The Blast Radius of Black Box AI: Why Amazon’s Outage Proves We Need the 'Glass Box'
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:
