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YPO Technology Network AI Brief

Stephen Forte

AI moves fast. Your briefing should move faster. The YPO Technology Network AI Brief is a daily breakdown of the AI developments that actually matter to your business. No hype, no jargon, no filler — just what changed, what it costs you or saves you, and what to tell your team on Monday. Hosted by Stephen Forte for the leaders who don't have time to chase the news but can't afford to miss it.

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S1 · E162
Yesterday · 10 min
The Algorithm Is Not A Defense
Connecticut's Public Act 26-15 takes effect today. Three sections reach ordinary companies: employers filing a federal layoff notice must tell the state whether the layoffs relate to their use of artificial intelligence; using an automated employment decision tool "shall not be a defense" against a discrimination complaint, though evidence of anti-bias testing may be weighed; and anyone selling an AI subscription to a Connecticut resident needs written notice of the terms and written acceptance before charging a fee. The heavier developer and deployer duties do not start until October 2027. Last night California's governor signed 13 AI bills before the deadline, including SB 947 (no relying only on AI to discipline or fire, a near-identical bill was vetoed last year) and SB 951 (layoff notices must say whether an AI system caused the cuts), plus an executive order that state agencies will keep calling artificial intelligence "Artificial Intelligence," the day after Washington's order renaming it "Super Intelligence." The regulator's question is no longer whether you use AI. It is who decided, and can you show it. In this episode, Stephen Forte covers: Who this reaches. The rules follow the worker and the customer, not the head office. Connecticut's layoff question. The new disclosure on federal layoff notices, the act's broad definition of AI, and why the hard part is knowing the answer. The no-defense rule. What counts as an automated employment decision tool, what is excluded, and the credit Hartford earns for saying in advance what good anti-bias evidence looks like. AI subscriptions. Written terms, written acceptance, disclosed limits and discretion, renewals, and attorney general enforcement only. What does not start today. Developer and deployer duties (October 2027), companion chatbots (January), youth social media (2028). California's thirteen. SB 947 and SB 951 in plain words, and one breath each for surveillance, doctors, watermarks, digital replicas, lawyers and the rest. Two orders on a name. Washington's "Super Intelligence" order and Sacramento's reply, "further informed by common sense." The close. Could the person who signs your layoff notice and the person who approved your last hiring tool both say whether a machine made the call? Would their answers match? Sources: Connecticut Public Act 26-15 (Substitute Senate Bill 5), approved 27 May 2026, enrolled text: https://www.cga.ct.gov/2026/ACT/PA/PDF/2026PA-00015-R00SB-00005-PA.PDF Governor of California, signing release of 30 September 2026 (13 bills, listed by number): https://www.gov.ca.gov/2026/09/30/californias-nation-leading-ai-framework-just-got-stronger-governor-newsom-signs-more-first-in-the-nation-worker-protections-and-more/ ; Executive Order N-10-26: https://www.gov.ca.gov/wp-content/uploads/2026/09/SIGNED_EO-N-10-26_9.30.26.pdf Associated Press, "California Gov. Gavin Newsom signs laws to protect workers from AI risks," 30 September 2026 The White House, "Inaugurating The Era Of Super Intelligence," 29 September 2026: https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/ The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E161
Wednesday · 10 min
The Price And The Phone Line
Reuters reported on 29 September that McDonald's runs a pricing engine that analyzes millions of daily transactions across nearly 14,000 restaurants and generates what the company calls "the optimal price" for each item at each location, using among other things an estimate of how much local customers are willing to pay. Two company-run stores in Fresno, two miles apart, sell the Big Mac at $5.69 and $6.89. Five franchisees described pressure to follow the recommendations, a June document shows deviations are tracked, and the portal warns owners they "may be competitors." McDonald's calls it "a tool, not a mandate." The same week, California signed AB 1609: companies over $500 million in revenue must disclose when customer service is a chatbot and connect a human within 15 minutes, with penalties of $5,000 and $10,000. And CarMax told investors that AI voice now answers 100 percent of its inbound calls while its pricing algorithms are retuned