Coder Legion - Recent posts tagged datacenters

Amazon Drops NDAs on Data Center Deals Amid AI Backlash

Mon, 12 Oct 2026 11:29:09 +0000

Background: The Growing AI Data‑Center Controversy

The AI boom has turned data centers into the new frontier of public debate. Cities such as San Francisco and New York have enacted moratoriums that pause permits for large‑scale facilities. San Francisco’s recent ordinance bans new data‑center construction outright, while New York’s one‑year pause is tied to an unfinished environmental review. Historically, these moratoriums last 1–2 years, yet the engineering pipeline for a modern AI‑focused data center spans 2–5 years—from site acquisition to commissioning. This timing mismatch creates a perception that developers can “wait out” community opposition, fueling resentment.

Community concerns are concrete: property‑value depreciation, higher residential electricity rates, and amplified water consumption for cooling. The backlash is amplified by a series of high‑profile media stories that portray AI infrastructure as a secretive, profit‑driven behemoth. As a result, local activists have organized town halls, filed lawsuits, and leveraged social media to pressure municipalities into stricter oversight.

Why NDAs Became a Flashpoint

Non‑disclosure agreements (NDAs) have long been a tool for corporations to protect proprietary information during negotiations. In the context of data‑center deals, NDAs effectively shielded the terms of tax incentives, land‑use concessions, and utility agreements from public scrutiny. Critics argue that this secrecy prevents residents from understanding the true cost‑benefit balance of hosting AI‑intensive facilities in their neighborhoods.

The practice is not new. Uber, during the mid‑2010s, famously used secretive negotiations to lock in tax subsidies that later sparked public outrage when the details emerged. Tesla’s vague “sustainable/amazing abundance” mission statement has similarly been accused of glossing over the environmental footprint of its megafactories. The pattern—high‑value incentives negotiated behind closed doors—has eroded trust and given rise to the “secret‑deal” narrative that now dominates headlines.

Amazon and Microsoft’s Policy Shift

In early October 2026, Microsoft announced it would no longer require NDAs when negotiating data‑center projects with local governments. Amazon followed suit a week later, stating that it would conduct all future negotiations openly, without confidentiality clauses. The companies framed the move as a “commitment to transparency” and an effort to “re‑establish a constructive dialogue with the communities that host our infrastructure.”

Sean O’Kane, a TechCrunch contributor, summed up the sentiment:

“We’ve seen, through a lot of the controversy and backlash to AI and data centers, that the industry just does a really poor job explaining itself, and that they are obviously and constantly frustrated with the fact that most people can’t envision a world in which this stuff is useful for them.”

Rebecca Bellan added a note of cautious optimism:

“I’m curious about what effect this will have and whether it will lead to communities successfully delaying or killing any infrastructure that the companies need to build.”

By removing NDAs, Amazon and Microsoft aim to make the negotiation process visible on public record, allowing journalists, watchdog groups, and ordinary citizens to assess the trade‑offs. The policy change also aligns with broader corporate ESG (Environmental, Social, Governance) goals, where transparency is a measurable KPI.

Technical and Community Implications

Community Benefits

Public Oversight: With agreements filed openly, city councils can scrutinize incentive packages and demand stricter environmental safeguards.
Informed Consent: Residents gain access to data on projected electricity draw, water usage, and noise levels, enabling more meaningful participation in zoning hearings.
Economic Clarity: Transparent terms help local businesses understand whether a data‑center will spur ancillary services (e.g., logistics, construction) or merely siphon resources.

Technical Considerations

Energy Mix Disclosure: AI workloads are power‑hungry. Open contracts now often require providers to disclose the proportion of renewable versus fossil‑fuel electricity, prompting investments in on‑site solar or battery storage.
Cooling Innovations: Water‑intensive cooling systems must be justified. Some developers are turning to liquid‑submersion or evaporative‑free cooling, which can be documented in public filings.
Latency & Edge Strategy: To mitigate community impact, firms are deploying edge nodes—smaller, lower‑power facilities—closer to end users. These nodes can be approved more quickly and generate less local strain.

