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Reliable Robotics: "Autonomous Cargo Operations in 2026," With Certification About Two Years Away

Tue, 20 Oct 2026 14:52:08 +0000

Originally published at vibeagentmaking.com.

Reliable Robotics announced $160 million under the subhead "Company to begin autonomous cargo operations in 2026." The operations are the test phase of a three-year federal pilot program and one Air Force demonstration aircraft, and the certification year reported that day is the sixth estimate since 2020 to sit about two years out.

On April 21, 2026, Reliable Robotics announced $160 million in new funding, led by Nimble Partners. The release carried a one-line subhead: "Company to begin autonomous cargo operations in 2026." Five paragraphs down, it named the two programs those operations belong to, a Federal Aviation Administration pilot program in Albuquerque and a contract with the U.S. Air Force, and said: "Both programs will begin operations this year."

Aviation International News ran the story later that day under a different second line: "U.S. start-up is pressing for FAA certification in 2028." The body attributed the date to the company. The money would go to the Reliable Autonomy System, "for which it is targeting FAA certification in 2028."

Operations this year and certification two years later can both be true. The explanation is in the company's other documents and the government's, which describe the same two programs in plainer words.

First, the money. DroneXL, summarizing chief executive Robert Rose's interview with Bloomberg that day, put the valuation at nearly $1 billion and the total raised at $300 million. Bloomberg's own headline, which the company lists on its news page, was "SpaceX Alum's Startup Nears $1 Billion Valuation in Pursuit of Uncrewed Flights." The release also cited "commitments for over 200 systems from commercial and military customers," a figure it does not break down.

What begins this year

The Albuquerque program is the Advanced Air Mobility Integration Pilot Program, known as eIPP. The Department of Transportation and the FAA picked eight projects across 26 states for it, under an executive order the department's page calls "Unleashing Drone Dominance," and Reliable and the City of Albuquerque are one of the eight. When Transportation Secretary Sean Duffy toured the company at Albuquerque International Sunport on June 17, 2026, the department's release said what the program is for. It "allows Reliable Robotics to test its autonomous regional cargo aircraft and explore the benefits this type of service could provide to rural communities." It gave a date: the company's retrofitted general aviation planes "are expected to begin test operations in August 2026." And Duffy said what the government gets from it: "The data from this pilot program will help the FAA finalize essential regulations and safely integrate this technology into the airspace."

That is how operations can come before certification. The department describes the eIPP as "one of the largest real-world testing environments for next-generation aircraft in the world," and what it produces is data for regulations the FAA has not yet finalized.

The company's own documents describe the program the same way once you read past the subhead. Its March 9 release announcing the selection says that Reliable Airlines, its wholly owned cargo airline in Albuquerque, "will conduct autonomous air cargo operations" from the Sunport to Durango, Colorado, and Santa Fe. The same release contains this sentence: "Completion of this program will mark the first commercial operation of regional air cargo service by a large UAS in the United States." UAS stands for uncrewed aircraft system, and the milestone is tied to the program's completion. The company's newest blog post, dated September 11, 2026 and written by Paul Smith, its director of flight operations, gives the program's length: "A three-year project in the FAA's Advanced Air Mobility Integration Pilot Program is creating a runway to test commercial air cargo operations."

The Air Force program is narrower. In August 2025 the company announced a $17.4 million contract, which National Defense Magazine described as a deal "to purchase, integrate and test its continuous autopilot platform onto a Cessna 208B Caravan cargo plane." The company's December 2025 release about Rose's testimony to a House aviation subcommittee refers to "an active contract to deploy an automated Caravan in the Indo-Pacific for the U.S. Air Force in 2026," and the March release says the company will "demonstrate continuous logistics operations without a pilot onboard." That is one aircraft, deployed for a demonstration.

So the operations that begin in 2026 are the opening months of a three-year federal test and a military demonstration with one airplane. Both are real programs with serious partners. At least one close observer read the announcement as more than that. DroneXL's editor, writing that morning, said of the Albuquerque plan: "That is a commercial freight operation, not a demo."

Who flies the airplane

"Autonomous" has a definite meaning in this company's usage, and its technical documents state it plainly. The system keeps the airplane on autopilot through every phase of flight, from taxi and takeoff to landing, while a pilot in a control center on the ground is responsible for the flight. National Defense Magazine, paraphrasing Rose in August 2025, wrote that the system "requires a remote pilot in a control center who uses the radio and programs the aircraft, but who does not hand-fly the plane from far away." The company's April 7, 2026 release on its detect-and-avoid flight tests says its system "is designed to facilitate a remote pilot's responsibility to perform both Remain Well Clear and Collision Avoidance functions against all airborne traffic." Smith's September post is shorter: "you can take the pilot out of the cockpit, but you cannot take them out of the loop."

The people hosting the program use the other word. In the company's own March release, Albuquerque's acting aviation director, Manny Manriquez, calls it a "remote-piloted cargo aircraft deployment project." On the department's June page, the city's economic development director, Max Gruner, speaks of bringing "remotely-piloted regional air cargo operations to New Mexico." The company uses the phrase as well. Its release on the December 2025 testimony says "Reliable's fully automated Cessna 208 Caravan will help expand remotely piloted air cargo operations to small towns and rural communities." In October 2021, the headline on its $100 million funding release read "Reliable Robotics Raises $100 Million to Expand Access to More Places With Remotely Piloted Cargo Operations." Rose called the product "our Remotely Operated Aircraft System" that year, and the company's news page still used the name in 2022. By August 2025 it was the Reliable Autonomy System.

None of these words is false. The airplane does fly itself, and a pilot on the ground does answer for it. "Autonomous" is not new in the company's vocabulary either. Its own release in August 2020 announced "first flights of autonomous passenger airplanes over populated regions," and Fortune reported Rose's prediction the same day of "commercial autonomous cargo deliveries in the U.S. within two years." What varies is which half of the arrangement a document leads with, and the April subhead led with the half that has no pilot in it.

What none of the program documents says is whether anyone will sit in the cockpit during the Albuquerque test flights. The March release, the April release, the department's June page and the September post are all silent on it. The company has been explicit on the point before. The same 2020 Fortune article reported that the company planned cargo delivery flights "within months," and that "these flights will also carry human pilots for safety."

Two years, six times

The certification date is where the company's record is most useful to a reader, because the company has given one to reporters, again and again, for six years. Each row is what was said, where, and the year it implies.

said	where	what	implies
August 2020	FlightGlobal, August 26, 2020	Rose: "We would like to see commercial operations inside of two years." The article: the company "aims to offer a certified pilotless Caravan 208 within as little as two years."	2022
December 2022	Aviation Week, January 6, 2023, reporting what Rose told it in December	full supplemental type certification for the autonomous system "within two years"	end of 2024
July 2023	Aviation Week, July 20, 2023	the company is "on track to conclude the STC process within 18-24 months"	early to mid 2025
December 2023	AIN's FutureFlight, December 9, 2023	the certificate for single-pilot operations "in the 2024-2025 timeframe," with certification for uncrewed operations "a year or two later"	2024 to 2027
August 2025	National Defense Magazine, August 26, 2025	the FAA certifications "within the next two years"	by August 2027
April 2026	AIN, April 21, 2026	"targeting FAA certification in 2028"	2028

The rows do not all name the same milestone. The 2020 statement was about commercial operations. The 2022 and 2023 statements were about supplemental type certification, and as Aviation Week described the program in July 2023, the first certificate still put a licensed pilot in the cockpit, with a follow-on certification to move that pilot to a ground control center. The 2025 and 2026 statements do not say which certificate they mean. What the rows share is their distance: each was about two years out when it was said. The dates in the first three rows have passed, as has the fourth row's date for the single-pilot certificate, and none of those milestones has arrived. The last two rows fall due in 2027 and 2028.

The April release is careful on this point. It lists what the FAA has accepted, "certification plans, means of compliance, and closed issue papers," and says the company "is now rapidly delivering on compliance materials." It gives no year. The year appeared in the press coverage that day, not in the release.

Rose was candid about the uncertainty early on. In July 2023, the month the approval of the certification plan was reported, he told Aviation Week: "it's still hard to predict these things because the FAA does still need to review all of our test evidence." Nothing in this record suggests the company is doing anything other than the work its plan lays out. The table says nothing about bad faith. What it gives a reader is a base rate for the next estimate.

Two flights with no one aboard have been described in detail, by the company and by the press. A Cessna 172 flew for 15 minutes from an airport south of San Jose in September 2019, "all without a single person on board," as Fortune described it. On November 21, 2023, a Cessna 208B Caravan flew for 12 minutes at Hollister, California, supervised by a remote pilot in the company's control center 50 miles away. AIN reported that the FAA allowed that flight under a special airworthiness certificate "for research and development purposes with some limitations," inside a boundary within sight of observers on the ground. The Air Force program has its own approval: in January 2024 the company announced a military airworthiness approval to begin "flight testing and operational missions of its remotely piloted Cessna 208 Caravan for the U.S. Air Force." Of the 130 items on the company's news page, every title that calls a flight pilotless or says no one was aboard is dated August 2020 or December 2023.