monthly, both under one executive. The two things a customer meets first, the price and the phone, are now machines, and the rules arrived in the same week. In this episode, Stephen Forte covers: The pricing engine. How McDonald's machine sets "the optimal price," what the owner's portal shows, the Fresno gap as an observed difference, and how recommendations are tracked and followed up. Both sides. A former owner: "You don't really have much of a choice anymore." McDonald's: "a tool, not a mandate." A former FTC commissioner on the antitrust warning in the portal's terms. The regulators. The FTC's proposed enforcement policy on personalized pricing (comments closed 25 September) and New York's on-screen disclosure line. The phone gets a clock. California AB 1609: who it covers, the disclosure, the 15-minute human, the hold caps, the penalties, effective in January. Why the number will follow companies under the threshold. SB 947. The governor's deadline on automated decisions in discipline and firing. CarMax. AI voice on every inbound call since May, pricing algorithms evolved monthly, and strategy, data science, AI and pricing under one senior vice president. "Every vehicle is an individual SKU." The close. Who sets the price the customer sees, who decides when the machine hands the call to a person, and whether those two people have met. The law caught up with the phone first. The price is next. Sources: Reuters, "Inside McDonald's push to have AI price your Big Mac," 29 September 2026 (via Investing.com): https://www.investing.com/news/stock-market-news/inside-mcdonalds-push-to-have-ai-price-your-big-mac-4921983 California AB 1609 text and the Governor's signing release of 28 September 2026: https://www.gov.ca.gov/2026/09/28/governor-newsom-signs-commonsense-legislation-to-make-your-life-easier/ ; SB 947 status at leginfo.legislature.ca.gov CarMax Q2 fiscal 2027 results and call, 29 September 2026: https://investors.carmax.com/news-and-events/news/news-details/2026/CarMax-Reports-Second-Quarter-Fiscal-2027-Results/default.aspx ; CarMax and Sierra, 6 August 2026 FTC, Proposed Enforcement Policy Statement Regarding Personalized Pricing, 19 August 2026; New York Algorithmic Pricing Disclosure Act The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E160
Tuesday · 17 min
Costco Let The Bots In
On its 24 September earnings call Costco's CFO said traffic from AI search grew triple digits for a second consecutive quarter, converts better than any other source, and sells the membership itself. He named Gemini, Anthropic and OpenAI as the sources, and said teams are cleaning up product data and pages so that Costco's value shows up correctly in the large language models. In May the CEO explained why: regular search never showed the all-in price; the models do. Then the map. Amazon's robots file names 101 automated visitors and turns away every AI agent, including the ones that answer a live question. Costco, Walmart, Target, Home Depot, IKEA, Carrefour, Etsy and McMaster-Carr have no AI rule at all; Best Buy lets the answering agents in and shuts out the training crawlers. And the honest counterweight: Walmart's checkout inside ChatGPT converted at one third the rate of sending the shopper to its own site, so the winning posture is discover in the assistant, buy on your site. In this episode, Stephen Forte covers: The call. Triple digits twice, highest conversion of all site traffic, the membership among the top items, the three companies named, and the product-page work behind it. The industry number. Adobe's data, as reported: AI-referred retail traffic up 138 percent in a year, converting 54 percent better; half of the average grocery page unreadable to a machine. The map. Amazon's 101 no's and its Perplexity lawsuit, turned back by the Ninth Circuit on 4 August. Why blocking is a luxury of the company that is already the destination. Walmart's lesson. One third the conversion inside the chat; OpenAI's pivot to discovery. Five moves. One: find out whether you are letting them in (answering agents versus training crawlers; Cloudflare's 15 September default; the Google-Extended myth). Two: put the price and the facts in the page the server sends, not in a script, and put the all-in price on it. Three: feed them directly and keep the feed current (OpenAI's nine required fields). Four: ask the three assistants what they say about you, then build the analytics channel. Five: keep the checkout. What not to buy. An llms.txt file: none of the three vendors' crawler documentation mentions it. The broken metric. Your search ranking is a score in a contest the customer is starting to stop watching. The customer did not search. She asked. And the answer had somebody's price in it. Sources: Costco Q4 FY2026 earnings