Code is cheap. Confidence is not. Make correctness easier to prove.
AI can generate implementation faster than teams can build confidence in it. Make intent, constraints, and evidence of correctness clear before code arrives.
Shaping with AI
Categories
21 pages
Shaping with AI
AI tools, workflows, impact, prompt engineering
Using AI to become a team multiplier: a mindset that makes the people around you more effective - part 1
A practical reflection on building a team multiplier mindset with AI: sharing context in code reviews, learning together through pair programming, and writing documentation that helps the whole team move faster.
Leadership
Software solutions do not start with code
I can move from idea to code faster with AI, but the real work still starts before that: asking better questions, spotting constraints, and building the right mental model.
Shaping with AI
Switching from doing to directing
As AI takes over more of the mechanical work, engineers at every level need to learn how to direct, verify, and own what gets shipped. This article reflects on why that mindset should start early, not only at senior level.
Shaping with AI
How I used Cortex Code Desktop to assess the risks in Snowflake's upcoming behavior change bundle
Snowflake rolls out semantic and breaking changes through behavior change bundles. Before a bundle becomes the default, there is a window to test how those changes might affect your workloads. In this article, I show how I used Codex and later Cortex Code Desktop to assess the risks, identify likely breakpoints in our Airflow and dbt pipeline, and map out likely fixes before the bundle lands.
Shaping with AI