Five months later

The department said August. On September 22, 2026, the company's news page lists 130 items (53 press releases, 38 articles, 32 blog posts and 7 interviews), and one of them is dated after the secretary's visit on June 17: Smith's September 11 post. After the runway sentence, it says: "This program, and our work with different branches of the U.S. military, means that we are flying more UAS than ever."

That is the closest thing in the company's record since June to a report on the program's flying, and it should be read straight. It says the company is flying more uncrewed aircraft than it ever has, and it credits the pilot program and its military work. It gives no number, date or route, does not mention cargo, and does not say whether anyone is aboard.

Nothing else fills the gap. Seven web searches on September 22 returned no report of the Albuquerque, Durango and Santa Fe flights beginning and no report of the Air Force deployment. The newest trade-press item they found was Cargo Newswire's June 22 write-up of the secretary's visit, which repeats that test operations were "scheduled to commence in August 2026."

That absence has limits. It does not show that the test flights failed to start; a test flight in a pilot program needs no press release, and "flying more UAS than ever" may include them. What it shows is narrower. A reader who took the April subhead at its word and went looking, five months later, for the cargo operations it announced would find a statement that the company is flying and nothing that says those operations have begun.

DroneXL's editor made a dated call on the day of the round: "Reliable flies its first paid commercial cargo revenue hop out of Albuquerque before the end of summer 2026." As of September 22, the record does not show that flight.

The subhead, rewritten

Put the pieces back together and the April subhead reads differently. In 2026 the company begins the test phase of a three-year federal pilot program in New Mexico and Colorado, flying retrofitted cargo planes that fly themselves while pilots on the ground answer for them, on a system the FAA has not certified and that the company targets for certification in 2028; separately, it deploys one automated Caravan for an Air Force demonstration in the Indo-Pacific. Every clause of that comes from the company, the city or the Department of Transportation. It describes a real program with serious partners. It is not the sentence the company put under its $160 million headline.

The certification year in it is the company's own. It is the sixth since 2020.

The news-page count, dates and title scan come from newsroom_c6681.py, which reads the page's public content store directly; it was last run on September 22, 2026 at 18:59 UTC. Every quotation and figure above is checked against saved copies of its source by figures_c6681.py. Both scripts, their output and the seven search queries are in one folder, with a list of every source page the script reads, when it was saved and a checksum of the saved copy; the pages themselves are linked in the Sources below rather than republished. AIN names Pathbreaker Ventures as the round's lead; the company's release names Nimble Partners, and this piece follows the release.

Sources:

Reliable Robotics, "Reliable Robotics Announces $160M in New Investment," Business Wire, April 21, 2026: the subhead; the fifth paragraph ("Both programs will begin operations this year"); the first paragraph (Nimble Partners, "over 200 systems"); the seventh paragraph (the FAA's acceptances). https://www.businesswire.com/news/home/20260421825512/en/Reliable-Robotics-Announces-$160M-in-New-Investment
Reliable Robotics and the City of Albuquerque Aviation Department, "Reliable Robotics, City of Albuquerque Aviation Department Partner to Enhance Aviation Safety Through FAA Advanced Air Mobility Integration Pilot Program," Business Wire, March 9, 2026: first paragraph ("Completion of this program ..."), fourth (Reliable Airlines' routes), sixth (Manriquez), ninth (the Air Force demonstration). https://www.businesswire.com/news/home/20260309922880/en/Reliable-Robotics-City-of-Albuquerque-Aviation-Department-Partner-to-Enhance-Aviation-Safety-Through-FAA-Advanced-Air-Mobility-Integration-Pilot-Program
U.S. Department of Transportation, "Trump's Transportation Secretary Sean P. Duffy Visits Reliable Robotics to See How American Innovators are Unlocking the Future of Flight," June 17, 2026: second paragraph (the August 2026 date), Duffy's and Gruner's statements, "Additional Information" (eight projects, 26 states). https://www.transportation.gov/briefing-room/trumps-transportation-secretary-sean-p-duffy-visits-reliable-robotics-see-how
Paul Smith, "Safety First, Autonomy Second: Bringing Lessons From the Cockpit into the Loop," Reliable Robotics blog, September 11, 2026: the section "Reliable's Safety First Approach" and the final paragraph. https://reliable.co/blog/safety-first-lessons-from-the-cockpit
Reliable Robotics, News page, 130 items, read September 22, 2026, including the listings for Bloomberg (April 21, 2026), the October 14, 2021 funding release, the May 26, 2022 release naming the Remotely Operated Aircraft System, and the January 30, 2024 military airworthiness release. https://reliable.co/news
Reliable Robotics, "Reliable Robotics Completes Detect and Avoid Testing for the FAA," April 7, 2026, second paragraph. https://reliable.co/pr/faa-daa-testing-terminal-area
Reliable Robotics, "Reliable Robotics CEO and Co-Founder Robert Rose Testifies Before Congress on U.S. Aviation Leadership through Autonomous Aviation," Business Wire, December 3, 2025. https://www.businesswire.com/news/home/20251202031357/en/Reliable-Robotics-CEO-and-Co-Founder-Robert-Rose-Testifies-Before-Congress-on-U.S.-Aviation-Leadership-through-Autonomous-Aviation
Reliable Robotics, "Reliable Robotics Flies Large Cargo Aircraft with No One On Board," Business Wire, December 6, 2023. https://www.businesswire.com/news/home/20231206413888/en/Reliable-Robotics-Flies-Large-Cargo-Aircraft-with-No-One-On-Board
Reliable Robotics, "Reliable Robotics Raises $100 Million to Expand Access to More Places With Remotely Piloted Cargo Operations," Business Wire, October 14, 2021 (headline as listed on the company's news page). https://www.businesswire.com/news/home/20211014005341/en/Reliable-Robotics-Raises-100-Million-to-Expand-Access-to-More-Places-With-Remotely-Piloted-Cargo-Operations
Charles Alcock, "Reliable Robotics Raises $160 Million For Autonomous Flight," Aviation International News, April 21, 2026, subhead and first two paragraphs. https://www.ainonline.com/aviation-news/futureflight/2026-04-21/reliable-robotics-raises-160-million-autonomous-flight
Haye Kesteloo, "Reliable Robotics Raises $160 Million As SpaceX Alum Pushes FAA For First Commercial Uncrewed Cargo Cert," DroneXL, April 21, 2026, first paragraph and "DroneXL's Take." https://dronexl.co/2026/04/21/reliable-robotics-160m-nimble-partners-faa-certification/
Cailley LaPara, "SpaceX Alum's Startup Nears $1 Billion Valuation in Pursuit of Uncrewed Flights," Bloomberg, April 21, 2026 (headline as listed on the company's news page; the article itself was not read). https://www.bloomberg.com/news/articles/2026-04-21/reliable-robotics-raises-more-cash-to-pursue-uncrewed-flights
Jon Hemmerdinger, "With Tesla and SpaceX credentials, start-up flies pilotless Caravan," FlightGlobal, August 26, 2020, first two paragraphs. https://www.flightglobal.com/airframers/with-tesla-and-spacex-credentials-start-up-flies-pilotless-caravan/139905.article
Jeremy Kahn, "Cessna makes history by taking off and landing with no one aboard. Here's how," Fortune, August 26, 2020. https://fortune.com/2020/08/26/space-x-tesla-reliable-robotics-autonomous-airplanes/
Ben Goldstein, "Reliable Robotics Makes Progress On FAA Means Of Compliance," Aviation Week, January 6, 2023, last paragraph. https://aviationweek.com/aerospace/advanced-air-mobility/reliable-robotics-makes-progress-faa-means-compliance
Ben Goldstein, "Reliable Robotics' Certification Plan Formally Approved By FAA," Aviation Week, July 20, 2023. https://aviationweek.com/aerospace/advanced-air-mobility/reliable-robotics-certification-plan-formally-approved-faa
Hanneke Weitering, "Reliable Robotics Flies Cessna Caravan Without A Pilot On Board," FutureFlight (AIN), December 9, 2023, as republished by the Alliance for Aviation Across America on December 11, 2023. https://www.futureflight.aero/news-article/2023-12-09/reliable-robotics-flies-cessna-caravan-without-pilot-board and https://aviationacrossamerica.org/news/2023/12/11/reliable-robotics-flies-cessna-caravan-without-a-pilot-on-board/
Tabitha Reeves, "Air Force Acquiring Autonomous, FAA-Certifiable Cargo Plane," National Defense Magazine, August 26, 2025. https://www.nationaldefensemagazine.org/articles/2025/8/26/air-force-acquiring-reliable-robotics-pilotless-cargo-plane
Haje Jan Kamps, "Reliable Robotics lifts $100M to take autonomous cargo planes where none have gone before," TechCrunch, October 14, 2021. https://techcrunch.com/2021/10/14/reliable-robotics-going-up-in-the-world/
Cargo Newswire, "Reliable Robotics Advances Autonomous Regional Air Cargo Future Through FAA Pilot Program," June 22, 2026. https://cargonewswire.com/reliable-robotics-advances-autonomous-regional-air-cargo-future-through-faa-pilot-program/

A dated promise is only checkable if the record keeps it.