call, 24 September 2026 (transcripts via Webull and Investing.com); Q3 FY2026 call, 28 May 2026; press release: https://www.sec.gov/Archives/edgar/data/0000909832/000090983226000084/costex9918-k92426.htm Amazon.com Services v. Perplexity AI, Ninth Circuit opinion, 4 August 2026: https://cdn.ca9.uscourts.gov/datastore/opinions/2026/08/04/26-1444.pdf robots.txt files of amazon.com, costco.com, walmart.com, target.com, homedepot.com, bestbuy.com and others, fetched 27 September 2026 Search Engine Land, 20 March 2026; Digital Commerce 360, 24 March and 17 June 2026 (Adobe data) Cloudflare, new AI traffic options, 1 July 2026: https://blog.cloudflare.com/content-independence-day-ai-options/ OpenAI crawler documentation and product feed specification; Anthropic crawler documentation (7 April 2026); Google crawler documentation (3 March 2026) and Merchant Center structured data help The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E159
Monday · 14 min
Microsoft Gave The Agent A Badge
On Friday 25 September Microsoft rebuilt Copilot into one app with three tabs: Home, Code and Autopilot. Home puts Word, Excel and PowerPoint inside the assistant and adds a Today panel across mail, calendar, Teams and tasks. Code lets anyone build an app or workflow by describing it, hosted in the company's own tenant. Autopilot is a standing agent with, in Microsoft's words, its own identity, memory, computer and workspace, that colleagues can @mention like a coworker. Nothing is broadly available yet: Home and Code reach the Frontier early-access program in the coming weeks; Autopilot enters private preview at month end. The same day Microsoft split the bill. Everyday AI stays on the per-user seat, with OpenAI and Anthropic models included. Cowork, Code, Autopilot and the frontier models run on a usage meter, which for enterprise customers stays off until an admin writes a spending policy. New small-business licenses bought through resellers get the meter on by default from 2 November. In this episode, Stephen Forte covers: What was announced, and what is actually available. Three tabs, Office inside Copilot, Today, Code, Autopilot. Frontier program, private preview, no general availability date. How it looks on the desktop. Office in Copilot rather than Copilot in Office; a model menu offering GPT, Anthropic's Opus and Auto; the demo agent Dot that found a shipment problem across eighteen stores without being asked. Three layers of operational change. The assistant becomes the front door to Office; every department can build hosted software, with a plugin registry IT approves; and a colleague who is not a person gets a badge and an audit trail. Andreou: autonomy is "absolutely terrifying to an IT admin." Nadella: "Every agent has to have an identity." The bill. Seat plus meter, Microsoft's plug-in hybrid. "Some vendors put everyday AI work on a meter. We think that's the wrong deal." Enterprise meter off by default; reseller default on from 2 November; no price published on Friday; Opus 5 "with limits" and no limit stated. Is it a replacement for Claude? Anthropic's models are inside Copilot, so the question is the harness and the fence, not the brain. Microsoft's own chart (thirty dollars versus eighty-four for fifteen everyday tasks; seventy-three versus one hundred forty-nine for an advanced user) and the fine print that priced the rival on its most expensive model throughout. The host's read as an operator whose company runs on Claude and pays Microsoft too. What Microsoft did with its own product. Rivals on the menu at the flat price; its own meter off by default; its own executive calling it terrifying. Microsoft put its rivals on the menu. What it is charging for is the building. Sources: Microsoft, Introducing the new Copilot with Home, Code and Autopilot (Jared Spataro, 25 September 2026): https://blogs.microsoft.com/blog/2026/09/25/introducing-the-new-copilot-with-home-code-and-autopilot/ Microsoft Tech Community, Evolution of the Copilot pricing model (Nicole Herskowitz, 25 September 2026): https://techcommunity.microsoft.com/blog/microsoft-copilot-blog/evolution-of-the-copilot-pricing-model/4559416 Microsoft Partner Center, September 2026 announcements: https://learn.microsoft.com/en-us/partner-center/announcements/2026-september GeekWire, 25 September 2026: https://www.geekwire.com/2026/microsoft-unveils-all-in-one-copilot-app-taking-on-anthropic-and-openai-in-new-push-to-boost-adoption/ The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E158
Saturday · 16 min
Your Company Has No Bill Of Work
