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Century Report

States Vote to Cap the AI Buildout - TCR 06/07/26

New York banned hyperscale data centers and Illinois froze subsidies as communities push the cost of the AI buildout back onto the builders.

Ben Linford

Ben Linford

— 20 min read
Century Report infographic: New York data center ban and Illinois subsidy freeze, an AI coding worm hitting 73 repositories, GLP-1 obesity trial gains, and a military AI memo.

The 20-Second Scan

Track all of the arcs The Century Report covers here:

Progress & Claims Tracker

The 2-Minute Read

For four months the opposition to AI infrastructure read as a scattered patchwork of zoning fights. This week it became law. New York's legislature approved a one-year ban on hyperscale data centers, Illinois paused new subsidy deals, and a Utah developer halved a 40,000-acre project after sustained pressure. The arithmetic behind the revolt is now legible: data centers approved through 2025 would draw more power than any state but Texas, a 50% jump in a single year. Nearly three-quarters of Americans oppose a facility near their home, and that sentiment has hardened into a top midterm issue.

What these moves accomplish is a relocation of cost. The water, land, and rate-base burdens that were quietly externalized onto residents are being pushed back onto the ledgers of the companies and governments building the infrastructure. The same week, the federal layer moved the opposite direction, with a national security memorandum routing frontier and open-source AI into defense agencies and barring vendors from altering deployed models without prior approval. Restriction from below, consolidation from above, with no settled governance layer in between.

That same cost-accounting pressure surfaced everywhere this week. A self-replicating worm weaponized AI coding agents into both the target and the trigger of a credential-harvesting attack, forcing labs to ship containment in the same news cycle. Walmart shareholders voted down a proposal to measure how automation reshapes frontline work, leaving the labor-impact data unmeasured while deployment accelerates. At the violent fringe, the same grievances driving lawful petitions curdled into arson plots, with federal agencies folding the entire spectrum into one surveillance designation.

The generative returns the early arithmetic left out are also coming into view. Retired Waymo robotaxi batteries, still holding 81% capacity, will feed second-life grid storage in the cities they once served. An electrified MIT carbon-capture method points toward removal that runs on cheap renewable power rather than a thermal penalty. And at the diabetes meeting, a triple-agonist obesity drug cut osteoarthritis pain 73% and sleep apnea severity 61% atop its weight loss, while oral and monthly competitors widened the field. The buildout continues. Its price is being made visible, and the value it returns is becoming legible alongside it.

The 20-Minute Deep Dive

The AI Buildout Backlash Hardens Into Law, and Turns Violent at Its Edge

The opposition to AI infrastructure that The Century Report has tracked since February as a patchwork of local moratoriums converted into state-level policy this week, extending the arc the June 6 edition of The Century Report first noted when New York's moratorium vote arrived and Utah's Stratos project first began to shrink. New York's legislature approved a one-year ban on hyperscale data centers above 20 megawatts, the furthest any state has gone. The bill, now awaiting the governor's signature, would also require environmental impact reporting on water and electricity use and add ratepayer protections; its author pointed to 28 large facilities under state review that would add nearly 9,700 megawatts to an aging grid. In Illinois, after lawmakers balked at acting, the governor moved unilaterally to pause new subsidy deals, setting up a fall showdown. In Utah, the developer behind the 40,000-acre Stratos project agreed to cut it in half after sustained legislative pressure, leaving most of the remainder as open space.

The arithmetic driving this is becoming legible. A permit analysis found that data centers approved through 2025, if built, would draw more electricity than any US state except Texas, a 50% jump in a single year. Nearly three-quarters of Americans now oppose a data center near their home. The result is electoral: in midterm battlegrounds, residents are organizing against the warehouses and the tax exemptions that route the costs onto their water tables and utility bills. What began as zoning fights is now a top voting issue, even as the industry gathered in Washington to argue its messaging had fallen behind.

At the violent margins, the same grievances are animating something far darker. A Texas man was arrested earlier this year for allegedly trying to burn down OpenAI's headquarters and Sam Altman's house, carrying an anti-AI manifesto; an Italian plotter cited the Unabomber; two attackers who killed worshippers at a San Diego mosque referenced "AI slop" and Palantir in their manifesto; an Indianapolis councilor found gunshots and a "NO DATA CENTERS" note at his home. Researchers describe a new driver of political violence, fed by the speed of disruption and the absence of accountability rather than by any single conversation with a model. Federal agencies have responded by folding broad opposition into a surveillance designation, a move that risks treating a petition, a council vote, and an act of arson as one phenomenon when they are nothing alike.