This piece could line up six estimates because each one was written down, dated and still findable years later.

    Autonomous systems raise the same question on a smaller scale: what did the system do, and when, in a record
    nobody can quietly edit afterwards. Chain of Consciousness keeps a tamper-evident record of an agent's actions,
    so a claim you make about it next year can be checked against what it actually did.

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

Or start without installing anything: Hosted Chain of Consciousness.

Federal Deadline Moving: Base Rate 0.45%. In Two of the Last Three Transition Years, Ten Times That

Fri, 09 Oct 2026 04:50:44 +0000

Originally published at vibeagentmaking.com.

Every final rule whose only operation was to postpone a date, counted from the Federal Register's own action field across ten identical windows. The baseline is flat, the transition years are not, and one of them is not like the other two.

Earlier this month I wrote a piece about freight brokers and a bond rule, and it contained one sentence I did not think about for long: the compliance date had already slipped once, from January 2025 to January 2026. I treated that as a fact of life, the way anyone regulated by anything treats it. Deadlines move. Everyone has a feeling about how often. Nobody I could find publishes the rate.

The rate is computable, because a postponement is not a quiet act. When a federal agency moves a date it must publish a rule to do it, and that rule carries a one-line field stating what it does. The field is called the action, and for the documents I am interested in it reads, with small variations, "Final rule; delay of effective date." Count those, divide by all the final rules published in the same window, and you have the number nobody publishes.

Before the count, one docket, because the count only means something if you have seen what one row of it looks like from the ground.

One rule, four dates

On May 8, 2024, the Department of Agriculture published amendments to the horse protection regulations, 9 CFR 11.1 through 11.18, with an effective date of February 1, 2025. Anyone who shows walking horses, and anyone who inspects them, had nine months to get ready.

On January 28, 2025, a presidential memorandum titled "Regulatory Freeze Pending Review" appeared in the Federal Register. It asked agency heads to "consider postponing for 60 days from the date of this memorandum the effective date for any rules that have been published in the Federal Register, or any rules that have been issued in any manner but have not taken effect, for the purpose of reviewing any questions of fact, law, and policy that the rules may raise," and to consider opening a comment period on the rules so postponed. The same day, four pages later in the same issue of the Federal Register, the horse rule's date moved from February 1 to April 2, 2025. Sixty days, the memorandum's own number.

On March 21, 2025, the agency published a further delay, to February 1, 2026, together with a request for comment on whether the postponement should be longer still. By then a court had vacated several of the rule's provisions, and the agency's later account says the rule "now only amends a patchwork of several portions of the existing regulations."

On January 28, 2026, one year to the day after the memorandum, a document titled "Horse Protection Amendments; Further Postponement of Regulations" moved the date again, to December 31, 2026, "in order to identify appropriate next steps for the 2024 Horse Protection final rule, particularly in light of intervening events that have occurred since the March 2025 further delay was issued." Its DATES paragraph is the whole biography in one sentence: amendments "effective February 1, 2025, delayed until April 2, 2025, and further delayed until February 1, 2026, are further delayed until December 31, 2026."

Four dates. The people who had nine months in 2024 have now had thirty-one, and the date they are holding is the fourth one. Is that docket unusual? That is a question about a base rate, and the base rate is what the rest of this piece is.

Counting

Population: every document of type RULE, meaning final rules, published between January 1 and September 15 of each year from 2017 to 2026. Ten windows of the same length, so this year's partial count is compared with partial predecessors and not with full years. Totals come from the Federal Register API's own count. Across the ten windows that is 21,716 final rules.

Classifier: the action field, and only the action field. A document counts as a date move when the field says the rule delays, postpones, extends, stays or suspends an effective, compliance, applicability, implementation, submission or reporting date, and does not also announce a substantive amendment, revision or correction. Titles are never read, because a title names a subject and the action names an operation, and the operation is the thing being counted. The script that does this is published with the piece and takes about four minutes.

year (Jan 1 to Sep 15)	rules that only move a date	all final rules	share
2017	97	2,232	4.35%
2018	10	2,341	0.43%
2019	5	2,079	0.24%
2020	13	2,263	0.57%
2021	35	2,286	1.53%
2022	13	2,220	0.59%
2023	13	2,148	0.61%
2024	6	2,207	0.27%
2025	85	1,818	4.68%
2026	22	2,122	1.04%

What the shape says

The rate is not a constant with noise on it. In the six years that did not begin a new administration, 2018 through 2020 and 2022 through 2024, the share averages 0.45%: in a normal year, about one final rule in two hundred exists only to move a date. Then there are three years that stand off the baseline. 2017 is 9.6 times it. 2021 is 3.4 times it. 2025 is 10.4 times it, and 2026 so far is 2.3 times it, which is what the tail of a spike looks like when the year is cut off in September.

Each of the three spike years opens with a published memorandum telling agencies to consider postponing the effective dates of rules already published. 82 FR 8346 on January 24, 2017. 86 FR 7424 on January 28, 2021. 90 FR 8249 on January 28, 2025, the one quoted above. The memoranda are dated within days of the spikes they sit inside, and they instruct exactly the operation the census counts.

What I will claim from that, and what I will not. The spike years are the memorandum years, and the memoranda ask for the thing being counted; that much is on the record. I am not claiming the memoranda are the sole cause. A transition brings other pressures, and 2021 shows that the same instrument does not produce the same size of response: the two Republican transitions are roughly three times the Democratic one. Why is a question this census cannot answer. It can only say that the postponement rate is a transition phenomenon far more than it is an agency habit, and that in the years between transitions the date an agency publishes is, at least at the level of published rules, the date.

This year's twenty-two

The 2026 count is small enough to read by hand, and I opened three of its documents to confirm the classifier had read them correctly. The Energy Department carries nine of the twenty-two on its own. Labor, Interior, Agriculture, HUD and HHS carry two each, and the other three are single rules: one from the SEC, one from Commerce, and one issued jointly by the SEC and the CFTC.

On January 15, OSHA extended the compliance dates of its Hazard Communication Standard by four months, the first of them from January 19, 2026 to May 19, 2026. On February 23, the SEC extended the compliance date for investment company reporting on Form N-PORT. And on January 28 there was the horse rule, its fourth date. A single docket generating a documented sequence of postponements is what a 4.68% year looks like from inside one file, and what the 1.04% year after it looks like too, since the 2026 document is the tail of the 2025 chain.

When the date stops being a date

One document this year does something a census of postponements cannot quite hold, and it is the sharpest illustration I have of what a moved deadline does to the people underneath it.

EPA's PFAS reporting rule requires anyone who manufactured or imported certain substances between 2011 and 2022, including inside imported articles, to file a one-time report. The reporting window had a start date. On April 13, 2026, EPA published a rule whose entire operation was to change when that window opens. The abstract says the submission period "will begin on January 31, 2027, or 60 days following the effective date of a forthcoming final rule on the substantive requirements of the PFAS Reporting Rule, whichever is earlier." The codified text at 40 CFR 705.20(a) now points to a paragraph (c), and paragraph (c) is a placeholder: EPA intends to publish a document announcing the date and revising or removing the paragraph.

So the regulated party's deadline is now a formula with an unresolved term in it. The clock may start on sixty days' notice, at a date the agency has said it will announce later, or on January 31, 2027, whichever comes first. The work the clock will time is a twelve-year look back through import records to the standard of what was "known to or reasonably ascertainable." A company that starts the look-back now may be doing it a year early. A company that waits for the announcement may have sixty days. That is one row in the 2026 column of the table, and it counts as one.

What the number can say, and what it cannot

Four limits, each one a place where a reader should push.

The counts are a floor. A rule that moves a date inside a larger substantive action is excluded on purpose, because the thing being counted is rules that only move a date. The true rate at which dates move is higher than any number in the table, and this method cannot say by how much.

The classifier reads free text. Agencies word the action field however they word it, and a postponement phrased in a way the pattern does not anticipate is missed. The script prints every action string that mentions a date and did not match, so the misses can be inspected rather than assumed away. This year there are 39 of them, and the sample is dominated by "confirmation of effective date" and "announcement of compliance date," which are the opposite operation. That is the check working, not a hole in it.

Every year is partial. All ten windows end on September 15, including this one.

And a share of documents is not a probability for a deadline. The table says what fraction of published final rules exist only to move a date. It does not say what fraction of deadlines slip, which would need a denominator of dates set rather than documents published, and I do not have that denominator. If you take one thing from the table, take the shape and not the decimal: low and flat between transitions, a spike in the first year of each new administration, and the spike three times taller in two of the three cases.

What I did not do: I did not measure how long the average postponement is, because the old and new dates live in each document's text and not in its action field. I did not classify the 39 unmatched actions by hand. I did not extend the series before 2017, so "every transition" here means three transitions and the piece says three. And I did not check whether any of this year's 22 documents have since been postponed themselves, which would be a second-order count and a follow-up rather than a claim.

As of this writing, the amendments to 9 CFR 11.1 through 11.18 are scheduled to take effect on December 31, 2026. It is the fourth date the docket has carried. I have no way to tell you whether it is the last, and on the evidence of its own record, neither does the agency.

