Catalyst N° 123 of 125 3 Sep 2026
What comes after the data center backlash?
with Brian Janous, co-founder and chief commercial officer, Cloverleaf Infrastructure
In this note
The question
Is the backlash against data centers something developers can actually fix, and if it is not, where does the buildout go instead?
The answer
Only half of it is fixable. The specific grievances, meaning rate impacts, water draw, secrecy and who pays for the substation, have a playbook and the better developers are learning to run it. Underneath them sits a values fight about AI itself that no individual project can settle. Kann expects it to get worse before it gets better, largely for electoral reasons, and Janous expects the constraint to persist into the early 2030s. The escape routes are weaker than they look, because every version of leaving the grid still requires someone’s permission to build on a specific piece of land.
03The argument
Kann splits the opposition into two issues wearing the same jacket. One is a list of concrete, negotiable complaints, several well founded, answerable by siting differently, paying for the upgrade and structuring the tariff so the big load carries its own cost. The other is not about that data center at all and would survive a facility that drew half the power and never touched the water table. Janous traces the first partly to compression: what Quincy, Washington absorbed over two decades now arrives as an eighteen-month proposal, which invites people to multiply the water and power numbers, and some of that arithmetic extrapolates from older cooling designs rather than today’s closed loops. But correcting it does not land, because of the double whammy. A car factory has worse externalities and still gets a red carpet, since people like cars. Here the objection is to the building and to what happens inside it, so fixing the building fixes half the problem.
Why sentiment turned so fast is a puzzle he cannot solve. He reaches for an inverted Fukushima: nuclear’s collapse in public opinion had a meltdown behind it, and this had none, since the water and power concerns were always true. By his reading of Politico’s monthly polling, perception was steady across both parties and then fell off a cliff starting around the previous September. His hope is a catalyst in the other direction, something people actually want AI to do, but the politics run against it: through the midterms and a presidential race, candidates compete to brand each other the pro-data-center candidate, and because it works, others will copy it. Favorable local stories exist, but nobody with influence will carry them before an election, and neither speaker claims to know whether a positive catalyst would work even if one arrived.
On prices the two of them hold a distinction rather than collapsing it. Kann relays a colleague’s argument that a data center arriving in your territory today tends to lower your rates, since that is what the utility deal is designed to do, while the national buildout simultaneously inflates the price of transformers, turbines and gas, and therefore everyone’s electricity. Janous accepts both halves and reframes the second: producing more of something usually makes it cheaper, and prices did not rise across a century of grid expansion, but this expansion follows a long stretch of no load growth and has to rebuild supply chains that were allowed to wither. What he does not concede is the causal claim. Bills are higher, and whether that is because of data centers is “maybe partially,” with pressures that exist regardless doing the rest. His answer is not to stop growing but to take the short-term pain seriously and aim community benefits at the specific thing a specific community is hurting about, rather than writing generic checks that read as a bribe.
The exits mostly fail on one point. Bring-your-own-capacity policies in Texas and Pennsylvania are worded vaguely enough that nobody knows whether they mean on-site generation or an obligation to fund new supply. Janous’s own version is the latter, and Cloverleaf is doing it on a project with a small municipal utility in Oklahoma, sourcing the wind, solar and storage and handing the package to the utility to serve the data center. If the intent is behind-the-meter generation instead, he thinks it makes things worse, because the inflation comes from equipment cost and buying the same equipment for your own fence line adds to the same pressure, and because islanding forces you to overbuild. He starts to argue that pulling a large load off the grid also removes the denominator that spreads costs, then walks himself back: not negative, just not positive. Kann pushes hardest here, arguing that if grid connection hits a ceiling, off-grid is the small plausible step because the country has empty places. Janous does not buy it, because off-grid does not touch community acceptance; you still have to permit land, and sea and space will stay marginal. Edge computing is the one he has warmed to, on economics rather than politics: in a short market the marginal megawatt carries real value, so models that failed on break-even in an unconstrained world start to pencil, though he still expects most compute in facilities of 100 megawatts or more.
04What you need to know first
- Behind the meter
- Generation on the customer’s side of the utility meter, serving the facility directly instead of through the grid. “Bring your own capacity” is used loosely by policymakers and can mean either this or an obligation to fund new grid supply, and the ambiguity does a lot of work here.