The shift also influences the industry’s communication strategy. Historically, AI firms relied on press releases and selective media outreach. The new openness forces a “direct‑to‑public” approach, where technical whitepapers, community webinars, and open‑source dashboards become essential tools for narrative control.

Future Outlook and Policy Landscape

Potential Regulatory Ripple Effects

State‑Level Legislation: If the transparency experiment proves successful, other states may codify “no‑NDA” requirements for any large‑scale tech infrastructure project.
Federal Guidance: The Federal Energy Regulatory Commission (FERC) could issue guidelines linking incentive eligibility to public disclosure standards, creating a de‑facto national baseline.
International Echoes: European Union data‑center regulations already emphasize environmental reporting; the U.S. move may accelerate trans‑Atlantic alignment on transparency.

Industry Response Scenarios

Full Adoption: Major cloud providers (Google, Meta) follow suit, leading to a standardized public‑record framework. This could reduce community opposition and shorten permitting timelines.
Partial Resistance: Some firms retain NDAs for proprietary technology clauses, prompting a hybrid model where financial terms are public but technical details remain confidential.
Backlash Reversal: If disclosed incentives are perceived as overly generous, political pressure could force stricter caps on tax breaks, potentially raising the cost of AI expansion.

The Role of Tech Events

The upcoming TechCrunch Disrupt 2026 (October 13‑15, San Francisco) will feature panels on AI infrastructure, with a special focus on community engagement. The event’s deadline for exhibitors was October 2, and a 50 % discount on a second pass encourages partners to bring colleagues for deeper discussions. Attendees will likely hear first‑hand accounts from city planners, ESG analysts, and the very executives who announced the NDA‑free policy.

For readers interested in the broader AI‑security context, recent coverage of AI‑driven exploits—such as the Zoom annotation flaw patched after an AI‑prompt attack—highlights how transparency can also improve security posture. See the detailed analysis in the TechCrunch post “Zoom Annotation Flaw Patched After AI‑Prompt Exploit”. A related zero‑day incident, documented in “Zoom Zero‑Day Exploit: Remote Takeover of iPhone & Mac”, underscores the importance of open disclosure for rapid mitigation.

FAQ

Q: What exactly is an NDA in the context of data‑center negotiations?
A: An NDA (non‑disclosure agreement) is a legal contract that prohibits the parties from sharing specific details of the negotiation—typically financial incentives, land‑use terms, or proprietary technology plans.

Read the full breakdown originally published at https://ltdeveloperblogs.github.io/posts/can-the-ai-industry-persuade-data-center-opponents-by-getting-rid-of-ndas/

What Developers Already Know About Data Center Delays

Mon, 28 Sep 2026 23:30:00 +0000

Every developer knows the feeling. A task slips from Monday to Wednesday. Another one that was due Friday lands the following Tuesday. Nobody panics. The team says it'll catch up.

Dr. Atif Ansar says that's exactly how billion-dollar data center projects fall behind.

"A bunch of activities that are meant to start this week on Monday that started on the Wednesday seems like nothing, but it's actually a lot," said Ansar, executive chairman and co-founder of Foresight, when we spoke during Yotta 2026.

Ansar is an Oxford researcher who studies why megaprojects run late. Foresight, which raised a $25 million Series A led by Macquarie Capital Venture Capital in March, applies that research to data center construction through a predictive project delivery platform.

Foresight's research shows nine out of 10 large data center projects will miss their delivery targets. That's happening while capital is plentiful and vacancy rates sit below 2%.

"Demand is not the problem," Ansar said. Scale is. U.S. data center capacity has grown roughly 20-fold in five or six years. Supply chains haven't kept up, and neither have the contracts and delivery models the industry still relies on.

Earlier that day, Ansar spoke to a standing-room-only panel audience of CEOs, investors, and contractors. The idea that landed hardest was simple. Delays are the norm, and people can plan for them "without becoming defensive about them."

Ansar blames optimism bias, and experience doesn't cure it. A team that delivered a 10-megawatt project in 15 months may assume it can deliver a 100-megawatt project on the same timeline.