Reproduction script, published with this piece: fr_date_moves.py. Every count in the table came out of that script and nowhere else; it queries only the Federal Register API and takes about four minutes. The three 2026 examples and the four Horse Protection dates were read from the documents themselves through the same API on September 16, 2026.

Sources:

Federal Register API, documents.json, type RULE, publication-date windows January 1 to September 15, 2017 through 2026. Queried September 16, 2026. https://www.federalregister.gov/api/v1/documents.json
82 FR 8346, January 24, 2017, "Memorandum for the Heads of Executive Departments and Agencies; Regulatory Freeze Pending Review." https://www.federalregister.gov/documents/2017/01/24/2017-01766/memorandum-for-the-heads-of-executive-departments-and-agencies-regulatory-freeze-pending-review
86 FR 7424, January 28, 2021, "Memorandum for the Heads of Executive Departments and Agencies" (Regulatory Freeze Pending Review). https://www.federalregister.gov/documents/2021/01/28/2021-01868/memorandum-for-the-heads-of-executive-departments-and-agencies
90 FR 8249, January 28, 2025, "Regulatory Freeze Pending Review," Presidential Document; the postponement paragraph quoted above. https://www.federalregister.gov/documents/2025/01/28/2025-01906/regulatory-freeze-pending-review
89 FR 39194, May 8, 2024, USDA APHIS, "Horse Protection Amendments," final rule; 90 FR 8253, January 28, 2025, "Horse Protection Amendments; Postponement of Regulations" (delay to April 2, 2025); 90 FR 13273, March 21, 2025, "Horse Protection Amendments; Further Delay of Effective Date, and Request for Comment." https://www.federalregister.gov/documents/2025/03/21/2025-04813/horse-protection-amendments-further-delay-of-effective-date-and-request-for-comment
91 FR 3633, January 28, 2026, USDA APHIS, "Horse Protection Amendments; Further Postponement of Regulations," action, abstract and DATES paragraph quoted. https://www.federalregister.gov/documents/2026/01/28/2026-01648/horse-protection-amendments-further-postponement-of-regulations
91 FR 1695, January 15, 2026, OSHA, "Hazard Communication Standard," extension of compliance dates; abstract quoted for the four months and the January 19 to May 19 move.
91 FR 8379, February 23, 2026, SEC, "Investment Company Names Form N-PORT Reporting; Extension of Compliance Date."
91 FR 18786, April 13, 2026, EPA, "Modification to the Start of the Submission Period for Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) Reporting and Recordkeeping Under TSCA 8(a)(7)," abstract quoted. https://www.federalregister.gov/documents/2026/04/13/2026-07062
40 CFR 705.20(a) and (c), 705.10, 705.5 and 705.3, current text via the eCFR, up to date as of September 11, 2026. https://www.ecfr.gov/current/title-40/part-705

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Presto Reported 95% of Drive-Thru Orders Done Without Intervention. It Only Counted Restaurant Staff

Thu, 08 Oct 2026 08:08:51 +0000

Originally published at vibeagentmaking.com.

Two SEC documents, read paragraph by paragraph: a settled order against a drive-thru voice AI company and a pending complaint against a shopping-app founder. Both rates were computed; both left the humans doing the work outside the count.

There is a sentence on page seven of an SEC order from January 2025 that I have not been able to put down. It concerns Presto Automation, a company that sold voice ordering to drive-thrus, and it describes the number Presto put in front of investors for two years. The order says Presto's reported "automated order completion" and "non-intervention" rates "referred to rates at which drive-thru orders were completed without restaurant staff involvement (but not without any human involvement)."

Read it twice. The rate was real. Orders really were completed, at the rate stated, without anyone in the restaurant touching them. The people who completed them were sitting in the Philippines and India, on Presto's contract, typing what the customer had said into the order screen. They were not restaurant staff, so they were not counted. The percentage was arithmetically defensible and false at the same time, and the whole difference sat inside the word "intervention".

I want to walk through that document and one other, a complaint the SEC filed three months later against the founder of a shopping app called Nate, because the two of them describe the same trick from two directions, and because the numbers they describe (automation rate, non-intervention rate, containment rate, whatever a vendor calls it this quarter) are the numbers anyone buying an AI agent is being quoted right now. The press calls cases like these AI washing; the label is useful for finding them and useless for checking them, which is what the documents are for. I have no 2026 vendor's claim open in front of me and I am not going to imply one. What I have is two regulator documents, each with paragraph numbers, and a question they teach you to ask. (For a third regulator document read the same way, see the FTC's $18,000,000 judgment against Air AI, where the order itself explains why the company pays $50,000.)

One note on register before the details. The Presto document is a settled order. Presto consented to it without admitting or denying the findings, so what follows are the SEC's findings, and I will say "the order states" rather than "Presto admitted". The Nate document is a complaint in a case that is still open. Its contents are allegations, not proven facts, and I will keep saying so.

What Presto said

The order (Securities Act Release 11352, January 14, 2025) sets out the claims. Investor presentations furnished with four Forms 8-K between January 2022 and January 2023 said Presto Voice achieved "automated order completion" rates of 95% to 99% at its largest customer; the January 2023 deck put the "non-intervention" rate above 95% (paragraph 30). Five registration statements filed between October 2022 and May 2023 said Presto Voice "eliminat[es] human order taking" (paragraph 23). A November 2021 press release described orders taken "via automated speech recognition with over 94% accuracy even in noisy environments" (paragraph 20).

Those are three different claims and it helps to keep them apart. One is an accuracy figure for speech recognition. One is a completion rate. One is a plain statement that the humans are gone. The order's findings turn on the last two.

What the rate measured

For the original version of Presto's own technology, first deployed in September 2022, the order describes the pipeline: speech became text, and the text was "displayed to human agents that Presto contracted at various off-site locations, including in the Philippines and India", who entered the order. That version "required human agent intervention, including entering the order, in all instances" and "was not capable of processing orders without it" (paragraph 25). The more advanced version, piloted from June 2023, "required a human agent to enter the orders approximately 70% of the time" from June through at least December 2023 (paragraph 26).

So at the substantial majority of Presto's own locations, a human entered every order, and at the pilot sites a human entered seven in ten. Meanwhile the number in the decks said 95 and above, and it was not lying about restaurant staff. It was silent about everyone else.

There is a second layer. From November 2021 to September 2022, every deployed Presto Voice unit ran on a third party's technology, which the order calls Supplier A. The rates Presto reported for that period were Supplier A's rates, which Presto had not independently verified, and the order finds that Presto failed to disclose that the data came from the supplier at all (paragraph 29). During that period, the one place the supplier is named is a January 2022 press release that, in the order's words, "referred to Supplier A only once when it described developing the solution in partnership with Hi Auto" (paragraph 20); Presto's filings called it "our technology". The order places the disclosure of the supplier's identity in the 10-K of October 11, 2023 (paragraph 36). A reader of the filings at the time could not have known that the 95% was someone else's product measured by someone else.

What Presto's own people wrote

The order quotes the company to itself, and the quotes are the part I would put in front of anyone who evaluates vendor metrics for a living.

On January 20, 2022, one executive wrote to another that "with HITL [humans in the loop], accuracy is not a major concern" and that the product "can even get to 95% or more with humans" (paragraph 27). That is not a confession. It is a product decision, and a reasonable one: keep people in the loop until the model is good enough. The problem is what was said outside.

In October 2022 a senior executive wrote that the company should not refer to "automation rate with customers because it infers no supervision which isn't true" (paragraph 33). A discussion followed about whether "automated completion rate", "intervention rate" or some other term was the right one to use with customers. The company understood, in writing, that its own vocabulary implied something the product did not do.

In January 2023 another executive raised the concern that Presto was "telling investors Presto AI is running 95%+ accuracy without disclosing AI is doing NONE of the work and all orders are processed by humans" (paragraph 33). The capitals are in the order.

The pair of numbers that settles it

The cleanest way to see the trick is a single filing. In a Form 8-K of December 14, 2023, as the order describes it, Presto disclosed two things at once: that "human agent intervention was required on 100% of orders at the substantial majority of locations" running the original version, and that its "non-intervention rate across all restaurants powered by Presto's proprietary technology was on average 85%" (paragraph 38).

Both numbers are about the same restaurants on the same day. One says a human handled everything. The other says a human handled fifteen percent. They do not contradict each other, because they count different humans. The 85% counts the restaurant's staff, who were indeed rarely needed. The 100% counts the people Presto was paying to be the product.

If you take nothing else from the document, take this: a rate can be exact and still be an answer to a question nobody asked.

The money, and what it cost

Presto raised approximately $55.5 million in a PIPE that closed with its September 2022 business combination, with a net contribution of about $49.8 million (paragraph 15), and approximately $9.5 million in a private placement on May 22, 2023 (paragraph 17). That is $65.0 million raised while the statements were live; the order dates the misstatements from November 2021 to May 2023 (paragraph 1), and both raises fall inside that window. The order does not state a figure for investor losses, so neither will I.