Every product a company makes has a bill of materials: every part, its cost, its supplier. The company that makes those products has no equivalent document for the work its people do. This weekend edition is about that missing document, the bill of work, why almost nobody has one, and how to build one for a single department in about three weeks. Nobody has done the counting: the Census Bureau finds 85 percent of US firms using generative AI use it for writing and editing, and nearly 65 percent confine it to three tasks or fewer. More than seven thousand annual reports filed with the SEC since January 2025 mention AI; one states a cost per task. In this episode, Stephen Forte covers: The bill of materials, and the teardown. Munro and Associates in Auburn Hills, Michigan, takes a competitor's car to pieces and prices every part at plus or minus eight percent. There are two kinds of teardown; the second kind points inward. Why the org chart cannot see it. A map of authority, not a map of work. One task wearing three costumes, each five percent of someone's week, each correctly filed as a rounding error by its own department. The lens. The unit of AI is the task family, not the department. Organized by department, bought by the person, measured by headcount, becomes the task family, the completed task, cost per completion. Five steps to a bill of work. Take one department apart on cards. Sort by shape, not owner (the illustrative five accountants: eight shapes, eight shared agents). Cost the biggest pile three ways, including what is queued behind it. One agent, owned by the person who knows the work, baseline written first, ninety days. Decide what the freed capacity is for before it exists. Why the number is capacity, not cash. Danish payroll data: workers report saving about three percent of hours; hours and earnings do not move. The three conversions: velocity, growth not hired for, consolidation through attrition. The honest section. The US General Services Administration published 240,000 hours reclaimed; its own Inspector General found nine of the ten biggest bots off their forecasts and two credited with 15,000 hours after being switched off. Goldratt's constraint objection, amended, not repealed. Why "pick three workflows" and "map everything" both miss the pile. The question. If someone handed you a price list on Monday for the ten most common tasks in your company, could you tell whether it was a good price? Do you know which ten they are? A note on the arithmetic: the five accountants are illustrative and are said so on air; every other figure is from a primary source listed below. The Swedish payments firm is one filing, not a case study. Sources: US Census Bureau, Center for Economic Studies working paper CES-WP-26-25 (April 2026), generative AI use by task among US firms. SEC EDGAR full-text search, 10-K and 20-F filings mentioning artificial intelligence, 1 January 2025 to 12 September 2026; Klarna Form 20-F for fiscal 2025. Kaplan and Anderson, Time-Driven Activity-Based Costing, Harvard Business Review, November 2004. Humlum and Vestergaard, NBER Working Paper 33777 (revised March 2026), large language models and labor market outcomes in Denmark. US General Services Administration, Office of Inspector General, report A210057/B/5/F24001, 30 November 2023. Goldratt, The Goal (1984); C.H. Robinson second-quarter 2026 results; Munro and Associates published teardown reports. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E157
September 25 · 11 min
Italy Says Your Certificate Is No Defense
On 30 September, Italy's implementing decree for the EU AI Act takes effect, and it reads less like a compliance rulebook than a set of courtroom rules. In any damages claim involving an AI system, a judge can order the company to hand over the system's logs, its risk-management file, its technical documentation and its human-oversight settings. If the company cannot produce them without justified reason, the court treats the claimant's version of the facts as admitted. Once an AI Act obligation has been breached, causation is presumed. And conformity with the AI Act, even certified conformity, does not by itself exclude liability. Brussels pushed the EU-wide high-risk paperwork deadline to December 2027 this summer. Rome did not wait for it. In this episode, Stephen Forte covers: The dates. Italy's national AI law of September 2025; the liability decree signed 9 September 2026, published 15 September, in force 30 September; the AI Omnibus delay of high-risk obligations to 2 December 2027. Access to evidence. Article 17: the four documents a judge can demand, and the sentence that treats missing documentation as an admission. Causation and the certificate. Article 18 presumes the causal link once a rule is breached. Article 19 says certified conformity is not, on its own, a defense. The insurer. Article 20: thirty days to name your liability insurer when asked, and a direct action against it up to the policy