Super Show Notes for Episode 2.03 of Damns Given Podcast
Guest: Amy Carrillo Cotten
Amy Carrillo Cotten is a technologist and Director of Transformation who grew up with a whiteboard in her kitchen and thought it was normal. She works at the intersection of engineering organizations and the humans inside them — specifically on what it takes to move a software org through systemic change. This conversation asks the real questions: What is AI actually doing to the engineering profession? What gets lost when we confuse writing code with solving problems? What does it mean to understand the assignment when the assignment keeps changing?
The Amy Carrillo Cotten TL;DR
What is AI doing to engineering? It is a tool for the tool makers — changing not only what engineers make, but how they make it. The ‘engineers are expendable’ narrative is insulting and largely false. But it is exposing a real identity crisis: engineers who defined their job as writing beautiful code will feel this existentially. Engineers who understood the job was always to solve problems will not.
How did software lose sight of problem solving? Two forks in the road. Technology got complex enough that learning it became the whole job. Then product managers and business analysts were added to translate between engineers and real problems — which quietly removed the engineer’s responsibility to understand the business. Both moves were reasonable. Both had costs.
What should leaders actually do right now? Ask whether you are creating conditions for change or just absorbing conditions for chaos. The pressure to adopt everything fast is itself a chaos vector. Selective, intentional engagement with AI produces transformation. Letting all of it in produces noise.
What does a good vendor look like in this era? They ask what you need instead of just showing you their new AI feature. They reflect meaningful data back about how you are actually using the product. The forward-deployed engineer model — consulting and customer success combined — is the emerging standard. Push your vendors for it.
Actions for Leaders
Separate AI press releases from actual business decisions. Many layoffs attributed to AI were happening anyway. The generative AI era is being used to polish over decisions that have other causes. Look past the sheen.
Rediscover the problem. The engineers thriving right now are using the time AI frees up to go back to first principles: what is the problem, who has it, what does a win look like from their seat? Talk to users more. Build what was previously too ambitious to attempt.
Do not confuse ‘learn AI’ with building a model for transformation For most of the industry, learning AI means learning to coach it, prompt it effectively, build agents, and know when to trust it. Those are real, learnable skills. The rest is distraction.
Reconnect identity with resilience, not competence. Engineers built around ‘I am smart’ are struggling. Engineers built around ‘I can learn’ are thriving. That distinction applies to every profession here, not just engineering.
“Living scared is not going to help anyone... What is my value, and what is valued in the marketplace? Those are two different things.” — Amy Carrillo Cotten
Summary
The engineering profession did not lose its way because of AI. It lost its way over two decades when the technology got complex enough to become the job itself, at the expense of the problems it was supposed to solve. AI is exposing that drift, not creating it.
The leaders who come out of this with something real are the ones who use the disruption as a forcing function back to first principles. Those questions — what problem, who has it, what does a win look like — got buried under a decade of tooling and shiny objects. They are available again now.
The people navigating this era well are not the ones who know the most. They are humble, curious, and learning in community. That combination is what trust is built on. It turns out it is also what survives disruption.
Give a Damn.
Stay brains on, heart open, forward progress.