Software 3.0: Engineering in the AI Age
A path for developers and technical leaders to understand how AI is fundamentally changing the software development lifecycle.
By the end you will
- Transition from manual coding to supervising AI-driven development agents
- Deploy automated evaluation frameworks to maintain code quality in Software 3.0
- Realign engineering career paths with the new values of judgment and system architecture
The digital world stands at a pivotal moment as we witness the emergence of Software 3.0 – a revolutionary paradigm where your words become code and language itself is the new programming interface. Throughout computing history, we've progressed through dist
Why this next: Introduces the paradigm of Software 3.0 where natural language becomes the primary programming interface.
What happens when AI writes your code for you? The software development landscape is undergoing a seismic shift with the emergence of "Vibe Coding", a revolutionary approach where developers describe what they want built and artificial intelligence gene
Why this next: Investigates 'Vibe Coding' and how describing intent allows AI to generate complex codebases.
What if your AI had a never-tired reviewer that caught quiet errors before they reached customers? We dive into LLM-as-judge—the simple but powerful pattern where one model generates and another evaluates—to show how leaders can scale quality without surrendering
Why this next: Discusses 'LLM-as-a-Judge' as a scalable way to evaluate and test the quality of AI-generated code.
The scariest part of AI in software is not that it writes code. It is that it changes what “being an engineer” even means. When generative AI can scaffold applications, spin up infrastructure configs, draft tests, refactor modules, and debug common failures in mi
Why this next: Examines the shift in engineer identity as the cost of writing code drops to near zero.
- 5Ep 84 - The Philosophical Shift: As Intelligence Becomes Cheap, Evaluation Becomes Everything 12 min
AI can generate code, analysis, and recommendations faster than any team in history, but there’s a catch: verification doesn’t scale the same way. When intelligence becomes abundant, judgment becomes scarce, and that scarcity reshapes what “good engineering” and
Why this next: Focuses on the philosophical shift from producing code to exercising sound technical judgment.