AI Won’t End Engineering. It Will Raise the Bar for Engineering Leadership.

A seemingly naive cohort of people (a fairly large one, however) sees the end of an engineering civilization brought upon us by “the holy AI”.

A simple futuristic outlook shows that AI itself needs data centers, new security and regulatory guidelines, big data warehouses for petabytes of corporate information, connectors and MCPs, integrations with systems of record, chat systems, or document management platforms.

> Add on top all hardware advancements in AR/VR, smart eyewear and watches, the Whoops of the world, IoT.

> Then robotics.

> Then an upcoming layer of smart card innovations and advancements.

> And what about space?

Technology is an irreplaceable pillar of our modern civilization. While mouse clicking and copying forms over by hand, or modifying 12 different XML files for a yet another Java ORM framework, is taken care of by automated “vibe coding” systems, or design processes streamlined through Lovable interactive prototypes, this doesn’t neglect the rising need of engineering leadership in larger organizations, MNCs, mid-market companies, and PE portfolios.

I have been observing engineering flame wars for 25+ years.

– Vanilla software vs. frameworks.
– Frameworks vs. CMS or ERPs.
– Battles between functional, procedural, OOP languages (and other exotic ones).
– Complex engineering layers vs. startup incumbents.
– RDBMS vs. NoSQL databases.
– Monolith cloud vs. segmented systems.
– FOSS vs. corporate.
– Android vs. iOS (or Linux vs. macOS vs. Windows).

But engineering leadership is largely a combination of computer science foundational knowledge and business acumen.

Foundational CS101 translates between platforms, systems, hardware, and OS.

And operational principles on P&L, revenue funnels, opex, ROI/MER, SWOT, company moat translates between organizations – and are empowered by shrewd engineering brilliance.