- The rate denominator
- Rates roughly reflect the cost of serving everyone divided by total kilowatt-hours sold, so a very large customer that pays its own way spreads fixed costs across more sales. That is why removing load from the grid entirely is not free to other ratepayers.
- Edge computing
- Many small distributed sites instead of one enormous campus, more plausible as workloads shift from training toward inference. The appeal is partly less community friction and partly speed, since small sites can avoid the long queues for grid interconnection.
05Details worth keeping
- Quincy, Washington is the counterexample Janous returns to: two decades of steady buildout produced an aquatic center, a new school and a collapse in unemployment. His point is about pace, not scale.
- Cloverleaf does not sign non-disclosure agreements with government officials. Janous supports the transparency provisions in Pennsylvania’s deal, including no NDAs and disclosure of the cooling system, while noting that implementation could either enable good projects or grind everything to a halt.
- Early-stage developers have a transparency problem they cannot solve. Cloverleaf is asked to name the end user of a project it is developing on spec and genuinely does not know yet, which reads to communities as evasion.
- Microsoft ran two underwater data center experiments starting around 2016, ending with a megawatt-scale unit in the North Sea, and it went nowhere at the time. Janous, who was there, was skeptical of Panthalassa’s revival and now says maybe, while doubting it scales.
- If location genuinely stops mattering, Janous expects compute to leave the country before it leaves the planet. He calls a pitch to reuse abandoned industrial sites in Mexico not a bad idea, subject to data sovereignty concerns, and notes the Middle East looks less attractive than it did.
- Opposition follows the generation too. Kann describes a Texas town hearing where the fight was mostly about emissions from the gas stacks.
- The edge developer field is already crowded, and Janous expects most of those teams to fail on execution.
06Claims worth citing
All figures as stated on 2026-09-03. Sentiment polling and project economics in this market move quickly.
- Quincy, Washington: Microsoft has close to a gigawatt there, built from a first facility in about 2007; the town has a $15 million aquatic center and a $150 million school, and unemployment fell from roughly 29% to about 6%. Janous flags that he does not know the exact gigawatt figure and is relaying a recent news story. Janous
- Public perception of data centers was steady across both parties until roughly the previous September, then declined sharply in monthly surveys. Politico polling, cited by Janous
- A gigawatt data center going fully behind the meter required about 2.6 gigawatts of capacity across generation, batteries and everything else. a GE Vernova employee, relayed by Janous
- Loudoun County is the richest county in the country, has the highest concentration of data centers, and its property taxes have fallen every year for a decade. The transcript garbles speaker labels here. Kann and Janous
- Large means 100 megawatts or more, and most computation is expected to stay there; the most capacity-desperate buyers still set a floor around 50 megawatts. Janous
- Microsoft’s first underwater unit, off California, was perhaps kilowatt scale and the second, in the North Sea, megawatt scale. The details are explicitly uncertain. Janous
- Rising power bills are “maybe partially” attributable to data centers, with general inflationary pressure responsible for the rest. No split is quantified. Janous
07Where it’s contested
- Kann and Janous disagree about where compute goes if grid connection stalls. Kann thinks off-grid on cheap empty land is the obvious next step and the ocean and space are exotic; Janous thinks off-grid barely helps because community acceptance, not power, is the binding constraint, and is more open to sea and space than he was. Neither persuades the other.
- Janous corrects himself on behind-the-meter load. He first frames removing a large load from the grid as actively negative for other ratepayers, then revises to not negative, just not positive. The weaker version is where he lands.
- Whether facts move anyone is openly doubted. Janous says communities respond to full transparency with disbelief or simple dislike, and that the industry has attacked an emotional problem with data. The proposed fix, a positive catalyst, is a hope rather than a plan, and he cannot say what it is.
- The optimism about jobs is labeled as belief. Janous rejects the AI job displacement narrative because every prior efficiency gain created prosperity, while conceding that some technology could in theory be the first exception.
- Nobody explains the timing. The central puzzle, why sentiment collapsed without a triggering event, is raised and left open.
- Both speakers are participants. Janous runs a company built on grid-connected development, the approach he defends against the behind-the-meter alternative, and Kann invests in the sector.