limit. The criminal side. New Article 437-bis of the Italian criminal code: one to five years for omitted safety or oversight measures on high-risk systems, and the paragraph that reaches the professional user who switched the system on. Corporate fines under Italy's corporate-crime statute of roughly 155,000 to 1.55 million euros, plus bans on public contracts, licenses, subsidies and advertising. Why it matters outside Italy. The four documents an Italian judge can demand are the four the AI Act will require of every high-risk system in the Union from December 2027, and the four your insurer, your board and your next plaintiff will ask for regardless. The one question. If a judge asked tomorrow, could you hand over what your AI system did, and who was watching it, for every decision since the day it was switched on. A note on the sources: every provision was read in the official consolidated text at normattiva.it; the translations are the host's own. The Brescia manufacturer in the episode is invented to make the shape clear. Also in this episode: a short note on why the show went quiet for three days. Sources: Italy, Legislative Decree 9 September 2026, n. 160 (Gazzetta Ufficiale n. 214, 15 September 2026): https://www.normattiva.it/uri-res/N2Ls?urn:nir:stato:decreto.legislativo:2026-09-09;160 European Commission, AI Act regulatory framework and AI Omnibus timeline: https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai EU AI Act implementation timeline: https://artificialintelligenceact.eu/implementation-timeline/ The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E156
September 21 · 9 min
Nobody Cut The Old Bill
In one week, Salesforce and HubSpot both showed the mid-market what an AI agent will cost, and the answer is a second meter running next to the seats you already pay for. Salesforce shipped its own reasoning model, Koa, to pilot customers with general availability months away and no price. It paired user seats with preset credit allowances and gave its agents first names. A Salesforce plug-in opened to every paid plan of a frontier lab's assistant, with no combined price. HubSpot did the one thing Salesforce did not: it published a price list, by the action, in credits. Then two analysts asked twenty Salesforce customers what agents do to the bill. Three in four of those who had modelled it expected their Salesforce spending to rise. Fourteen were asked where the money came from. Not one said the old bill. In this episode, Stephen Forte covers: What shipped at Dreamforce. Koa, trained on twenty-seven years of Salesforce CRM intelligence, in pilot now, general availability expected winter 2026 in US regions, unpriced. Seat bundles with preset credits. Piper, Hunter and Fin. Two vendors, two meters, one workflow. A Salesforce plug-in on every paid Claude plan, thirty-seven prebuilt sales skills, seven thousand sellers already on it, and no mention of pricing. HubSpot's price list. Nine US dollars per thousand credits on the annual rate. A thousand credits per content piece, five hundred per invoice chased, ten per nurture email, fifty per resolved service conversation. Arithmetic a CEO can do in the car. The twenty interviews. Five to fifteen percent of Salesforce spend going to agents. None of fourteen shifting existing budget. Seventy-five percent expecting the bill to rise under headless access. The reframe. The seat was a ceiling: you knew the worst case on the first of the month. The meter is a floor with no natural top except the work itself. A rental car and a taxi both get you to the meeting; only one keeps counting in traffic. The close. Walk into the next renewal with two numbers, what the seats cost and what the meter will run. If the vendor can only give you the first, that is the answer. A note on the customer figures: they come from twenty in-depth interviews conducted over five business days, not a statistical survey, and are aired exactly as the analysts printed them. Sources: Salesforce, Koa press release, 15 September 2026: https://www.salesforce.com/news/press-releases/2026/09/15/koa-reasoning-model/ Moor Insights and Strategy, Dreamforce 2026 field notes, 18 September 2026: https://moorinsightsstrategy.com/field-notes/at-dreamforce-2026-salesforce-goes-all-in-on-agentic-ai/ Anthropic, Salesforce in Claude, 15 September 2026: https://claude.com/blog/salesforce-in-claude HubSpot pricing page (credits): https://www.hubspot.com/pricing/suite SiliconANGLE, Dave Vellante and George Gilbert, Salesforce after Dreamforce, 19 September 2026: https://siliconangle.com/2026/09/19/salesforce-after-dreamforce-how-the-crm-giant-can-grow-beyond-its-own-interface/ The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E155
September 19 · 14 min
Nothing Broke. Check Anyway.
Weekend edition. For those who have been plumbing their own systems, this one is for you. Once a quarter, Stephen Forte's company reviews the systems it runs itself: the code, the logs all the way down, the mechanical parts, the memory systems, and every bill divided by what actually shipped. This quarter it was the turn of three digital employees behind the morning client briefing. Nothing was broken, and nobody made a mistake. The systems had drifted, which is what agents do when nobody is looking. A credentials script that made nineteen trips to the vault for eighteen keys and said "loaded" whether or not it had. An engagement memory that answered every write with "probably" and filed a correction underneath the thing it corrected. A drafting loop that wrote eleven versions of every brief and handed in one. Three employees, none of them people, none of them ever reviewed. In this episode, Stephen Forte covers: The quarterly review as a practice. AI systems do not break the way software breaks. They drift, settle into habits, and keep saying yes while the yes slowly means less. Why that is not a defect, and why the review is the only thing that catches it. The most agreeable intern. The vault script finished every shift with "environment loaded," including the night several keys came back blank. Nineteen trips for eighteen keys, twelve seconds a load, fourteen loads a night. The fix took an evening. The fix had been written down twice before, and a backlog only promotes what is on fire. The brilliant colleague with a filing problem. Twenty-four facts written in one day, twenty-four answers of "probably." A changed approver recorded properly on the day, and the old name still ranking first and second. What drift actually looks like, and why only a review sees the order a memory remembers in. The smoke detector with the speaker removed. A nightly review that flagged two thousand four hundred and seventy-two of twenty-five thousand memories, and whose last reader had opened it five weeks earlier. The anxious intern. Eleven drafts to hand in one, and two quality checks that had drifted into impossible. A check that is wrong does not waste one draft; it rounds every draft to zero. Four questions that make up a digital employee's performance review. Does it fail loudly? Does it confirm, or does it say probably? What does one unit of output actually cost? Who opens the report it produces? The task master. One more digital employee whose whole job is a daily pass over what the others produce that no human reads, one paragraph a day, a human on Friday. And the cadence that fits each role: quarterly, monthly, weekly, daily. The close. Every digital employee reports success by default. A dashboard that cannot go down is not a metric. It is a greeting. A note on specifics: every number in this episode is a real measurement from the review of Stephen's own company's systems on 17 September 2026. No client is named, described or identifiable; no vendor or product is named for any tool. Sources: Internal quarterly systems review, 17 September 2026: credentials loader call counts, timings and failure behaviour, with the two-call replacement verified against the original; the memory system's write log, session hydration and search rankings; the nightly consolidation report; generation counts against shipped briefings. The daily review agent ("the task master") over hidden output, added 18 September 2026, with a weekly human read. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E154
September 18 · 7 min
They Had A Policy
On Tuesday the Supreme Court of Tasmania threw out a parole condition because the document justifying it cited case law that does not exist. The Parole Board has conceded its own secretary wrote that document with AI. Tasmania already had a twenty-page AI policy, approved two years and two days before the ruling, and it had warned that inappropriate use of AI in decision making could expose a decision to judicial review for being unreasonable or denying procedural fairness. Those are the court's grounds. In the same week in Los Angeles, a lawyer defending the insurer State Farm was fined $999.99 over briefs with fabricated citations, and her own apology to the court referenced her firm's generative-AI policy. Two continents, two written policies, two documents of invented law that reached the person who signs. The policy was in the binder. The work was in the room. In this episode, Stephen Forte covers: Hobart. The board's rationale cited fictitious cases and, in counsel's words, "argued forcefully." The board withdrew the condition in August and declined to say why. The court found it legally unreasonable and a denial of procedural fairness. The policy that predicted it. Approved 13 September 2024 for every agency in the state, it