Taste, Judgment, and What AI Can't Hire For
How this was made Verified AI
Every Intellegix briefing is generated from that day's broadcast and run through automated checks before it publishes — with a human paged on any flag. Here is the trail for this edition.
An essay titled 'Taste Is All That's Left' generated 336 comments on Hacker News — a signal that it struck a genuine nerve. The core argument: as AI code generation becomes capable of producing working implementations of most standard software problems, the differentiating human skill is no longer the ability to write code. It is the ability to judge what good code looks like — what architecture serves the problem, what approach is elegant versus merely functional. Taste, in this framing, becomes the scarce resource.
Coinbase provided a concrete, institutional response to exactly that thesis. After spending a year rebuilding its engineering interview process, the company published a candid account of what it found: traditional LeetCode-style assessment had become obviously gameable with AI assistance. The replacement shifted evaluation toward system design, architectural reasoning, and the ability to critique and improve AI-generated code — questions that are substantially harder to construct and evaluate, but that probe the judgment the essay argues is now the primary differentiator.
The 'taste' argument is compelling but not unchallenged. Its critics note that it implies a cleaner separation between execution and judgment than actually exists in practice. Taste is developed through execution — through writing code, making poor decisions, and suffering the consequences. If AI handles execution, there is a genuine and unresolved question about whether future engineers will develop the judgment that comes from that particular form of productive suffering.
Two infrastructure startup announcements offered a different lens on the engineering culture question. Herdr, a workflow orchestration runtime joining YC that positions itself as a competitor in the space occupied by tools like Temporal, explicitly committed to keeping its runtime open source even within the accelerator program. The commitment addresses a known concern: Temporal's open-source and commercial versions have diverged in ways that generated community frustration. By making the 'runtime stays open' pledge early, Herdr is treating developer trust as a competitive differentiator — an acknowledgment that in infrastructure markets, perceived alignment with the community is itself a procurement input.
New Orleans is separately testing Carbyne's AI-powered triage for 911 calls, with AI performing initial call assessment before dispatching human operators or determining response priority. The Hacker News comment thread was sharply divided: one camp argued this could meaningfully improve response times in an understaffed dispatch environment; another argued the failure mode for incorrect AI triage of a medical or violent emergency is simply unacceptable. Commenters also flagged that Carbyne was founded in Israel with significant connections to intelligence community alumni, raising questions about data retention and access for a system handling sensitive emergency call information — call locations, nature of emergencies, medical details.