3 posts tagged with "ai-fatigue"

There’s a dangerous trend happening in the world of AI developer tools right now. The industry is pushing developers toward a "Black Box" paradigm—an environment where you give an autonomous AI a prompt, cross your fingers, and wait for it to report back.

It acts like a blind servant: you hand off a task, it disappears into the dark, and eventually returns with finished code.

There is just one massive problem with this approach: it generates an incredible amount of waste.

Industry reports and our own testing show that in the initial stages of product creation, developers using black-box AI tools end up throwing away up to 80% of the output. Why? Because software engineering isn't just about typing lines of code; it's about context, architecture, and micro-corrections. When you rely on the "Slot Machine" prompting cycle, you aren't engineering anymore—you're just pulling a lever and hoping the AI hallucinated the same architecture you had in your head.

At Priset, we vehemently reject the Black Box. We are building a Glass Box Pair Programmer.

Yesterday, the news broke that Amazon’s e-commerce group summoned its engineers to a mandatory "powwow" following a series of severe outages. The culprit? According to internal briefings leaked to the FT, it was a trend of incidents characterized by a “high blast radius” and “Gen-AI assisted changes.”

At one point, tens of thousands of users experienced checkout failures and app crashes. As a fix, Amazon is now requiring junior and mid-level engineers to get senior sign-off on any AI-assisted changes.

At Priset, we read this and think, "We told you so." We saw the inevitable collision course of the "Black Box" AI movement.

When the industry pushed for autonomous, "agentic" AI that operates in the shadows—pushing 100s of Pull Requests (PRs) and sometimes even reviewing itself—they built a slot machine instead of a tool. They promised unprecedented speed, but as APIContext CEO Mayur Upadhyaya noted, “failures can propagate faster and in less predictable ways... because the change logic wasn't written by a human in the traditional sense.”

This is exactly why Priset champions the Glass Box approach. AI shouldn't be an autonomous Android running wild in your repos; it should be Power Armor worn by an empowered human architect.

Here is why the Black Box approach fails at the enterprise level, and why Priset’s Glass Box methodology is the only sustainable path forward:

Recently, an enterprise client asked us a very direct question: "If we roll out Priset across our entire AppDev department, realistically, how much faster will we get?"

Our motto at Priset is "The 100x Developer is Here." So, our instinctive response was to tell them to take their current non-AI process velocity and multiply it by 100.

But as engineers, we don't like relying on gut feelings. We operate a "Glass Box," not a black box, and that philosophy extends to how we market our product. To give our enterprise partners an airtight, mathematically sound answer, we sat down and analyzed six of our most recent real-world deliverables—ranging from legacy tech modernization to full mobile app scaffolding.

What we found surprised even us: 100x is actually a highly conservative baseline.

Here is the raw data, the statistical breakdown, and the honest reality of what Enterprise Engineering teams can expect when they equip their engineers with Priset.