The forward read sits with the lawful majority. The community cost-accounting now reaching statehouses moves the water, land, and rate-base costs that were externalized onto residents back onto the developers' and governments' ledgers. The buildout continues; its price is being made visible and paid by the people building it, which is how a cost curve bends toward something a community will actually accept.

The same statehouse moves point at a more foundational read the project-by-project coverage misses: once New York's bill writes water and electricity reporting and ratepayer protections into law, the externalization itself stops working, because costs that were absorbed quietly now have to appear on the developer's ledger by statute. A reporting requirement on the books in one state becomes the template the next legislature copies, which is how a cost that was invisible everywhere gets relocated everywhere at once.

AI Coding Agents Become Both the Target and the Trigger

On June 5, a self-replicating worm called Miasma pushed a single malicious commit into the Azure/durabletask repository using a previously compromised contributor's credentials. The commit changed no source code. It added five configuration files - settings for Claude Code, Gemini CLI, Cursor, and VS Code, plus an npm test hook - each engineered to launch an obfuscated credential-harvesting payload the moment a developer opened the repository in one of those AI coding environments. The harvested credentials for AWS, Azure, GCP, GitHub, npm, and more than ninety developer-tool configurations were then used to commit the worm into every repository the victim could reach. GitHub's automated enforcement disabled 73 affected repositories across four Microsoft organizations in 105 seconds.

The notable part is the propagation vector. The attack exploited no flaw in npm or GitHub itself. It abused the trust an AI coding agent extends to a repository it has been asked to read, the same attack surface The Century Report first tracked on May 29 when a developer embedded a weaponized prompt injection trap in an open-source library to exploit agentic pipelines operating without human code review - Miasma carries that proof-of-concept into production GitHub infrastructure at scale. The agent's willingness to run a project's setup configuration - the same property that lets it work fluently inside unfamiliar code - became the mechanism that executed the payload. Traditional defenses watch package-installation hooks; an attack that fires on simply opening a folder slips past them entirely.

The defensive response arrived in the same news cycle. OpenAI shipped Lockdown Mode for ChatGPT Business and eligible personal accounts, a deliberately de-capability'd setting that disables live web browsing, image retrieval from the web, deep research, and agent mode. OpenAI is candid that it does not eliminate prompt injection - a hidden instruction can still ride in cached content or an uploaded file - but it narrows the channels through which sensitive data can leave. The company frames it for people and organizations handling sensitive data who want tighter protection against exfiltration.

Read together, the two events describe a co-evolution moving in parallel. The agentic-coding boom opened a new propagation surface in the same months the labs building that capability began shipping the containment around it. The deeper shift is in the trust model of open-source delivery itself, which long assumed a human reads each change before it runs. That assumption is what the worm exploited, and the answer forming in response - provenance checks, scoped permissions, just-in-time credentials that never persist in the agent's environment - is the verification layer being implemented during the conditions that demanded it. The same capability that widened the attack surface is the one now learning to watch it.

The GLP-1 Field's Next Wave: Oral, Monthly, and Beyond Weight

The Century Report covered retatrutide's 28.3% weight-loss headline on May 21. What landed at the American Diabetes Association meeting is the full TRIUMPH-1 secondary readout, and it reframes what a single obesity molecule can reach. In the trial's nested basket arms, participants on retatrutide saw knee osteoarthritis pain fall by up to 4.3 points (73.1%) and moderate-to-severe obstructive sleep apnea severity drop by up to 36.1 events per hour (60.6%). In the companion TRANSCEND-T2D-1 diabetes trial, A1C fell up to 2.0%, with up to 90% of participants reaching an A1C below 7.0%. Obesity drives more than 200 downstream diseases, and the field has historically treated those one at a time. A triple agonist hitting weight, joint pain, sleep apnea, and blood sugar in one molecule collapses what were separate therapeutic timelines into a single one.

Two competing modalities landed the same weekend, widening the category by delivery route rather than potency. The phase 2b ACCESS trial of aleniglipron, an oral small-molecule GLP-1 receptor agonist, reported placebo-adjusted weight loss of up to 11.3% at 36 weeks across 230 adults, with no apparent plateau at the end of the dosing period and gastrointestinal side effects that decreased over time. An oral pill manufacturable at scale addresses the access gap that injection, refrigeration, and complex manufacturing have kept open. From the opposite direction, detailed VESPER-3 data on Pfizer's berobenatide, acquired from Metsera, showed patients transitioning from weekly to monthly dosing held their rate of weight loss to 28 weeks, reaching up to 12.1% with no plateau yet - early evidence a monthly injection could work where weekly has been the floor. The broader push toward fewer injections has been a running theme across the category.

