Most of us now talk to our computers like we did in the 60s, through a terminal. The difference is what is on the other side. Along the way, we stopped writing code by hand.
This talk is about what that costs and what it buys. Treating AI systems with awe hides what they can't do and hands us back plausible slop. Named precisely, as a tool that drafts, reviews, searches, or automates a specific chore, it becomes something that can be tested, questioned, measured, and optimised.
Most of us have adopted AI tools without the surrounding guidance on how to coerce models into making something good and useful. The speed of development grew exponentially, to the point where we now interact with computers like we did in the 1960s, through a terminal. This talk is about how to concretely take your everyday prompt and make it better, from slop to a workflow that can be measured and improved far beyond your local environment. We'll cover gold standard practices such as context, guardrails, optimisation, and evaluation frameworks, the things that let you take advantage of AI tooling to the maximum, rather than being tied to reviewing every line it produces, increasing both speed and trustworthiness.
AI, agent optimisation