Everyone's talking about spec driven development — and almost everyone is thinking about it too narrowly. If your spec only describes what your engineering team needs to build, you're leaving most of its power on the table. In this episode, David Dieruf and Wael Rabadi challenge the AI coding community's definition of "spec" and make the case for holistic specification thinking that drives your entire business.

What You'll Learn:

• Why spec driven development as it's currently practiced is too narrow
• How LLMs fill context gaps the same way humans do — and why that's not hallucination
• Why BRD thinking and agile aren't mutually exclusive
• How a holistic spec drives backlogs, architecture, marketing, and sales from a single source of truth
• The regeneration power of AI when product direction changes from Feature A to Feature B
• Why ubiquitous language across all teams is more critical than ever in the AI era
• How the "multiplier effect" of centralized business context accelerates everything

Key Insight: A spec isn't a technical artifact — it's a business artifact. When your entire organization shares the same context, AI doesn't just help you write code faster. It helps you change direction, regenerate plans, and move the whole business forward in days instead of months.

Is computer science a dying field now that AI can generate code? Are developers just becoming "code monkeys" who paste AI output into repositories? In this episode, David Dieruf and Wael Rabadi tackle these questions head-on and explore what true development actually means when AI handles the implementation grunt work.

What You'll Learn:

• What true development means beyond writing code
• Why context and documentation are critical for effective AI pairing
• How AI exposes the difference between code monkeys and real developers
• The importance of shared understanding and ubiquitous language
• Why interdisciplinary teams and collaboration matter more in the AI age
• How to provide AI with the context it needs to be effective
• The future of software development careers when AI handles implementation

Key Insight: AI doesn't eliminate the need for skilled developers—it raises the bar. The question isn't whether AI will replace developers, but whether you're doing true development or just being a code monkey. If you're the latter, AI is coming for your job. If you're the former, AI is your new superpower.

Hosted by engineering leaders David Dieruf and Wael Rabadi, co-founders of Kisasa.

Most engineering teams treat staging environments as a safety net—a place to test changes before they hit production. But what if that safety net is actually slowing you down and creating more problems than it solves? In this episode, David Dieruf and Wael Rabadi challenge the conventional wisdom around staging environments and make the case for production-first development.

What You'll Learn:

• Why staging environments create false confidence and environment parity problems
• How infrastructure as code (CDKTF) enables production-first development
• Blue-green deployment strategies for safe production deployments
• Why moving the edge to deployment eliminates the need for staging
• How to simplify cloud security audits with infrastructure as code
• Practical approaches to deploying directly to production safely

Key Insight: If your staging environment isn't identical to production, it's not protecting you—it's just slowing you down. Invest in deployment practices that make production safe, not in maintaining a staging environment that lies to you.

Hosted by engineering leaders David Dieruf and Wael Rabadi, co-founders of Kisasa.