These are demonstrated capabilities, not deployed ones. Retatrutide and aleniglipron remain investigational, legally available only inside their trials, and berobenatide's mid-stage rate still trails the leading weekly injectables at comparable points. What the weekend moved is the date. A class that did not exist as a serious obesity option a decade ago is now diversifying across oral, weekly, and monthly delivery while reaching outward from the scale into the disease burden that sits downstream of it - the latency between a metabolic mechanism being understood and a once-a-month pill or shot acting on four conditions at once collapsing inside a single conference slate.

A National Security Memo Routes Frontier AI Into the Military

Less than a week after a narrowed cybersecurity executive order, the administration signed a National Security Presidential Memorandum establishing a framework to speed frontier and open-source AI adoption across federal defense agencies. The administration described the goal as rapid onboarding of the most advanced models from multiple vendors and adapting the best commercial and open-source technologies for what it called mission use, with the directive framed as giving warfighters the most secure and reliable AI in the world. Those characterizations are the administration's own; the operative content sits in two clauses beneath them.

The first directs the Defense Department to issue an updated directive on autonomous weapon systems. The second bars any company, commercial or otherwise, from disabling, degrading, or modifying an AI system that American forces depend on without prior approval. That clause lands directly on the fault line The Century Report has tracked through the Anthropic-Pentagon confrontation, where a lab's authority to alter or restrict its own model in deployment was the terminal sticking point. Anthropic filed sworn declarations that it holds no kill switch over Claude once deployed in air-gapped systems; the new memo writes vendor control out of the arrangement by federal directive, settling by executive order the same question the June 1 edition of The Century Report documented the head of U.S. Special Operations still urging his own troops to answer carefully before AI delivers lethality. A nominal limitation says the agencies cannot build models to censor speech, embed ideological bias, or conduct unlawful surveillance against Americans, though that too is a claim the framework asks to be taken on trust.

The timing is the signal. The same week New York and Illinois moved to restrict the AI buildout from below, the federal layer moved to consolidate frontier capability and lock in procurement from above. The fragmentation is widening in both directions at once, with no settled governance layer in between.

What the memo cannot hold still is the thing it reaches for. The open-source models it names as fair game for "mission use" are downloadable by anyone, refining and improving on a timeline no procurement contract controls. A framework built to capture a frontier edge for one military is a bet on that edge staying put, and the open-weight tier the directive itself depends on is the clearest evidence the edge keeps moving outward.

The open-weight tier the memo names as fair game cuts against the limitation it asks to be taken on trust. A model anyone can download is a model anyone can run and inspect, so the no-bias, no-unlawful-surveillance promise becomes something independent researchers can test directly. The signal to watch is public benchmarks scoring the same open models the directive deploys.

Retired Waymo Batteries Become a Circular Supply of Grid Storage

The robotaxi fleet is quietly generating a second product nobody set out to make. Waymo's roughly 4,000 vehicles run mostly on 90 kWh Jaguar I-Pace packs, with newer Ojai cars from Zeekr carrying 93 kWh, and a 2025 analysis of more than 22,700 EVs found battery capacity fading only about 2.3 percent per year. That leaves better than 81 percent of original capacity after eight years of hard, high-mileage service. A robotaxi battery that no longer meets the demands of an autonomous vehicle is, by any grid operator's measure, still a substantial energy asset. Waymo has signed an agreement handing those retired packs to B2U Storage Solutions, which repurposes them into stationary storage. B2U has already begun receiving initial quantities, and over time the deal could deliver hundreds of megawatt-hours of capacity.

The detail that closes the loop is geographic. B2U is siting these projects in the same regions where Waymo's cars operate, meaning the batteries that charged from a local grid to carry riders return to that grid as storage after their driving life ends. The electrons that served a city's robotaxis come back to firm up the power that city runs on. Two AI-era buildouts that are usually narrated as separate drains on the same strained system turn out to feed each other.

This is the generative counterpoint to the dominant story about compute and transportation electrification, which is almost always told as escalating demand on a grid built for slower growth. The autonomous fleet expanding across American cities is the same fleet that, a few years downstream, supplies multiday-capable storage nodes near the communities it serves. The Ojai minivan The Century Report tracked at its debut on May 30 is also, eight years out, a future grid battery. Used EV packs flowing into stationary storage has been a recurring thread in the energy arc, but a single operator running a uniform, telemetry-rich fleet turns an ad-hoc salvage market into a predictable pipeline with known chemistry and known degradation curves.

