#technical-debt

#technical-debt

What happened with AWS outage recently is only a brief foreshadow of what might eventually come to pass if this trend continues. Imagine a world where most programmers are primarily LLM prompters with a very shallow understanding of core programming skills or even operational skills pertaining to an app, framework or library. What will we do if a major outage or technical issue occurs then and no person around knows what's really going on?

Take the old example of Ross Perot: Before he was a presidential candidate, he made his fortune producing welfare forms for the federal government. Today, this dynamic has evolved into sophisticated disaster capitalism, where public benefit systems create ideal conditions for private equity extraction that devastate both vulnerable communities and nonprofits.

In any enterprise application, user-provided data is often messy and incomplete. A user might sign up with a "company name," but turning that raw string into a verified domain, enriched with key technical or business contacts, is a common and challenging data engineering problem. For many development teams, this challenge often begins as a seemingly simple request from sales or marketing. It quickly evolves from a one-off task into a recurring source of technical debt.

"The NCA recognizes and understands the problems these legacy IT systems present. A lack of investment in IT infrastructure means the NCA is burdened with technical debt - that is, the increasing cost of replacing outdated systems when fast solutions have been prioritized over long-term solutions," the report said. The watchdog argues that the NCA has also been slow to fully embrace the benefits of cloud-based technology, which has adverse practical consequences.

Coinbase CEO Brian Armstrong was the recipient of some very bad vibes last week after bragging on X that nearly half his exchange's code is already AI-generated, with plans to push it higher. The post unleashed a torrent of ridicule, and seemed to crystalize the skepticism over the reliability of "vibe coding" tools that's been bubbling for months.

Every startup founder dreams of control. Building a sleek payment system in-house feels bold, innovative and even empowering. After all, Stripe began as a small project - why not follow the same path? The idea of owning every detail of the payment experience can be intoxicating. But behind that dream lies a reality few anticipate: endless complexity, hidden expenses and a dangerous distraction from the core product.

Slower systems aren't always a hardware issue. In fact, performance problems often stem from how your systems have evolved - layer by layer, fix by fix. Over time, even the best platforms become tangled in complexity, weighed down by technical debt, and held back by outdated design. Let's break down the key culprits behind why your IT infrastructure feels heavier each year.

Agentic AI programming is what happens when coding assistants stop acting like autocomplete and start collaborating on real work. In this episode, we cut through the hype and incentives to define "agentic," then get hands-on with how tools like Cursor, Claude Code, and LangChain actually behave inside an established codebase. Our guest, Matt Makai, now VP of Developer Relations at DigitalOcean, creator of Full Stack Python and Plushcap, shares hard-won tactics.

Every CEO knows the feeling of promised features taking months longer than expected, simple changes breaking unrelated systems, and top engineers fighting fires more than they build the future. Welcome to technical debt: the detritus of yesterday's innovation that increasingly blocks progress today. The crucial reality is that tech debt isn't an "IT issue"-it's a business strategy problem that directly impacts your bottom line, competitive positioning, and organizational resilience.

The definition of 'tech debt' is being hijacked by analysts and vendors, transforming its meaning from coding shortcuts to the struggles of dealing with legacy systems.

Many respondents noted there is a lack of clear quality metrics provided by the organization, highlighting a recurring theme of misalignment on what defines quality.

The term 'vibe coding' suggests a new approach where speed and creativity overshadow essential coding principles, highlighting concerns over long-term software maintainability.