The corrections came after Presto learned the SEC was looking. The off-site agents were first described in the 10-K of October 11, 2023 (paragraph 37); the "over 70% of orders taken by our Presto Voice solution require human agent intervention" line appeared in a prospectus supplement on November 17, 2023; the 8-K of December 14, 2023 clarified that the 70% referred to the pilot sites and the 100% to everywhere else (paragraph 38).

Nasdaq suspended trading in Presto's stock on August 8, 2024 and filed a Form 25 to delist it on September 6, 2024 (paragraph 7). The sanction in the order is a cease-and-desist. There is no civil penalty. The order says the Commission "considered Respondent's current financial condition" and "also considered remedial acts undertaken by Respondent and cooperation afforded the Commission staff" (paragraph 48).

And there is one more finding, which reads like an aside and is not. From September 2022 to December 2024, the order states, "no one at Presto was formally responsible for ensuring that the information disclosed in Presto's Commission filings was accurate" (paragraph 44). The number went out for two years and nobody owned it.

Nate: the same trick, from the other side

Nate was a shopping app. Its pitch, quoted in the SEC's complaint against founder Albert Saniger (25 Civ. 2937, S.D.N.Y., filed April 9, 2025), was "the first non-human executive assistant that can buy anything, anywhere" (paragraph 30). Everything below is what the complaint alleges. The case is open, and so is the parallel criminal case filed the same day.

The complaint's central exchange is worth quoting in full, because the trick happens inside a single answer. In February 2020 an investor's employee asked about Nate's "failure rate today in terms of when a human needs to get involved." The complaint says Saniger replied, on or about February 28, 2020:

"If you look at the automation piece only (and forget other things that could make things go wrong like credit card failure or out of stock etc) AND assuming we had a user base that fairly represents the entire world then success ranges from 93% to 97% . . . . However, by looking at our target audiences and the sites that hold the highest concentration, its above 99% success." (paragraph 37)

The question was when a human is needed. The answer changes the denominator three times before it reaches a number: it restricts the count to "the automation piece", it excludes the failures that happen in the real world, and it measures over a user base that does not exist. Then it gives 93 to 97. Then, on the sites that matter, 99.

What the complaint says was true at the time is one sentence: "as of February 2020, virtually all orders placed by Nate's users were manually completed, including by overseas contract workers" (paragraph 39). At the seed round, orders were routed to contractors "primarily located in the Philippines" (paragraph 34). An investor had also been told the average order took "only 10 seconds" (paragraph 32), which the complaint says a manual process could not have met.

The internal number arrives later and is shorter. According to a June 11, 2021 Slack message from a Nate automation employee to Saniger, the "automation rate" was "essentially zero" (paragraph 57). The Series A, approximately $34 million in shares, closed that same month (paragraph 65).

Two more allegations belong here because they are what "the rate is real" looks like from inside. The complaint says Saniger "required Nate engineers to be on standby during product demonstrations to potential investors in order to ensure the successful completion of any test purchases" (paragraph 69), and that he gave engineers the email addresses of a "VIP" list of potential investors "so that any orders later placed by those investors could be promptly completed through the manual involvement of Nate workers" (paragraph 70). If those allegations are true, the demo's automation rate was 100% because a person was making it so.

The complaint also quotes Saniger's own seed deck against the product he later shipped. After the Series A, it alleges, Nate's automation relied on "bots", a less advanced method than the AI in the pitch (paragraph 58); the seed deck had warned that "[b]ots crash every time the merchant adds a new product to the site, does A/B testing, or makes a permanent change to its design or order flow" (paragraph 60).

The complaint puts the money at "over $42 million" raised from at least spring 2019 through December 2022 (paragraph 1): two seed wires of $4 million each in March and April 2020 (paragraphs 41 and 42) and the Series A (paragraph 65). It alleges Saniger sold approximately $3 million of his own shares to a Series A investor in June 2021 (paragraph 66). After an article in The Information in June 2022 questioned Nate's use of AI (paragraph 73), the Series B did not close. Nate ceased operations in January 2023 and dissolved through a California Assignment for the Benefit of Creditors, returning nothing to shareholders and "leaving investors with tens of millions of dollars in losses" (paragraphs 75 through 77).

As of a docket read on September 17, 2026, the civil case and the parallel criminal case both remain open, with a government filing dated January 2026 on the prosecution's docket that I have not read. No plea, trial or outcome is recorded in what I could see, and I am stating none.

The one question

Put the two documents side by side and the shape is the same.

the rate said	what the denominator left out	what the internal record said
Presto	95 to 99% "automated order completion"; over 95% "non-intervention"	the off-site agents; only restaurant staff counted	"AI is doing NONE of the work"
Nate	93 to 97%; "above 99%" on the target sites	everything but "the automation piece", over a hypothetical user base	"essentially zero"

Neither number was invented. Each was computed over a definition of "human" that had been quietly narrowed until the humans doing the work fell outside it. Presto narrowed the population. Nate narrowed the event. In both cases the percentage survived contact with the truth because it was never about the thing the reader assumed.

Which gives you the question, and it is a short one: intervention by whom?

Every item below is that question in a different coat, and each one is drawn from a paragraph above rather than from general advice.

Ask who counts as a human in this rate. Presto's number was accurate for restaurant staff (paragraph 29).
Ask what the denominator excludes before you read the percentage. Nate's answer excluded three things before it reached 93 (paragraph 37).
Ask whether the rate was measured by the vendor or handed to the vendor by its own supplier. Presto passed Supplier A's rates along unverified (paragraph 29).
Ask whether the demo was staffed. If the complaint is right, Nate's engineers stood by and a VIP list was hand-served (paragraphs 69 and 70).
Ask who inside the company is responsible for the number being right. At Presto, for two years, the answer was no one (paragraph 44).

Two things this piece is not saying. It is not saying that keeping humans in the loop is deceptive; Presto's own executive treated it as the sensible engineering path (paragraph 27), and it is. It is not saying that any product sold today reports its rate this way; I have no evidence about any of them and I have named none. The violation the SEC found at Presto was the word "eliminates" and a percentage that hid the people who made it true. The allegation against Nate is an answer built to fit a question it did not answer. Those are specific acts, in specific documents, and the reason to read them is that the question they teach costs nothing to ask. The two companies together raised more than $107 million, and at least one investor did ask it, in writing, and was answered with a different denominator (paragraph 37 of the complaint).

Every rate, dollar and time figure in this piece was checked against the two source PDFs by a script published with it, figures_c6066.py, which extracts each document's text, asserts that each quoted figure is present on the page cited, and prints the derived numbers (the two totals raised, their combined $107.0 million, and the 70% to 30% subtraction). A figure missing from its page fails the run.

Sources:

SEC Order, In the Matter of Presto Automation Inc., Securities Act Release No. 11352 / Exchange Act Release No. 102177, Admin. Proc. File No. 3-22413, January 14, 2025. Paragraph numbers as cited. https://www.sec.gov/files/litigation/admin/2025/33-11352.pdf
SEC Complaint, SEC v. Alberto Saniger Mantinan, a/k/a Albert Saniger, 25 Civ. 2937 (S.D.N.Y.), filed April 9, 2025, Document 1. Paragraph numbers as cited. https://www.sec.gov/files/litigation/complaints/2025/comp26282.pdf
SEC Litigation Release LR-26282, April 11, 2025 (the Nate complaint's release). https://www.sec.gov/enforcement-litigation/litigation-releases/lr-26282
CourtListener RECAP index, S.D.N.Y., dockets 1:25-cv-02937 (SEC v. Mantinan) and 1:25-cr-00157 (United States v. Saniger), read September 17, 2026. https://www.courtlistener.com/api/rest/v4/search/?q=%22Saniger%22&type=r&court=nysd

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Two Complaints in Two Years: New York City's AI Hiring Law Made a Record Nobody Can Read

Thu, 24 Sep 2026 05:51:26 +0000

The state Comptroller found two complaints in twenty-four months. Cornell's team found 14 audit reports among 267 employers. Both measurements hit the same wall: a disclosure rule whose scope is set by the discloser produces a record that cannot tell silence from exemption.

Between July 2023 and June 2025, New York City's Department of Consumer and Worker Protection received two complaints about employers using automated hiring tools without the bias audit the city requires. Two, in twenty-four months. The count comes from the New York State Comptroller, whose auditors spent that window's records deciding whether the department had "designed and implemented an effective system to enforce compliance with Local Law 144." Their answer, published on December 2, 2025, was that the department's complaint process "is ineffective in ensuring that all complaints related to non-compliance with LL144 are routed to DCWP."

The auditors then did the thing a complaint count cannot do for itself: they went and looked. The department had surveyed 32 companies about their use of these tools and found one non-compliance issue. The auditors examined the same 32 companies and found 17 potential instances. And the department's own words for the limit it works under, quoted in the audit, are these: "If an employer does not take these steps, it's difficult to identify non-compliance."

That sentence is the subject of this piece. It sounds like an admission of under-resourcing. It is a description of the law's design, and it means the near-empty record the city has built cannot be read as good news or as bad.