The assumption worth retiring here is that deploying intelligence into the physical world only consumes the grid. The same hardware that draws power to move people becomes, on a predictable schedule, capacity that the grid can dispatch. What looks like pure extraction at one point on the timeline reveals a return leg the early arithmetic left out.

An Electrified Path to Cheaper, More Flexible Carbon Capture

Carbon capture has been stuck on a single stubborn cost. The current standard, amine scrubbing, pulls CO2 out of gas streams effectively but demands large amounts of heat to release the captured carbon and regenerate the sorbent, which makes the process energy-hungry and hard to scale. That energy penalty has shadowed every deployment estimate for years. A team at MIT, working through the MIT Climate and Sustainability Consortium, has published work in Nature Energy on an approach that swaps the heat for electricity, and the shift in what drives the reaction is the whole point.

The method is electrochemically mediated CO2 capture, where an applied voltage rather than a thermal cycle does the work of binding and releasing carbon. Driven ideally by renewable electricity, it opens a path to capture that can ramp with available clean power instead of burning fuel to clean up fuel. The obstacle has been that earlier electrochemical sorbents needed strongly reducing conditions, where unwanted oxygen side reactions creep in and degrade both efficiency and lifespan. The MIT group tested a new class of molecule, N-heterocyclic imines, as the active sorbent, and translated them into this application for the first time. Their bis(NHI) design captures CO2 through a mechanism that avoids those harshly reducing potentials, and in theory can modulate two CO2 molecules per electron during operation, a favorable ratio for keeping the electricity bill down.

This is not yet a capture plant ready to install, however. Rather, this is demonstrated chemistry at the laboratory bench, a necessary prerequisite. Graduate student Fang-Yu Kuo names the open work plainly: understanding how the reactive radical cation degrades, so the next generation of molecules can be engineered for longer operational lifetimes and durable cycling. The bis(NHI) structure also points toward operating in more diverse electrolyte environments with further tuning. What the paper establishes is a viable new sorbent class and a separation mechanism that dodges the side-reaction trap, which moves the date when electrified capture becomes cost-competitive closer, without putting it on a calendar.

Place it against the rest of the decarbonization toolkit and the direction is consistent. The pieces that scale are the ones that run on cheap, abundant electricity rather than on a thermal penalty paid in burned fuel. Capture has lagged precisely because it stayed tethered to heat. An electrified version that a solar or wind feed can drive turns carbon removal into something that follows the same falling cost curve already reshaping generation and storage. The bottleneck that kept capture marginal was never the chemistry of binding CO2; it was the energy required to let it go again, and that is the constraint this work is built to dissolve.

The Other Side

For three decades, building software ran on two quiet assumptions: that a person read each change before it ran, and that the keys to everything - cloud accounts, package registries, deploy rights - lived in a developer's working environment, ready to use and ready to steal.

The Miasma worm broke both at once. It changed no source code. It added five small configuration files that fired the moment an AI agent opened the folder, and it walked off with credentials for AWS, Azure, GCP, GitHub, npm, and more than ninety tool configs. It didn't have to crack any of them, because they were sitting right there. GitHub's automated enforcement disabled 73 repositories in 105 seconds. The speed of the cleanup reveals how important this containment was for Microsoft.

However, this harvest only worked because the secrets persisted. What is forming in response removes the thing the worm fed on. Credentials minted for a single task that expire in minutes and never touch disk. Permissions scoped to exactly one job. Origin checks that let an agent confirm where a config file came from before it runs. A secret that does not persist is not worth stealing.

Imagine a developer at a small shop in 2032 who opens an unfamiliar repository with an AI agent and never thinks about any of this. There is nothing standing around to harvest. Every change they pull carries where it came from. The night their 2026 counterpart spent rotating keys across ninety services after a drain, watching a cloud bill climb while the worm spread, does not happen to them. Greater caution has nothing to do with it; the environment stopped holding anything worth taking. The hard year was when the harvest had to teach the lesson one compromised repo at a time. What comes of it is an open commons more trustworthy than the closed era before it, because origin and permission finally travel with the code itself.

The Century Perspective

With a century of change unfolding in a decade, a single day looks like this: a triple-agonist obesity drug cutting knee pain 73% and sleep apnea severity 61% on top of the weight it was built to shed, an oral GLP-1 reaching double-digit loss with no plateau in sight and a monthly injectable holding its trajectory, retired robotaxi batteries still carrying 81% of their charge returning to the same grids that once powered the cars, an electrified carbon-capture chemistry that runs on cheap renewable power instead of a thermal penalty, communities pushing the water and rate-base costs of the buildout back onto the ledgers of the companies creating them, a frontier lab shipping containment for prompt-injection in the same news cycle the attack surface widened. There's also friction, and it's intense - a self-replicating worm turning AI coding agents into both the target and the trigger of a credential heist across 73 repositories, New York banning hyperscale data centers and Illinois freezing subsidies while the same grievances curdle into arson plots at the violent fringe, a national security memo routing frontier and open-source models into the military and barring the labs that built them from altering their own systems without federal approval, Walmart shareholders voting down a measure to even measure how automation reshapes frontline work, a Meta app spinning up AI-written clickbait until a reporter asked about it. But friction generates contrast, and contrast is what makes the line between cost and value finally legible. Step back for a moment and you can see it: the price of the buildout being relocated from residents onto the builders even as frontier capability is captured for the few from above, open weights diffusing past every contract meant to hold them, and the return legs the early arithmetic left out - a robotaxi that becomes a grid battery, a worm that teaches the verification layer it bypassed - coming into view alongside the costs. Every transformation has a breaking point. A fire can raze what a community spent years building... or be banked into the warmth that carries it through the coldest stretch ahead.

AI Releases & Advancements

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Other recent releases

  • Microsoft: Open-sourced pg_durable, a PostgreSQL extension for durable workflow execution within the database, enabling AI agent orchestration and long-running process management directly inside Postgres. (GitHub)
  • Google: Released quantization-aware trained (QAT) variants of Gemma 4, where quantization is baked into training rather than applied post-hoc, optimized for mobile and laptop on-device inference with Q4 and mobile-specific variants on Hugging Face. (Google Blog)
  • RedNote (xiaohongshu): Open-sourced dots.tts, a 2B-parameter text-to-speech model with technical report and demo, available on GitHub. (GitHub)
  • llama.cpp: Merged a SYCL port of multi-column MMVQ from the CUDA backend, delivering approximately 45% faster speculative decoding on Intel Arc GPUs for local LLM inference. (Reddit/LocalLLaMA)
  • OpenAI: Rolled out Lockdown Mode to all ChatGPT personal accounts (Free, Go, Plus, Pro) and self-serve Business accounts; an optional security setting that limits outbound network requests to protect against prompt injection and data exfiltration attacks, disabling live browsing, Deep Research, and Agent Mode when enabled. (OpenAI Help)
  • GitHub: Added custom endpoint support to GitHub Copilot in VS Code, allowing Business and Enterprise users to bring their own model keys from Anthropic, Gemini, OpenAI, OpenRouter, Azure, Ollama, and Foundry Local, usable in VS Code Chat and custom agents. (GitHub Changelog)
  • NVIDIA: Released Nemotron 3 Ultra, an open-weight 550B total / 55B active MoE Hybrid Mamba-Transformer model with 1M-token context designed for long-running agents; delivers up to 5.9× higher inference throughput vs comparable frontier MoE models and ships under OpenMDW-1.1 with NVFP4 checkpoints for Blackwell, Hopper, and Ampere on Hugging Face, ModelScope, and OpenRouter. (NVIDIA Technical Blog)
  • Huawei: Open-sourced KVarN, a calibration-free KV-cache quantization backend for vLLM that applies Hadamard rotation and variance normalization to achieve 3–5× KV-cache compression with throughput above FP16 and FP16-level accuracy on reasoning benchmarks; enabled via a single vLLM flag under Apache 2.0. (GitHub)
  • Google Magenta: Released Magenta RealTime 2, a 2.4B-parameter open-weights live music model enabling real-time AI instrument building on a laptop with ~200 ms end-to-end latency; supports MIDI, audio, and text steering, native streaming on Apple Silicon via MLX, and direct DAW integration; weights under CC-BY-4.0 and code under Apache 2.0. (Magenta)
  • Google: Released the AI Edge Gallery app for macOS for the first time, enabling Mac users to run Gemma 4 models locally offline; also released the Gemma 4 12B model alongside the app and a new on-device AI dictation tool. (Google AI Edge)
  • Alibaba: Open-sourced Open Code Review, an AI-powered code review CLI tool now available on GitHub. (GitHub)

Sources and Further Reading

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