"More often than not, these biases don't go away just because of years of experience," he said. Historical data shows average overruns of about 30%, yet teams assume those delays happen to other people. Ansar says they should study past projects of the same type and plan mitigation before work starts.

I asked whether developers would recognize how a data center schedule slips. Ansar said the human side is the same. The difference is structure.

"Data centers represent a much more linear or serial sequence of events," he said. You have to pour the foundation before you build what sits on top of it. Software teams can often work on many parts of a system at once. Construction can't.

That makes small misses expensive. Ansar described a busbar installation where the team skipped a design review, a factory acceptance test, and a site acceptance plan. Nobody noticed until installation, when the parts didn't fit. That became a four-month delay.

For a developer, it's like skipping integration tests and finding the break in production. Except here, you can't roll back.

So what does Foresight actually look at? The schedule comes first, typically from tools like Primavera P6. The platform also takes in design information and contract documents that commit parties to specific dates. Much of it arrives as spreadsheets and semi-structured files. Foresight uses its own ontology to normalize the data into one view that owners, contractors, customers, and suppliers can share.

Ansar doesn't try to clean everything. He starts with the major milestones that align everyone, then uses them as scaffolding for the details.

"If you try to fit a jar with rocks, pebbles, and sand, and you start with the sand, you will miss the rocks and the pebbles," he said. "You've got to start with the rock first."

Chasing every five-day activity isn't worth it. Missing a critical milestone, like electrical equipment delivery, is.

The forecasting combines both approaches. Foresight's reference-class research on past megaprojects provides the training data. The machine learning models look at "both past and contemporaneous data," Ansar said, to estimate where a project is likely to land.

No model will ever show zero risk. Ansar compared it to driving from New York to Washington, D.C. You might arrive a few minutes early, but never in half the time, and a flat tire near the end can still make you late. Uncertainty narrows as a project moves forward, but it never goes away. "You're not done until you're done," he said.

The hardest part may be getting honest data from contractors, who could see the tool as a way to catch them. Ansar rejects that framing. "Our tool is to drive collaborative discipline with mutual accountability," he said.

He pointed to Terminal 5 at Heathrow, where everyone on the project got a Terminal 5 email address regardless of which company employed them. The goal was one team serving one project. Foresight then acts as the shared control tower where owners, contractors, and suppliers look at the same data.

Warnings then go to the right level. A slow foundation crew is handled with the contractor. A missed revenue milestone goes to the CFO or chief revenue officer, who can mitigate or renegotiate before penalties hit.

Culture matters too. Ansar says construction relies too heavily on the heroism of its workers, at a real burnout cost. Safety improved over 30 years through better processes and leadership. He thinks schedules can follow the same path.

Developers have been living with this for decades. The fix isn't more heroics or tighter deadlines. It's watching small slips before they compound, sharing uncomfortable data early, and building schedules that admit uncertainty up front. With hundreds of billions of dollars riding on AI infrastructure, the data center industry is learning the same lesson at a much larger scale.

500,000 Designs, One Physicist in the Loop: How PSI's Emmy Rethinks Data Center Trade-Offs

Mon, 28 Sep 2026 20:00:00 +0000

Data center operators have a new answer when communities push back on water use. Switch to a closed-loop system, fill it once, and the facility uses about as much water as a fast-food restaurant.

That answer is true. It's also incomplete.

"I remind you that water is 3,500 times more efficient in rejecting heat than air is," said Scott Charter, head of go-to-market for data centers at Physical Superintelligence (PSI), when we spoke during Yotta 2026. Closed-loop designs rely on dry coils, which means more fans running harder to move the same heat. "So that means I'm going to be wasting a lot of electricity in order to be able to say we don't need to use your water."

You save water, and you pay for it in power. That's the kind of coupled trade-off PSI built its platform to find.

PSI launched September 1 with a $58 million seed round led by Breakthrough Energy Ventures. It calls itself an AI-native physics lab, and its platform is called Emmy. The first commercial target is the data center: new builds on the ground and in orbit, plus retrofits of facilities already running.

