The best barometer for AI's enterprise value is not replacing the bottom 5% of workers. A better goal is empowering most employees to become 10x more productive. This reframes the AI conversation from a cost-cutting tool to a massive value-creation engine through human-AI partnership.

The most significant productivity gains come from applying AI to every stage of development, including research, planning, product marketing, and status updates. Limiting AI to just code generation misses the larger opportunity to automate the entire engineering process.

The true ROI of AI lies in reallocating the time and resources saved from automation towards accelerating growth and innovation. Instead of simply cutting staff, companies should use the efficiency gains to pursue new initiatives that increase demand for their products or services.

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.

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.

Coastline Academy frames AI's value around productivity gains, not just expense reduction. Their small engineering team increased output by 80% in one year without new hires by using AI as an augmentation tool. This approach focuses on scaling capabilities rather than simply shrinking 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.

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 paradigm shift with AI agents is from "tools to click buttons in" (like CRMs) to autonomous systems that work for you in the background. This is a new form of productivity, akin to delegating tasks to a team member rather than just using a better tool yourself.