Artificial intelligence
fromMedium
1 day agoAdvance Planning for AI Project Evaluation
AI evaluations are essential to determine effectiveness and impact on business and customers.
Tim Cook described John Ternus as 'a brilliant engineer and thinker who has spent the past 25 years building the Apple products our users love so much, obsessed with every detail, focused on every possible way we can make something better, bolder, more beautiful, and more meaningful.'
Well, our guest today argues that the best way is by moving to a more project-driven model of work, up and down the organization from the corporate level to individual teams. He wants us to both ruthlessly prioritize as well as stay fluid so that we're identifying strategic goals, assembling teams to go after them, evaluating as we go, and then either continuing, shifting, or disbanding based on our outcomes.
Most of these companies start the journey from a functional standpoint, avoiding extra layers that may "divert users' attention", such as refined flows, potential edge cases, and, sometimes, proper visual design foundations and user experience. Here, the goal is to ship the product first to validate its value, then address other considerations.
Your AI pilot showed 94% accuracy improvements. The LLM is yielding solid results. You're getting defunded anyway. The reason? You solved a problem AI can solve. Your budget-holder needed you to solve theirs. Companies launch AI pilots that produce results, then stall at scale. The team's diagnosis: "They don't get it." What's really going on: These projects never earned budget-holder buy-in.
"I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue."
To find the typical example, just observe an average stand-up meeting. The ones who talk more get all the attention. In her article, software engineer Priyanka Jain tells the story of two colleagues assigned the same task. One posted updates, asked questions, and collaborated loudly. The other stayed silent and shipped clean code. Both delivered. Yet only one was praised as a "great team player."