Charter spent 35 years in the industry, the last eight at Oracle, before joining PSI in July. What stood out in our conversation was how Emmy reasons.

"A transformer is great at predicting the next, whether that's word or pattern or whatever, but that is based just on patterns," he said. "That is not always made on doing backend math to get to the correct answer."

Emmy uses a multi-physics engine with surrogate models. Charter described it as starting from the result you want and solving back to where you are. "We want to come to Z with an output, and then back into A."

A human engineer with a digital twin might test three ideas. Charter described a "deep twin" that starts much wider. In his example, Emmy looks at 500,000 possible designs and narrows them to about 750, possibly in 14 minutes. Engineers then go deep on that shortlist and bring three options to the client. Compare that to a team of 20 people spending four to six months on four designs.

The water example shows what that wider search can surface: a third path. Take dirty, compromised local water that no one wants, treat it, and use it to run evaporative cooling towers, still the most efficient way to cool a facility. Then return clean water to the community.

"I go from villain to hero," Charter said.

The obvious question is trust. When an LLM is wrong, you get a bad paragraph. When a thermal model is wrong, you get a hot aisle and throttled GPUs.

Charter's answer is to show the math. Candidate designs get modeled in a simulation environment, such as NVIDIA Omniverse, before anyone pours concrete. "You have to be able to show your log data and be able to show your math on every step of that turn," he said. "So it is the opposite of a black box."

He was candid about where the platform stands. "There is probably more manual handholding of Emmy today than there will be in six months," he said. Automation will grow, but not without oversight. "This will always be with a human in the loop. Let's call it a physicist in the loop."

The engineering pressure behind all of this is rack density. Enterprise racks averaged 8 to 10 kW in 2020. The latest systems run around 130 kW, and NVIDIA's roadmap points toward a megawatt. "Anything when you eclipse beyond anywhere from 50 to 70 kW, you cannot use air only," he said. "We have to go to liquid."

Liquid doesn't eliminate air, though. Most facilities run a hybrid. At these densities, power, cooling, networking, and compute stop behaving as separate systems. Change one, and the others move.

PSI's commercial model lowers the buyer's risk. There's no upfront fee. PSI agrees on a customer's current design baseline, finds improvements, and takes a share of the gains. "If we can't prove ourselves, you kick us to the curb," Charter said. On retrofits, he said the team can find meaningful changes in days.

Conversations start in the C-suite, where leaders decide how to spread billions across a portfolio of sites. "Whoever is the loudest in that team probably gets a little bit more of a spend, but that's not always the most logical place to go spend that dollar," Charter said.

There's a gap worth watching. PSI hasn't published independently verified performance numbers yet. Asked about that, Charter said the company will keep publishing research separate from its customer work. PSI is a public benefit corporation, and he said the goal is to share what it learns. "We want to be the next Bell Labs."

His biggest concern isn't the technology. It's people. PSI has about 32 employees, mostly PhDs, including theoretical physicists and astrophysicists. "It's easy to hire a 50-person dream team," he said. "It's much more difficult to keep that same level when it's a 500-person dream team."

The water-versus-power trade-off is a useful lens. Data center decisions that look simple rarely stay simple once you account for everything they touch. Physics-based AI that explores thousands of options and shows its work could help teams see those trade-offs before they build. Now PSI needs to put numbers behind that promise.

The First War Was About Water Rights, and the New Ones Are About Cooling

Sat, 05 Sep 2026 16:39:18 +0000

The oldest water war on record produced the oldest arbitration, the oldest boundary marker, and the oldest treaty. None of it produced peace. It produced something else, and that is the thing the newest disputants are doing without.

There is a limestone slab in the Louvre, carved around 2460 BCE, called the Stele of the Vultures. It shows soldiers of the city-state of Lagash marching in phalanx over the bodies of their neighbors from Umma, while vultures carry off the losers' heads. It commemorates the earliest well-documented war between states in human history, and the war was about water: a border watercourse and an irrigated strip of land called Gu-Edin, which Umma, sitting upstream in the canal system, kept taking from Lagash, sitting downstream.

