FT: “Unlike most static software, AI agents with agency will constantly adapt to the real world and will therefore need to be constantly verified. But many believe that, unlike human employees, they will be less easy to control because they do not respond to a pay cheque. Building simple AI agents has now become a trivially easy exercise and is happening at mass scale. But verifying how agents with agency are used remains a wicked challenge.” More: “Innovation transforms the nature of work — our job is to guide that transition by mapping existing skills to new roles…AI is not destiny. We must choose wisely. We must design intentionally. And we must keep humans at the centre of this revolution.”
Economist: “Most modern resource exploration still suffers from very low success rates. Although at least 80% of the world’s valuable resources show no sign of existence above ground, some 85% of operating mines were dug as a result of surface observations. Much of what lies beneath the ground remains a mystery. Kobold wants to return the focus to risk, by using new algorithms and data to reduce uncertainty. This includes quantifying how much geologists do not know—producing somewhat surreal numbers that indicate how likely a rock is to be somewhere. The idea, pioneered by Jef Caers, a geologist at Stanford who also designs economic models, comes from game theory. Faced with two options that hold an equal probability of success, the choice between them is arbitrary. When more information becomes available, it becomes less so. Yet you need to be convinced that the additional information is relevant, and that obtaining it costs less than just taking an arbitrary gamble.”
Matt Slotnick: “Today AI is largely used in an “agent in the loop” manner. That is, workflows are owned by existing software systems and agents are used by people to augment and amplify their ability to do the work prescribed to them. But as we feed these systems increasingly large amounts of data, the logical next step is to move planning and orchestration from people to the system itself. After all, once we’ve determined the reward function– to close a customer, or hire a candidate, the system has far more information with which to plan and act to make that process a reality. If there’s one thing AI is good at, it’s bringing deep context to unfathomably large amounts of data…A business is just a process machine, dynamically allocating resources towards their most efficient use… and agents are a far more efficient and scalable resource to allocate.” More: “In AI apps, a non-deterministic AI model decides the steps using context : relevant information about the lead that the AI is querying from other sources. The better the data, the better the workflow. The context is the most valuable component because it ultimately changes the workflow. Models are relatively similar in performance.”
WSJ: “Creating your own app is now possible with any number of artificial intelligence-based tools, leading to the “vibe coding” revolution for code-writing amateurs. But professional developers are picking it up now, too, bringing the practice—generally understood as the ability to create functioning apps and websites without strictly editing code—into businesses. In the next three years, market research and IT consulting firm Gartner predicts that 40% of new software for businesses will be created with techniques involving AI bots translating plain English prompts into usable code.”
