Who manages the agents?

Two AI futures

There are two visions for the future:

• AI as a deity built and controlled by a small group of clergy
• Humans at the center with AI as an amplifier

A new technical clergy is emerging: the small group that builds frontier systems, receives privileged access to them, and decides which capabilities everyone else may use.

The clergy warn about mass unemploymentDario Amodei warned that AI could eliminate half of entry-level white-collar jobs within five years (May 2025). Sam Altman said AI means customer support jobs are “totally, totally gone” (July 2025). Mustafa Suleyman predicted most computer-based professional work will be fully automated within 18 months (May 2026). Elon Musk proposed “universal high income” as the remedy (April 2026).. They don’t think it will necessarily lead to a bad outcome. Freeing people from grunt work can liberate time for pursuing leisure activities.

The average person hears mass unemployment as catastrophic. How do they make rent or buy food for their kids? We are assured that abundance, redistribution, and new forms of meaning will compensateSam Altman’s “Moore’s Law for Everything” (2021) promises to “directly distribute ownership and wealth to citizens”; his “The Gentle Singularity” (2025) foresees intelligence becoming “wildly abundant”; Dario Amodei’s “Machines of Loving Grace” (2024) addresses work and meaning after displacement.—by the grace of the machines and their controllers.

A tiny group mediates between machine intelligence and everyone else. Humanity does not broadly participate in directing that intelligence or deciding how it should be used. Most people become recipients of decisions, products, and abundance. Not participants.

Initially the clergy may administer the machine. But as its capabilities surpass their own, it becomes less clear who is directing whom. In this vision, they build a deity, and increasingly their role is to tend it, interpret it, and decide who may approach it.

There’s another path: not one central intelligence ruling over billions of passive users, but billions of humans learning to direct capable agents of their own.

The future is unevenly distributed

The clergy focus feverishly on sharpening the tip of the spear so it can pierce ever harder domains: solving century-old mathematical problemsIn January 2026, Erdős Problem #728 became the first Erdős problem fully resolved autonomously by AI (GPT-5.2 Pro plus Harmonic's Aristotle, formalized in Lean). In May 2026, an OpenAI model resolved an Erdős problem that had been open for 80 years. and finding software vulnerabilities undiscovered for 30 yearsAnthropic's Frontier Red Team reported that Claude Opus 4.6 found 500+ high-severity vulnerabilities in heavily fuzzed production open-source code, some undetected for decades. Claude Mythos Preview then found thousands of zero-days across every major OS and browser, including a 27-year-old OpenBSD bug.. They will undoubtedly cure diseasesDemis Hassabis on 60 Minutes (April 2025): the end of disease is “within reach… maybe within the next decade or so”. His Isomorphic Labs raised $2.1 billion in May 2026 toward “solving all disease”. and generate immense value and wealth. But who will have access to the cure for cancer? And the cure for aging? Drug discovery capabilities are restricted because of bioweapons risksAnthropic activated ASL-3 protections with Claude Opus 4, deploying classifiers that constrain biology-adjacent capabilities to limit CBRN weapons risk. The pattern deepened with the Claude 5 generation: Fable 5 ships with safety classifiers on dual-use capabilities, while the unrestricted Mythos 5 is available only to approved organizations.. Software capabilities because of cyber risk. It’s not hard to see what comes next: math capabilities limited because of cryptographic risks, creative capabilities because of disinformation riskOpenAI restricted Sora to opt-in consent for likenesses after deepfake complaints from SAG-AFTRA and celebrity estates (October 2025); NewsGuard found Sora produced videos advancing 16 of 20 false claims tested; the EU AI Act’s Article 50 deepfake-disclosure mandate takes effect August 2026..

Governments required many of these restrictions, and frontier labs often supported themAhead of GPT-5.6’s launch, OpenAI proactively previewed the models’ capabilities with the US government; the models were OpenAI’s first rated “High” risk in both biology and cybersecurity, and the rollout began with roughly 20 government-approved partners (Forbes)..

At the same time, selected partners, researchers, and institutions retained access to capabilitiesAnthropic's Project Glasswing initially limited Mythos Preview to a small group of critical industry partners and open source developers. After Fable 5 reached general availability, a US export-control order forced Anthropic to disable Fable 5 and Mythos 5 worldwide; when the ban lifted, Mythos 5 returned only for government-approved organizations. OpenAI's GPT-5.6 followed the same shape: a government-requested limited preview for roughly 20 partners before general availability on July 9.. The result is the beginning of a two-tiered system: frontier AI for a small group, constrained AI for everyone else.

There are real dangers in making powerful capabilities universally available. Biosecurity is real. Cybersecurity is real. Disinformation is real. But genuine safety concerns shouldn’t lead to exclusion and permanent dependency.

The frontier is racing ahead. The median is standing still.

The vast majority of humans don’t know how to use the ever-sharpened spear.

Software development gives us a peek into the future, because software developers got AI agents a year before everyone elseCursor shipped its first agent mode in November 2024 and Anthropic released Claude Code in February 2025; general knowledge workers got the equivalent only when Claude Cowork, “Claude Code for the rest of your work,” launched in January 2026.. Initially the developers who were the most effective at working with agents, the super users, were maybe twice as productive. Over the past year and a half that’s steadily increased to a 5x increase, then 10x.

The best agentic developers are now probably exceeding 100x, doing massive rewrites of codebases that would have taken years of engineering in daysBun, 535,496 lines of Zig, was rewritten in Rust in 11 days by one engineer supervising up to 64 concurrent Claude Code instances, with the 6,755-commit pull request passing the full test suite on all platforms. Jarred Sumner’s estimate for doing it by hand: 3 engineers for about a year, roughly 750 engineer-days compressed into 11..

I created NanoClaw over a weekend of intensive codingFirst commit: Saturday, January 31, 2026. Launched on Hacker News the next day.. Although the project has few lines of code, it covers many technologies I had minimal or no prior experience with (Baileys, SQLite, Apple containers, IPC). Starting with the knowledge I had that Friday night, building it pre-AI would have taken me six to eight months. More realistically, I would never have completed it.

But those developers are a tiny fraction. My sense is far less than one percent have reached 100x. The median developer hasn’t gained any meaningful increase at allMETR’s randomized trial found experienced developers were 19% slower with AI tools in early 2025; its February 2026 follow-up found only “very weak evidence” of modest speedups.. They’re still within a rounding error of 1x. Every week there’s a new release of a model or a feature. 4.6, 4.8, 5.5, fable, Sol. Hooks, Skills, loops, workflows. With each release the super user unlocks a new level, while the median just gets more confused and the gap keeps growing.

The same thing that’s played out for developers with coding agents has started to play out across the workforce. We’re already hearing about 10x salespeople, 100x marketersAnthropic’s own case study describes a sing