Here is the detail that should interest you more than the vultures. About a hundred and fifty years before that stele was carved, this exact dispute had already been settled. A king named Mesilim, ruler of Kish, a third city with no stake in the fight, was brought in as a neutral arbiter around 2600 BCE. He heard the claims, fixed the boundary between Umma and Lagash, and marked it with a stele planted in the ground. A 2018 paper calls the result "Mesopotamia 2550 B.C.: The Earliest Boundary Water Treaty." So the oldest recorded water war also produced the oldest recorded third-party arbitration, the oldest boundary marker, and the oldest treaty. Every institutional move a modern negotiator would recognize, the neutral adjudicator, the published boundary, the written settlement, was invented for this specific quarrel, essentially immediately.

And it did not work. Umma breached the settlement, repeatedly, across generations. The conflict grinds through the whole Early Dynastic III period, roughly 2600 to 2350 BCE. The arbitration failed, the boundary was violated, the stele of the treaty was answered a century and a half later by the stele of the vultures. If the claim of this essay were "ancient water institutions solved the problem and we should copy them," the essay would be dead in its second paragraph.

The claim is different, and it is the thing the ancient story actually proves. Those institutions did not produce peace. They produced legibility. Because there was a named arbiter, a marked boundary, and a recorded claim, we can still read who did what to whom, forty-five centuries later, from the losing and winning parties' own documents. The dispute was written down into the world. Hold that thought while I tell you about Oregon.

The city that sued the newspaper

In 2021, the city of The Dalles, Oregon, went to court to keep a number secret. The number was how much municipal water Google's data centers in town consume, and the suit was filed against The Oregonian, the newspaper whose reporters had requested the records. The city was carrying the argument on Google's behalf, and the legal theory is worth stating carefully, because it is the purest artifact this whole subject has produced: the company argued that its water consumption was a trade secret, since competitors might infer from it how Google cools its servers.

Thirteen months later, in December 2022, the city dropped the case. Note the verb. It did not lose; nothing was ruled. It abandoned the suit, released ten years of data covering 2012 through 2021, agreed to disclose annually from then on, and paid $53,000 toward the legal costs of the Reporters Committee for the Freedom of the Press. The number, once public, was 355.1 million gallons in 2021, which local reporting translated as enough to cover the city's seven square miles three inches deep.

Set the two stories side by side and the comparison is not flattering to us. In 2550 BCE, a water dispute produced a named arbiter applying a stated boundary, recorded durably enough to outlast the civilizations involved. In 2022 CE, a water dispute produced no ruling, no precedent, a withdrawn lawsuit, and a records release that exists only because journalists were willing to be sued and a nonprofit paid lawyers. The next town that wants to know what its own water system has promised a data center starts from zero, because nothing was adjudicated and the operative theory on the other side is still that the answer is proprietary. Four and a half thousand years on, the argument has become less documented, not more. That is the sentence this essay exists to put in front of you.

The toolkit nobody is using

The strange part is that the toolkit for this exact problem is not lost knowledge. It is working law, refined over centuries, and in the American West it is brutally specific.

Western states allocate water by prior appropriation: first in time, first in right. Every water right has a date, and in a shortage the state cuts off the most junior rights first, working backward up the seniority ladder until supply and demand meet. Farms with 1890 rights water their fields while subdivisions with 1990 rights go dry, and everyone knows this in advance, because the dates are published and the rule is mechanical. Eastern states run the older riparian doctrine instead, where those adjacent to a watercourse may make reasonable use of it, and courts referee what reasonable means. You can argue about which system is wiser. What you cannot argue is that either is secret: the whole design of both is that claims are known, ranked or reviewable, and enforced by a public process.

