AI Myths in Software Engineering. AI is colliding with software engineering at full speed — and a lot of myths are emerging along the way.
In this episode of Serverless Craic, Dave Anderson, Mark McCann, and Michael O’Reilly unpack how AI, GenAI, and agentic systems intersect with the ideas behind The Value Flywheel Effect. Rather than hype or fear, this is a grounded engineering discussion about quality, responsibility and long-term value.
We explore six common myths about AI and software engineering — and why good engineering judgement, domain knowledge, and clarity of purpose matter more than ever.
If you care about building sustainable systems, not just shipping demos, this one’s for you.
Chapters
00:00 – Welcome & context
Why AI + serverless + the Value Flywheel is colliding right now
01:50 – Myth 1: “Software engineering is dead”
Why engineering skills are more valuable, not less
07:06 – Myth 2: “My skills will become irrelevant”
Moving up the value chain, domain expertise, and growth mindset
13:40 – Myth 3: “The quality isn’t good enough”
Standards, constraints, and why worst it’ll ever be is today
18:44 – Myth 4: “The model understands the problem”
Pattern matching vs understanding, context, and critical thinking
24:20 – Myth 5: “I’ll be forced to use AI”
Workflows, guardrails, security, and excessive privileges
31:54 – Myth 6: “We’ll need fewer engineers”
Jevons Paradox, lowered barriers, and the coming demand explosion
34:22 – Closing thoughts
AI, velocity, and the future of sustainable software engineering
Key Themes Discussed
AI as an abstraction layer, not a replacement for engineering
Why standards, constraints, and operability still matter
Domain-Driven Design as AI-amplifying, not obsolete
Agentic systems, skills, prompts, and containment
Security risks: excessive privileges & supply-chain concerns
Velocity vs sustainability in AI-assisted development
Resources & References
The Value Flywheel Effect – principles referenced throughout
Wardley Mapping & situational awareness
Domain-Driven Design (DDD)
OWASP Top 10 for LLMs (excessive privileges, agent risks)
Jevons Paradox (efficiency driving increased demand)
Early cloud cost & governance parallels
Threat modelling for AI and agentic systems
Serverless Craic from The Serverless Edge
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