Computing

We are currently engineering our own succession crisis. By handing junior developers AI coding assistants that default to generating architecture and logic at superhuman speeds, we have solved the velocity problem—but we are quietly eroding foundational engineering muscle memory. We are raising a generation of developers who can prompt an app into existence but will be completely paralyzed when the underlying systems collapse. If you look around the industry, the proposed solution is usually a tool: a "Socratic prompt" or a custom GPT designed to ask questions rather than write code. But tools are not enough. In a sprint-driven culture that incentivizes shipping features by Friday, individual discipline will always lose to the temptation of generative autocomplete. When an AI acts as the "Driver" at the keyboard, regular AI pair programming , the human is elevated to the role of "Navigator." This works beautifully for senior engineers who already possess t...

Construx principal consultant Steve Tockey makes a profound observation: “If you are not basing your software technical decisions, at least in part, on engineering economy, then you are not—by definition—doing software engineering.” He points to a quote by Leon Levy:  “ ...software economics has often been misconceived as the means of estimating the cost of programming projects. But economics is primarily a science of choice, and software economics should provide methods and models for analyzing the choices that software projects must make. ”  This got me thinking about the current state of agentic engineering. We are essentially lacking the engineering economy required to make sound investment choices. To highlight this gap, this blog compares traditional cash-flow streams before adding a modern perspective. FinOps —including tokenomics—is a vast field, and this discussion only scratches the surface. Its aim is to highlight a growing trend: companies replacing human softwar...

I have worked in software engineering for more than thirty years and witnessed several combinatorial explosions firsthand. The AI-driven explosion now under way is different, and that distinction should shape our response. In both software and agentic engineering—the extension of software engineering to ecosystems of software and autonomous agents—quality must remain the central concern. If code can now be produced at a staggering pace, what limits our ability to deliver high-quality products quickly? The bottleneck lies in the scaffolding surrounding construction. Writing code faster isn't the danger; the danger is what happens when that code starts talking to itself. The desire to scale agentic engineering is understandable given how deeply software permeates society. At the time of ENIAC , few could have anticipated that software would enable fly-by-wire aircraft, self-driving cars, embedded medical devices, machines that surpass humans at chess and go, or unmanned missions suc...