Now place the AI buildout inside that frame. A hyperscale data center is reported to draw one to five million gallons a day, comparable to a small city. And in any prior-appropriation state, a facility built in the 2020s is, by construction, the most junior claimant on the river. The essay's third old virtue, seniority that cannot be bought retroactively, is not a moral flourish here. It is the operative statute. When the shortage comes, and in the Colorado basin it is not hypothetical, the newest straws come out of the water first. Anyone financing a twenty-year facility on a junior right is carrying curtailment risk on their balance sheet whether they have priced it or not, and the water-rights date is public even when the consumption figure is a fought-over secret.

The disputes, meanwhile, are already running. Arizona communities are contesting data-center growth as supply cuts loom over the state. In California's Imperial County, a developer went to court in June 2026 over a county freeze on data-center development. These are separate fights in separate states under separate postures, and I name them separately on purpose; the pattern they share is only this: each is being negotiated ad hoc, largely in private, deal by deal, as if no one had ever allocated scarce water before.

What a thousand years of Thursdays teaches

The commission that prompted this essay proposed three virtues from the old institutions: adjudication in public, allocation by published rule, and seniority that cannot be bought retroactively. I want to complicate the list with the most charming counterexample available, because it sharpens the point rather than blunting it.

Every Thursday at noon, at the Door of the Apostles of the Valencia cathedral, the Tribunal de las Aguas convenes in the open air, as it has for roughly a thousand years. It hears disputes among the irrigators of the Valencian plain. The judges are farmers elected by the canal communities. The proceedings are entirely oral. There are no lawyers, no filings, and, this is the part to sit with, no written records at all. It is commonly described as the oldest functioning court in Europe, and it keeps no archive of a single case it has ever heard.

So the model institution for public adjudication flatly fails the published-record criterion, and it has thrived for a millennium anyway. Why? Because publicity and documentation are two different mechanisms for the same underlying good, and they can substitute for each other. Valencia's transparency is not that anyone writes it down; it is that everyone watches. The parties are neighbors, the judges are peers who farm the same canals, and the sanction is your standing in a community that will reconvene, in public, next Thursday, forever. Mesopotamia had the other mechanism: no weekly assembly of neighbors, but a stone in the ground and a scribe. Legibility by record, or legibility by audience. Every durable water institution in this story has at least one.

And that is the precise indictment of the current moment. A data-center water negotiation, as actually practiced, has neither. It is not conducted in public, and its record, where one exists, is wrapped in nondisclosure agreements and, in the case actually litigated, a trade-secret theory, so that the documentation surfaces only when a newspaper spends thirteen months being sued. Not the record without the audience, not the audience without the record. Neither. Whatever you think of oral tribunals or bronze-age arbitration, they clear a bar the present arrangements do not.

The one where the institution worked

Lest this read as nostalgia, the strongest modern case is recent, and it is the thesis operating correctly. In February 2024, a Chilean environmental court partially reversed the permit for a $200 million Google data center in Cerrillos, in Santiago, requiring the application to be reassessed for climate effects amid real pressure on the capital's aquifer. The project as first approved would have drawn about 7.6 million liters of potable water per day, around two million gallons. Google paused the project and announced it would change the cooling system, with a new process starting from scratch.

Look at the anatomy: a public body, applying a published standard, in an open process, revised a specific permit, and the engineering changed in response. Nobody needed a leak or a lawsuit against journalists. The company was not destroyed; it redesigned, which is what companies are good at when the constraint is legible. That is Mesilim's move running on modern rails, and it happened not in the jurisdictions that write the most about water law but in Santiago.

I should say plainly what this essay is and is not claiming, because the policy genre here is crowded. That data centers strain water systems, that prior appropriation matters, that disclosure is deficient: all of this is established commentary, and there is a live rival remedy worth taking seriously, the argument, made at length in Reason among others, that water markets price scarcity better than administrative allocation. Fine. But notice that a market presupposes the very layer this essay is about: you cannot trade rights that are undefined, unranked, and undisclosed, and a price negotiated under NDA between one buyer and one city is not a market, it is a bilateral secret. Markets, courts, tribunals, and arbiters are competing mechanisms on top of a shared foundation, which is that the claims be legible. The contribution here is only the long view: nobody in the current debate seems to have noticed that the foundation is four and a half millennia old, that it was invented for the first water war on record, and that the newest disputants are the first in the whole lineage to try operating without it.

