1. Things besides “more code” need to happen for a good tech product to be built and released (ideation, quality assurance)<p>2. The market’s tunnel vision around generative AI tools (more code! more art!) creates an ecosystem-wide effect whereby emphasis and usage of tools for other things is boxed out. People have certainly built a ton of great AI tools for design, documentation, and dev tools — things that suggest bug fixes/refactors as you write, summarize dense onboarding docs, and create test data that looks like production data, for example — and it doesn’t mean companies will use them<p>3. Focusing on fixing the simple yet time-consuming problem of “more code! where is my more code?!!?” will balloon the responsibilities of these other areas, whose demands can grow exponentially (because complexity can, especially in software products)<p>4. Companies have thus left themselves with a perfect storm: (a) buckets of new code, (b) smaller “leaner” teams after layoffs (so less density of institutional knowledge), and (c) a drought of investment in tools that actually help with the most difficult parts of releasing good software products<p>5. They will find (if they haven’t already) that they quickly need to hire people back, this time with AI-related skills that thanks to AI’s newness basically no one has