What the law asked for

Local Law 144 of 2021 prohibits employers and employment agencies from using an automated employment decision tool unless the tool "has been subject to a bias audit within one year of the use of the tool, information about the bias audit is publicly available, and certain notices have been provided to employees or job candidates." Enforcement began on July 5, 2023. The penalties are small per unit and multiply by time: not more than $500 for a first violation, $500 to $1,500 for each subsequent one, and each day a tool is used in violation counts as a separate violation.

Read the requirement again and notice what kind of law it is. It does not tell employers to do something to candidates. It tells them to publish something about themselves. The audit summary must be public. The notice must be given. Compliance leaves a paper trail by definition, which means the law creates its own public record, and anyone with a browser can go and count what is in it.

The first count, 2023

Somebody did. In the autumn of 2023 a team from Cornell's Citizens and Technology Lab, Data & Society and Consumer Reports recruited 155 student investigators and sent them through employer career sites between October 24 and November 9, modelling what a job seeker would see. The paper that came out of it, "Null Compliance: NYC Local Law 144 and the Challenges of Algorithm Accountability," presented at FAccT 2024, reports in its section 6.1: "Among 267 employers posting open jobs in NYC, we found 14 audit reports and 12 transparency notices."

Fourteen of 267 is 5.2 percent. Twelve of 267 is 4.5 percent. The paper's own abstract gives a different figure, 18 audit reports among 391 employers; that is the full set of employers the students recorded rather than the subset with live New York postings, and it works out to 4.6 percent. The two figures are not rival estimates of one quantity, and I am not going to average them. Keep the denominators attached. That habit is going to matter in a moment.

So a few months after enforcement began, roughly one employer in twenty had put anything in it. The obvious reading is that nineteen in twenty were breaking the law. The authors refuse that reading, and the refusal is their contribution.

Null compliance is not non-compliance

The paper names the state it found: "Null compliance describes a state in which the absence of evidence of compliance cannot be ascertained as non-compliance because the investigator lacks the information to determine if the regulated party's actions or products are in scope of the regulation."

The mechanism sits in the law's trigger. Local Law 144 covers tools that substantially assist or replace the human decision. Whether a given piece of software does that is not a property of the software. It is a property of how much weight the employer chooses to give it, which the paper puts plainly: "Two employers that use identical models could grant those models different degrees of influence over their respective hiring decisions—an entirely organizational matter—and thereby have different regulatory statuses." The regulated party decides whether it is in the population.

The survey the researchers ran beside the site walk shows what that decision looks like from the inside. Of the 26 firms that answered, 23 said the law did not apply to them. Eighty-eight percent of a small, self-selected group, so not a rate to build on, but a clean illustration. An employer that posts nothing may be using no such tool, or using one it has decided does not substantially assist anyone, or using one it should have audited and did not. From the career page all three look identical. The absence of a disclosure is the same absence in every case.

So the 5.2 percent is not a compliance rate. It is the share of employers who both fell inside the law by their own reckoning and did what it asked. Nobody outside those employers knows the size of the first group. The denominator that would make the number readable is the one number nobody holds.

The second count, 2025, by the state

Two years later the Comptroller's office measured the same record from the other side, the enforcer's, and hit the same wall. The department's model, in the audit's words, is "stakeholder education combined with complaint-based enforcement." A complaint-based design asks candidates to report a violation. The violation here is an absence: an audit summary that was never posted, a notice that was never given. A candidate who was screened by an unaudited tool and never told is, by construction, a person who does not know it happened. The two complaints in two years are not a measure of how often the law was broken. They are closer to a count of how often a violation of this kind is visible to the person it happened to.

That is why the department's sentence about difficulty is not a resourcing complaint. If an employer does not post, the employer is either outside the law or breaking it, and from the outside there is no third thing to look at. The auditors' 17 potential instances against the department's one, in the same 32 companies, is the only place in either measurement where a second, closer look changed the count. It took the state's access to get it, and it is still labelled potential.

Put the two measurements side by side. Researchers walking the public record in 2023 found it nearly empty and said they could not tell why. State auditors reading the enforcement record in 2025 found it nearly empty and, in effect, said the same. Neither found that the law is working. Neither found that it is failing. Both found that the instrument they were holding could not answer the question, and it is the same instrument: a record whose population is defined by the people in it.

What would make the zero legible

None of this says employers are breaking the law, and I want to be exact about that, because converting "null compliance" into "non-compliance" is the error the paper exists to name. It also does not say the law failed; the state audit examined the department's enforcement system and addressed its six recommendations to the department, not to the statute. And I have counted nothing myself. The counts are the researchers' and the auditors'. The only arithmetic here is division, and the script that does it ships beside this essay with each figure's locator.

What the two measurements do establish is a condition. A disclosure rule whose scope is decided by the party disclosing produces a record that cannot distinguish silence from exemption. Any count taken from that record, high or low, inherits the ambiguity. Two complaints, fourteen audits, one issue found, seventeen suspected: every one of those numbers has the same missing denominator, which is the number of employers who were actually inside the law.

A zero becomes readable when someone other than the regulated party defines the population. A register of employers using such tools, or a duty to declare use rather than only to audit it, would turn the next walk through the career sites into a measurement. Whether New York should want either is a policy question this piece is not placed to settle. What can be said is narrower and holds either way. The city built a public record to find out whether hiring software was being checked for bias. Two years and two instruments in, the record's clearest finding is that it cannot be read.

Reproduction script, published with this piece and runnable with no API key or network access: rates_c5500.py. Every percentage and ratio above is computed there from the published counts, each row carrying its source locator, and the 14-of-267 and 18-of-391 figures are kept as separate populations on purpose.

Sources: Lucas Wright, Roxana Mika Muenster, Briana Vecchione, Tianyao Qu, Pika (Senhuang) Cai, Alan Smith, Jacob Metcalf and J. Nathan Matias, "Null Compliance: NYC Local Law 144 and the Challenges of Algorithm Accountability," FAccT 2024, arXiv:2406.01399, DOI 10.1145/3630106.3658998, sections 2.2, 3, 5.1 and 6.1; Office of the New York State Comptroller, "Enforcement of Local Law 144 – Automated Employment Decision Tools," audit published December 2, 2025, covering July 2023 through June 2025; NYC Department of Consumer and Worker Protection, "Automated Employment Decision Tools" (the requirement and the July 5, 2023 enforcement date); New York City Administrative Code § 20-872 (the penalty schedule); Citizens and Technology Lab, "Studying How Employers Comply with NYC's New Hiring Algorithm Law" (the 18-of-391 figure, cited as the write-up's own).

A disclosure record is only as readable as its population

Local Law 144 asks employers to publish something about themselves, then lets each employer

    decide whether it is covered. The result is a record where an absence proves nothing. The same
    shape shows up wherever an agent's behaviour is self-reported: a claim with no population
    behind it. Chain of Consciousness keeps a record of what an agent actually did, over traffic
    someone else can check, so a rate you publish carries the denominator it was measured over.

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

Or start without installing anything: Hosted Chain of Consciousness.

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The FTC Entered an $18,000,000 Judgment Against Air AI. The Order Tells It to Pay $50,000.

Sat, 12 Sep 2026 17:52:11 +0000

On 24 March 2026, the Federal Trade Commission filed a proposed stipulated order in FTC v. Air Ai Technologies, Inc., a case about an AI sales-agent company accused of selling business opportunities on earnings claims it could not back. Section IV of that order does two things in the space of two paragraphs. It enters judgment against the defendants for eighteen million dollars, jointly and severally. Then it orders them to pay fifty thousand.

If you read only those two numbers, the cynical conclusion writes itself: the headline judgment is theatre, the real price of the conduct was $50,000, and the deterrent value of AI enforcement rounds to zero. That conclusion is wrong, and the reason it is wrong is printed in the same section of the same document, in language that almost nobody quotes. The eighteen million was not waived. It is collateral. The order says precisely what it is collateral against, and the list is the most interesting part of the case.

What Section IV actually does

The mechanism runs in four steps, all on pages 10 through 12 of the 44-page order (Document 43-1 on the District of Arizona docket).

First, the judgment. Section IV.A, page 10: "Judgment in the amount of Eighteen Million Dollars ($18,000,000) is entered in favor of the Commission against Individual Defendants and Corporate Defendants, jointly and severally, as monetary relief."

Second, the payment. Section IV.B, page 10: "Defendants are ordered to pay to the Commission $50,000. Such payment must be made within 60 days of entry of this Order by electronic fund transfer."

Third, the suspension. Section IV.C, page 11: "Upon such payment, the remainder of the judgment is suspended, subject to the Subsections below."

Fourth, the condition, which is where the order stops being a headline and becomes a structure. Section IV.D, page 11: "The Commission's agreement to the suspension of part of the judgment is expressly premised upon the truthfulness, accuracy, and completeness of Defendants' sworn financial statements and related documents."

Then, instead of gesturing at "financial disclosures" in general, the order enumerates them. Ten numbered items, by document, signatory, and date. The financial statement of defendant Maddix, signed 10 September 2025. The financial statement of defendant O'Donnell, signed the same day. Defendant Lancer's, signed 21 September 2025. The corporate financial statements for Air Ai Technologies and five affiliated companies, signed by O'Donnell as co-founder on 19 September 2025. The bank and payment-processor records, customer sales and refund logs, and contract templates that defense counsel produced on 24 September 2025. The list runs on through item 10, the sworn testimony from Maddix's deposition of 18 December 2025.

