engineers under her mentorship have driven cross-functional projects, improving cooperation and decision-making times.
She envisions future engineers as multidimensional, capable of understanding systems, communicating across domains, and collaborating with AI.
- Who
- Aishwarya Babu, an engineering manager with over a decade of experience.
- What
- A shift in engineering focus towards adaptability, breadth, and AI integration.
- When
- The transition is ongoing as AI redefines consumer-facing products.
- Where
- In contemporary engineering organizations, particularly in B2C marketplaces.
- Why
- To bridge technical depth with product understanding and customer insight, making AI a trusted partner.
- Key Figure
- Aishwarya Babu
- Role
- Engineering Manager
- Career Duration
- Over a decade
- Key Skills Promoted
- Adaptability, breadth, technical rigor, AI fluency, product knowledge, ambiguity navigation
- Impact
- Faster experimentation, quicker feature iteration, improved customer-driven decisions
- Engineering Vision
- Multidimensional development, customer value-grounded collaboration with AI