KEEP ME IN THE LOOP (Intro) October seventh, twenty twenty-six. A room opens across the time zones. CognivaLab. A collection of curious people, some building agents, some learning the tools, some wondering what all this acceleration is doing to the people using them. And one question to bring them together: How do we create coherence in the middle of all this change? (Verse 1) The tools are arriving faster than the training, another application, another command. Somebody says, “You’ve got to use AI,” but nobody says where to draw the line. In customer support, the details matter, who needs help, and what they’re trying to do. A bot can read the whole knowledge base and still miss what matters to you. An engineer is building interchangeable agents, another’s got an operating system of his own. We’re learning to automate the labor, but what happens to the things we used to know? (Pre-Chorus) Show me your M-D-S, minimum demonstrable standards. Who checked the work? What did it change? And who gets to make the judgment? (Chorus) Keep me in the loop, I need enough of the story to choose. Let the tools extend our reach, without losing what we knew. Keep me in the loop, measure what matters, not what grew. And if the right decision is not to use AI, we need to know that too. (Verse 2) One voice had gone all in on automation, three months down the rabbit hole. Until a decision needed making, and he’d lost the context he needed to know. Another heard the background buzzing, three or four prompts and then a break. Even when the tasks are finished, there’s a mental bill left to pay. Another worked where AI was mandatory, plenty of tools, a generous account. But nobody had provided the ethics, or asked what the work was really about. And someone said the young ones are producing more and more, but checking less. We need a human in the loop for quality, or we’re just accelerating the mess. (Chorus) Keep me in the loop, I need enough of the story to choose. Let the tools extend our reach, without losing what we knew. Keep me in the loop, measure what matters, not what grew. And if the right decision is not to use AI, we need to know that too. (Bridge) There’s a difference between capability and appropriateness. Between making something faster and making something worth making. If the machine can do the work but leaves us unable to judge the result, what have we really gained? Where does the human stop? Where does the machine begin? And what belongs in the space between? (Verse 3) So the room began to write its mission, collaborative tinkering, ethics and care. Human judgment at the center, shared experiments, the knowledge we can share. GitHub for the things we’re building, WhatsApp for the questions flying by. LinkedIn for a Friday nugget, one new lesson before we say goodbye. Monthly workshops, hands-on learning, show us how the things you made actually work. Certification by July twenty-seven, but the learning matters more than the paperwork. (Outro Chorus) Keep us in the loop, give us the knowledge to choose. Let the technology extend us without losing the human point of view. Keep us in the loop, we can make, and question, and improve. There’s a room where we decide together what’s worth making, and what we ought to do. (Outro) So, what did you learn this week? What did you make? What didn’t work? And what would you choose not to automate?