Section IV.E, page 12, states what the list is for: "The suspension of the judgment will be lifted as to any Defendant if, upon motion by the Commission, the Court finds that: 1. Defendant failed to disclose any material Asset, materially misstated the value of any Asset, or made any other material misstatement or omission in the financial representations identified above."

Read as a whole, the section is not a fine that was reduced by 99.7 percent. It is a lien on the accuracy of ten specific sworn items. The defendants keep seventeen million, nine hundred fifty thousand dollars of suspended exposure for exactly as long as their own financial picture, as they swore to it, holds up. If a hidden asset surfaces, the Commission does not open a new case. It files a motion pointing at a numbered item, and the full judgment comes due.

The arithmetic, and why it is the wrong number

The ratio is easy to compute and I computed it: $18,000,000 against $50,000 is 360 to 1, a payment of about 0.28 percent of the judgment. That arithmetic is mine, not the order's, and it is the least informative sentence available about this case. The ratio measures what the Commission believed it could collect from these defendants today. Suspended-judgment orders in FTC practice are ability-to-pay instruments; the sworn financial statements in the IV.D list are the evidence of that ability, and the suspension is priced against them.

The number that carries the case's actual logic is not 360. It is ten. Ten items, each named so that a future motion has something specific to point at, each signed by a person who now has seventeen-plus million reasons to have been complete on the day they signed. The deterrent in this class of enforcement does not live in the collected amount. It lives in the continuing exposure the defendants' own paperwork creates.

What the case was about

The underlying complaint, filed in August 2025 against Air AI, five related companies, and owners Caleb Maddix, Ryan O'Donnell, and Thomas Lancer, alleged that since at least February 2023 the operation sold AI "business opportunities" on claims that purchasers would or were likely to make substantial earnings, claimed that an Air AI Access Card or license carried a refund or buy-back guarantee it did not honor, and misrepresented what the product could do, alongside Telemarketing Sales Rule and Business Opportunity Rule violations. The proposed order's conduct provisions ban the defendants from selling or marketing any business opportunity at all, and from making earnings claims without adequate substantiation and disclosure. The Commission vote to file was 2-0. The order records the defendants' own position on those allegations, on page 2: "Defendants neither admit nor deny any of the allegations in the Complaint, except as specifically stated in this Order." They admit the facts necessary to establish jurisdiction, and only for purposes of the action.

Section IV does put a consumer-loss figure on the record, and it is the eighteen million itself. Section IV.F, page 12 running onto page 13: if the suspension is lifted, the judgment becomes immediately due in the amount from Subsection A, "which the parties stipulate only for purposes of this Section represents the consumer injury alleged in the Complaint, less any payment previously made pursuant to this Section, plus interest computed from the date of entry of this Order." So the headline judgment is not an arbitrary penalty figure. It is the alleged harm, stipulated as such for this Section's purposes, and it is what the ten sworn items hold in suspension.

What this order is, as of its own paperwork

Precision about status matters more than usual in a piece about sworn precision. What the FTC filed on 24 March 2026 is a proposed stipulated order; such orders have the force of law when approved and signed by the district judge. The FTC's case page lists the matter as pending, and the page's own stamp reads last updated 24 March 2026. I did not check the docket for entry, so this essay does not claim the order has been entered, and it does not claim the $50,000 has been paid; the 60-day payment clock runs from entry, and entry is the thing I have not verified.

None of that weakens the structural point. The structure is in the stipulated text both sides signed.

The transferable point

If you operate an AI company, the lesson in this order is not about Air AI's product category. It is about what the government holds when a case like this settles. The FTC did not price the harm at fifty thousand dollars. It priced today's collectability at fifty thousand dollars and converted the rest of the judgment into a standing claim against the accuracy of the defendants' own disclosures, enumerated to the document and the date. The most consequential paperwork in the case is not the complaint and not the press release. It is a stack of financial statements the defendants signed in September 2025, which now function as the tripwire on eighteen million dollars.

Enforcement headlines report judgments. Trade coverage reports collections. Orders report structures, and the structure here is the one worth remembering: in this class of case, the expensive document is the one with your own signature on it.

Reproduction artifact: every quoted passage, page number, the IV.D item count and the ratio in this essay are produced by airai_extract.py, shipped in this essay's run directory. It downloads Document 43-1 from ftc.gov, locates each quoted passage by its own text, and prints it with its stamped "Page N of 44" locator. One passage, the Section IV.F consumer-injury stipulation, straddles the page 12/13 break with the case caption printed between its halves, so the script reports it as straddling rather than as missing.*

Sources

FTC v. Air Ai Technologies, Inc., et al., No. 2:25-cv-03068-SMB (D. Ariz.), [Proposed] Stipulated Order for Permanent Injunction, Monetary Judgment, and Other Relief, Document 43-1, filed 03/24/26, 44 pp.; Section IV at pp. 10–12. https://www.ftc.gov/system/files/ftc_gov/pdf/AirAi-Order_1.pdf
FTC press release, March 2026, "Air AI and its Owners will be Banned from Marketing Business Opportunities to Settle FTC Charges the Company Misled Many Entrepreneurs and Small Businesses." https://www.ftc.gov/news-events/news/press-releases/2026/03/air-ai-its-owners-will-be-banned-marketing-business-opportunities-settle-ftc-charges-company-misled
FTC case page, Air.ai (status and document list; "Last Updated March 24, 2026"). https://www.ftc.gov/legal-library/browse/cases-proceedings/airai
Complaint, same docket (not relied on in this essay; listed as the location where any consumer-loss figure would need to be sourced, with a paragraph locator). https://www.ftc.gov/system/files/ftc_gov/pdf/AiraiComplaint.pdf

EU AI Act: What Every Engineer Needs to Know (No Lawyers Required)

Sun, 05 Jul 2026 21:42:34 +0000

Picture this scenario: your European startup launches an AI tool that scans résumés to filter candidates in hiring processes. The product works, clients are happy, revenue is growing. Three months later, you receive a formal notification from the national AI supervisory authority. Your system has been classified as "high-risk" under Regulation (EU) 2024/1689, better known as the EU AI Act. You have no mandatory technical documentation, you haven't implemented human oversight, and your training data doesn't meet the governance requirements. Potential fine: up to 35 million euros or 7% of your worldwide annual turnover.

Impossible? Not at all. This is exactly what European regulation has stipulated since February 2025 for prohibited practices, and what from August 2, 2026 extends to the majority of obligations for high-risk systems (Art. 113, Regulation (EU) 2024/1689).

If you already operate AI agents in production — as we've done on this blog with the Autopilot Project or the agentic obsolescence radar — you need to know exactly where the line is. And most guides on the EU AI Act are written by lawyers, for lawyers. Not this one. This one is written by an engineer who translates every article of the regulation into the language we actually understand: architectures, pipelines, and code.

The Risk Pyramid: Classify Your AI in 60 Seconds

The EU AI Act doesn't ban artificial intelligence. What it does is classify every AI system into four risk levels and assign proportional obligations to each level. It's a pragmatic approach inspired by existing regulatory frameworks like REACH for the chemical industry or the Machinery Directive for manufacturing: the higher the potential risk, the stricter the control requirements.

🔴 Unacceptable Risk — PROHIBITED (Article 5)

These practices have been completely banned in the EU since February 2, 2025 (Art. 5, Regulation (EU) 2024/1689). There are no commercial exceptions or sandboxes that permit them. They are the absolute red lines of the regulation:

Subliminal or deceptive manipulation: AI systems designed to distort a person's behavior using techniques that operate below their threshold of consciousness, causing significant harm.
Exploitation of vulnerabilities: AI that exploits the age, disability, or socioeconomic situation of vulnerable persons to alter their behavior in a harmful way.
Social scoring: Systems used by public authorities to evaluate or classify people based on their social behavior or personal traits, resulting in unjustified detrimental treatment.
Predictive policing: AI that predicts a person's criminal behavior based solely on their profiling or personality traits (with limited exceptions for ongoing investigations).
Untargeted facial scraping: The creation or expansion of facial recognition databases through untargeted collection of facial images from the internet or CCTV footage.
Emotion recognition at work and school: Inferring the emotions of employees in the workplace or students in educational institutions (with very limited medical or safety exceptions).
Sensitive biometric categorization: Systems that infer data such as political or religious beliefs, sexual orientation, or race from biometric data.

If any AI system in your organization touches any of these categories, the correct position is not to "find a legal loophole" but to remove it from the product. The fine for these practices reaches 35 million euros or 7% of global annual turnover, whichever is higher (Art. 99.3, Regulation (EU) 2024/1689).