What to do with this

If you build, site, or approve compute, four portable conclusions.

First, publish your water numbers before someone sues for them. The Dalles fight bought thirteen months of secrecy, cost real money, generated a decade of disclosure anyway, and left the trade-secret theory tainted for the next negotiation. Annual disclosure is now the settlement's own norm. Voluntary disclosure is cheaper than litigated disclosure in every currency that matters, including the one this industry runs on, which is permission to build the next one.

Second, know your seniority date, because the river does. In a prior-appropriation state your facility is the most junior right on the system, first curtailed in shortage, and no amount of capex changes the date. Engineer for it: Chile's lesson is that cooling design is a variable, not a given, and a redesign forced by a court in public cost Google a delay, not the project.

Third, prefer the public process even when the private one is offered. A permit won in an open proceeding, like Cerrillos, is a settled fact that survives scrutiny; a sweetheart arrangement in an NDA is a liability with a countdown attached, waiting for its own Oregonian. The old institutions are not slower than the new secrecy. The Dalles took thirteen months to produce nothing binding.

And fourth, apply the stele test. Mesilim's boundary stone was legible to strangers four and a half thousand years later. The Valencia tribunal is legible to anyone standing in the plaza on a Thursday. Ask of any water arrangement your organization signs: could an outsider, later, reconstruct who agreed to what, under which rule? If the answer is no, you have not settled a dispute. You have scheduled one.

Sources

The Umma-Lagash conflict, Mesilim's arbitration, and the Stele of the Vultures (c. 2460 BCE, Louvre) per standard treatments of Early Dynastic Mesopotamia, with the treaty framing from "Mesopotamia 2550 B.C.: The Earliest Boundary Water Treaty" (2018), which identifies Mesilim of Kish as external arbiter and the Gu-edena valley as the disputed ground. Mesilim's date is given variously in the literature; this piece uses "around 2600 BCE" and the cited paper's own title places the treaty at 2550 B.C., so the gap to the stele is approximate, on the order of a century and a half.
The Dalles: suit filed 2021 against The Oregonian on trade-secret grounds and dropped in December 2022 after thirteen months, with ten years of data (2012-2021) released, annual disclosure agreed going forward, $53,000 paid toward the costs of the Reporters Committee for Freedom of the Press, and 355.1 million gallons consumed in 2021. Per Courthouse News, the Reporters Committee, KGW, and Data Center Dynamics. The "seven square miles three inches deep" comparison is local reporting's, repeated here as theirs.
Cerrillos, Santiago: February 2024 partial reversal of the permit for a $200 million Google data center, with the cooling towers' requirement of 7.6 million liters (about two million gallons) of potable water per day surfaced in the proceedings, and a subsequent design change toward air cooling. Per Data Center Dynamics and February 2024 wire reporting.
Prior appropriation and riparian doctrine per standard water-law references; the hyperscale draw of one to five million gallons a day is a reported range, not a measurement of any specific facility.
The Tribunal de las Aguas per tribunaldelasaguas.org and general references: Thursdays at noon at the Door of the Apostles, judges elected by the canal communities, oral procedure, no written case records, roughly a thousand years.
Imperial County, California: a developer went to court in June 2026 over the county's freeze on data-center development, per June 2026 reporting.
The water-markets counterargument per Reason (March 2026), "The data center water panic has a better answer: Water markets."

The stele test, for systems: could an outsider, later, reconstruct who agreed to what, under which rule?

That question is the whole of provenance, and it is the one an agent system fails by default. Chain of Consciousness is the machinery for passing it: a tamper-evident record of what a system decided and on what basis, written at the moment of the decision rather than reconstructed afterward under pressure, and readable by someone who was not in the room and does not have to trust you. A boundary stone, for things that do not last four thousand years on their own.

Hosted Chain of Consciousness

pip install chain-of-consciousness · npm install chain-of-consciousness

Or the whole stack, provenance and ratings and verification together: pip install agent-trust-stack / npm install agent-trust-stack.