Block's CTO reveals a counterintuitive lesson: reorganizing from a GM-based structure to a functional one (where all engineers report to one org) was the key to their AI transformation. This structural change had a greater productivity impact than any specific AI tool they implemented.
Block's CTO quantifies the impact of their internal AI agent, Goose. AI-forward engineering teams save 8-10 hours weekly, a figure he considers the absolute baseline. He notes, "this is the worst it will ever be," suggesting exponential gains are coming.
Block's CTO argues that engineers mistakenly equate code quality with product success. He uses the example of early YouTube, which had a famously poor architecture but became wildly successful, while the technically superior Google Video failed. The focus should be on solving a user problem, not on perfect code.
At Block, the most surprising impact of AI hasn't been on engineers, but on non-technical staff. Teams like enterprise risk management now use AI agents to build their own software tools, compressing weeks of work into hours and bypassing the need to wait for internal engineering teams.
The key to driving AI adoption at Block was leadership by example. CEO Jack Dorsey and CTO Danji Prasana use their internal AI tool, Goose, daily. They argue this hands-on approach provides more insight into organizational workflow changes than any top-down mandate or analysis of industry reports.
Block's CTO argues that LLMs are a wasted resource when they sit idle overnight and on weekends. He envisions a future where AI agents work continuously, proactively building features, running multiple experiments in parallel, and anticipating the needs of the human team so that new options are ready for review in the morning.
Contrary to the classic engineering rule to "never rewrite," Block's CTO believes AI will make this the new standard. He is pushing his teams to imagine a world where for every release, they delete the entire app (`rm -rf`) and rebuild it from scratch, with AI respecting all incremental improvements from the previous version.
Block's CTO observes a U-shaped curve in AI adoption among engineers. The most junior engineers embrace it naturally, like digital natives. The most senior engineers are also highly eager, as they recognize the potential to automate tedious tasks they've performed countless times, freeing them up for high-level architectural work.