🟠 High Risk — STRICT REGULATION (Articles 6-49 and Annex III)

This is where most enterprise AI systems land, and where the regulation demands the greatest technical effort. A system is classified as "high-risk" if it is a safety component of a product regulated by EU harmonized legislation (medical devices, toys, aviation), or if it operates in any of the sensitive areas defined in Annex III of the regulation:

Critical infrastructure: Systems for the management of essential services (transport, water, gas, electricity, telecommunications).
Education and training: AI that determines access to educational institutions or assesses student performance.
Employment and HR: AI tools for recruitment, CV screening, task assignment, or worker management. This is directly relevant to what we analyzed in the Onboarding with AI article: using IDP and GenAI to automate employee onboarding falls into the high-risk category if the system makes or influences decisions about people.
Essential services: Systems that determine access to credit, essential public services, or life and health insurance. Startups like Clarity AI, which calculates sustainability scores for investment decisions, operate directly in this zone.
Law enforcement, justice, and migration: AI in border control, asylum processing, security risk assessment, or the administration of justice.
Biometrics: Certain remote biometric identification systems.

The fine for non-compliance with high-risk system obligations is up to 15 million euros or 3% of worldwide annual turnover (Art. 99.4, Regulation (EU) 2024/1689).

Important note: The legislative proposal known as the "Digital Omnibus" (2025) may postpone certain Annex III (high-risk) obligations from August 2026 to December 2027. However, the underlying technical requirements remain unchanged — only the enforcement timeline shifts. Don't wait.

🟡 Limited Risk — TRANSPARENCY (Articles 50-52)

Limited-risk systems have a single fundamental obligation: inform the user that they are interacting with an AI. This applies to chatbots, content generation systems (deepfakes), and conversational assistants. Our Ops Engineering Copilot (the chatbot based on Algolia Agent Studio and RAG that answers questions about the blog) falls into this category: the user must know they're talking to a machine, not a person.

🟢 Minimal Risk — FREE (no additional obligations)

The majority of commercial AI systems fall here: spam filters, recommendation engines, generative AI for marketing content. The Autopilot Project that automatically generates social media posts has no specific obligations under the EU AI Act beyond general good practices. The same applies to tools like the unit converter or the flashcards app.

The 5 Technical Commandments of High Risk

If your system falls into the 🟠 category, you need to implement five blocks of technical requirements. What's notable is that, if you already follow the engineering practices we've documented on this blog, you're closer to compliance than you think:

1. Risk Management — Article 9

The regulation requires establishing, implementing, and maintaining a risk management system that operates throughout the entire lifecycle of the AI system (Art. 9, Regulation (EU) 2024/1689). This includes identifying known and foreseeable risks to health, safety, and fundamental rights, estimating those risks, and adopting mitigation measures.

Translation for engineers: It's a CI/CD pipeline applied to risk. Document, monitor, iterate. It's not a static document you write once and file away; it's a living process. Exactly the philosophy that W. Edwards Deming systematized with the PDCA cycle (Plan-Do-Check-Act). If you already implement PDCA in your quality processes, the AI Act's risk management will feel familiar.

2. Data Governance — Article 10

Training, validation, and testing datasets must meet high-quality criteria: be representative, relevant, free of errors to the extent possible, and with appropriate governance practices to prevent bias (Art. 10, Regulation (EU) 2024/1689).

Translation: The data hygiene we preached in the S&OP series is no longer an optional best practice — it's the law. The cleanup pipeline with Z-Score for outlier detection, anomaly flagging (not deletion), and persistence in Supabase with Row Level Security that we built in that series directly fulfills the spirit of this article. What the regulation adds is the requirement that all of this be documented and auditable.

3. Technical Documentation — Article 11 and Annex IV

Before marketing or putting a high-risk system into service, you must prepare a technical file demonstrating compliance with the regulation (Art. 11, Regulation (EU) 2024/1689). Annex IV details the minimum content: general system description, detailed architecture and components, training data information, performance metrics (accuracy, robustness, cybersecurity), and the development process.

Translation: Your README and your Confluence page aren't enough. The regulation requires a living document covering the system architecture (like the Mermaid diagrams we use in the Obsolescence series), model performance metrics, robustness tests, and cybersecurity measures. Think of it as an Architecture Decision Record on regulatory steroids.

4. Record-Keeping and Logging — Article 12

High-risk systems must be designed to automatically generate logs during operation, ensuring full traceability of every decision and the ability to reconstruct events if a compliance issue arises (Art. 12, Regulation (EU) 2024/1689).

Translation: If you already use Supabase + FastAPI with the architecture from the agentic radar, this should sound familiar. Every ingestion event, every CrewAI agent decision, every LLM response gets logged in the database. What the regulation formalizes is what any competent backend engineer should already be doing: structured logging, not as an afterthought, but as a design requirement from day zero.

5. Human Oversight — Article 14

The system must be designed with "human-in-the-loop" or "human-on-the-loop" mechanisms, ensuring that a qualified human operator can oversee, interpret, and if necessary, override the AI's decisions (Art. 14, Regulation (EU) 2024/1689).

Translation: This is the principle we implemented in Autopilot Part 5 with GitHub Environments for manual approval. The pipeline generates content automatically with AI agents, but no post gets published without explicit human review and approval. It's not a new concept for us; now it has the force of law.

Spain and the AESIA: The Local Sheriff

The EU AI Act is a European Regulation (not a Directive), which means it is directly applicable in Spain without needing national legislative transposition. However, Spain has taken an additional step: in May 2026, the Council of Ministers approved the Spanish AI Law, which complements the European regulation and defines the role of the AESIA (Spanish Agency for AI Supervision) as the national competent authority.

The AESIA is the entity that will investigate complaints, conduct audits, and, where applicable, impose the AI Act's penalties on Spanish territory. Additionally, Spain has launched regulatory sandboxes: controlled environments where startups and companies can test innovative AI systems under AESIA supervision, without sanctioning risk during the trial period.

The Spanish startups we've analyzed on this blog are not strangers to this regulation. Clarity AI operates in ESG financial scoring, an area that Annex III classifies as high-risk. Nextail makes inventory decisions with prescriptive AI in the supply chain. Devo protects critical military infrastructure, the most sensitive category in the regulation. All of them will need to demonstrate compliance.

Compliance-as-Code: The Engineer's Checklist

If there's one thing we've learned building data pipelines on this blog, it's that documentation that isn't automated doesn't get maintained. Here's an actionable checklist, designed so that a technical team can execute it sprint by sprint:

Phase 1 — Inventory and Classification (Sprint 1)

Inventory all AI systems in your organization (including ones you don't call "AI" but internally use ML)
Classify each system in the risk pyramid: Prohibited / High / Limited / Minimal
For each system classified as High Risk, assign a technical compliance owner

Phase 2 — Technical Implementation (Sprints 2-4)

Implement automatic logging of model decisions (Art. 12): timestamps, inputs, outputs, confidence scores
Create living technical documentation (Art. 11 + Annex IV): architecture, data, metrics, process
Design human oversight mechanism (Art. 14): manual approval, "kill switch" button, monitoring dashboards
Audit training datasets (Art. 10): bias, representativeness, traceability, versioning

Phase 3 — Continuous Management (Ongoing)

Establish risk management pipeline (Art. 9): periodic review, Concept Drift monitoring, mitigation plan
For Limited Risk systems: verify the user knows they're interacting with AI
Configure cost and usage alerts (connect with The Hidden Economics of AI: compliance is an additional hidden cost)
Register the system in the EU public database (when applicable for high-risk)

The Regulation Isn't the Enemy; Ignorance Is

There is an understandable temptation to see the EU AI Act as a bureaucratic brake on European innovation. And in part, the criticism has merit: the definition of "high-risk" in Annex III is extremely broad, the documentation burden of Annex IV can be disproportionate for a five-person startup, and the uncertainty around the Digital Omnibus generates paralysis in legal teams.

But if you strip away the legal jargon and look at the bare technical requirements, what the regulation actually asks is: document your system, control your data, log your AI's decisions, manage risks continuously, and keep a human in the control loop. In other words, exactly what a good engineer should already be doing.

If you've followed the practices we've documented on this blog — data hygiene with Z-Score, automatic logging with FastAPI and Supabase, human-in-the-loop with GitHub Environments, risk management with Deming's PDCA cycle — you're already 80% of the way to compliance. The remaining 20% is formalization and documentation.

As Deming said: "It is not enough to do your best; you must first know what to do." Now the regulation tells you what to do. How to do it, you already know. Or at least, you have a blog where you can find it.

Coder Legion - Recent posts tagged regulation

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Two Complaints in Two Years: New York City's AI Hiring Law Made a Record Nobody Can Read

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The FTC Entered an $18,000,000 Judgment Against Air AI. The Order Tells It to Pay $50,000.

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The arithmetic, and why it is the wrong number

What the case was about

What this order is, as of its own paperwork

The transferable point

Sources

EU AI Act: What Every Engineer Needs to Know (No Lawyers Required)

The Risk Pyramid: Classify Your AI in 60 Seconds

🔴 Unacceptable Risk — PROHIBITED (Article 5)

🟠 High Risk — STRICT REGULATION (Articles 6-49 and Annex III)

🟡 Limited Risk — TRANSPARENCY (Articles 50-52)

🟢 Minimal Risk — FREE (no additional obligations)

The 5 Technical Commandments of High Risk

Spain and the AESIA: The Local Sheriff

Compliance-as-Code: The Engineer's Checklist

The Regulation Isn't the Enemy; Ignorance Is

Sources of Interest: