Diego Pacheco Tech blog

More tokens are not more intelligence. Still, it is easy to get hooked on token usage. Is it learning, experimentation, or just FOMO? Subscription models trained us to extract as much as possible from a fixed monthly payment. But when more usage creates more code to review, why do we need to max everything out? Are we getting more from AI? Or are we repeating an old consumption habit with a new resource? I was reading and watching Gergely Orosz’s conversation with Dex Horthy, “Context engineering with Dex Horthy” , and it made me think about fast loops, slow loops, token harder, and token smarter. Faster loops do not necessarily accelerate value delivery. Unless the lead time decreases and the value increases, we may be trapped in local optimization.

Ambiguity is not simply having a difficult problem. It is not knowing exactly what the problem is, what matters most, or which direction will create value. It appears during requirements, scoping, analysis, and design—across the whole solution space. It also appears across teams: product, design, engineering, and the business. Ambiguity has always been one of the hardest parts of engineering. Agentic AI makes it worse at scale. A human engineer receiving an ambiguous request may push back, ask questions, make assumptions, or stall. An agent immediately produces something: code, commits, documentation, and a confident summary. The output looks like progress. It may have little to do with the outcome anyone wanted.  We always had this problem, but now agents are a huge employer.

Software engineering keeps changing names for the same old problems. Before 2023, changes were introduced with some level os stability; now, changes happen much faster, to the point that we do not really understand the problems. We had those problems in the past, considering things like (agile/scrum, microservices,  devops), but never has it been a fast loop like this. First, we had scripting. Then automation. Then CI/CD. Then DevOps. Then Platform Engineering. Then AI Agents. Now we have Loop Engineering. However, companies have barely functional CI/CD due to a lack of incentives, poor vision, poor management, and other dysfunctions.  Loop engineering, the name is new. The problem is not. The problem is: how do you make a machine do useful engineering work without babysitting every step? That’s it. But "solution" and "waste" manifest in the same way, using the same tools. Loop Engineering is not just about prompting with a fancy jacket. It is not “write a bette...