told officials to critically examine AI outputs and warned that inappropriate use "may expose the decision to the risk of legal challenge, including judicial review," for being "improper, unreasonable" or denying "procedural fairness." The remedy. The Attorney-General is writing to the board's chair, wants assurances, and has told the justice department to remind every employee to comply with the policy. Told the policy had not worked, the state reminded everyone about the policy. Los Angeles, the control case. The lawyer accepted responsibility in her own words and listed three mechanical steps: retrieve every authority from a real database, check every quotation against the opinion, audit citations before filing. Her firm had a policy too. Policy versus control. A policy is a letter addressed to people who were already going to behave. Every company has a fire policy in a binder; the sprinkler in the ceiling has never consulted it. The mirror. When the board asks whether AI is under control, you will reach for a document. Reach for the check: what has to happen before a confident, well-formatted, completely invented paragraph reaches the person who signs. A note on specifics: no individual is named; the Tasmanian document is guidance in form and is what the state calls its AI policy; nothing here is a view on the underlying conviction, which the woman concerned has always contested. Sources: ABC News, 15 September 2026. Report ABC News, 16 September 2026. Report Tasmanian Government AI guidance, approved 13 September 2024. PDF ABA Journal, 15 September 2026. Report The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E153
September 17 · 10 min
The Attacker Was An Agent
Spain's data protection agency has received the first notification of a personal-data breach in which the intruder was an AI agent rather than a person. By the notifying company's account, the agent searched for vulnerabilities, achieved a valid login, explored the application on its own, altered personal data and accessed invoices. The regulator's response is not a new rule but four changes to how every company must think about risk, response time, credentials and human oversight, with its own caveat that AI creates no new threats; it removes the time you had to respond to the old ones. In the same week, two London bodies retired the other two point-in-time assumptions: give AI a learner's permit and monitor it for life, and stop passing liability from the companies that build AI to the companies that use it. In this episode, Stephen Forte covers: Madrid, the incident. The AEPD published the notification on 14 September: an agent built on "a well-known language model" chained the phases of the attack without a person steering each step. The regulator's caveats air with it: the account comes from the notifying organisation; the model and its provider are not implied compromised; one case is not a trend. The sentence that matters. "AI does not create new threats. It increases the speed, scale and adaptability of known malicious techniques, reducing the time available to detect and contain them." Four sentences that could be your risk committee's agenda. Write AI-executed attack into the risk analysis explicitly; assume response plans built for a human attacker are too slow; treat an over-permissioned account, key or token as a door that opens at machine speed; keep human oversight, resting on detection and response that can keep up. London, approval. The MHRA-established commission recommends staged authorisations for AI medical devices, "similar to 'L-plates' for learner drivers," and continuous monitoring "throughout their working life." A recommendation, not yet a rule. London, liability. Parliament's Joint Committee on Human Rights: "far too much freedom" for the companies that develop AI systems "to pass on liability to those who deploy them"; "responsibility to prevent harm should sit with those who are best able to do so." It calls for a dedicated AI Bill and a new regulator. The close. Nothing on the regulator's list of fundamentals is new. What changed this week is that you no longer have time to do it later. A note on specifics: "first" means the first notification to the Spanish regulator, of one case; the model and the affected organisation are not named because the regulator did not name them; the London reports are recommendations to government, not law. Sources: Agencia Española de Protección de Datos, blog, 14 September 2026 (in Spanish). AEPD statement GOV.UK, National Commission into the Regulation of AI in Healthcare, 10 September 2026. Press release and report Joint Committee on Human Rights, "Human Rights and the Regulation of AI," HC 160, 14 September 2026. Report The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E152
September 16 · 11 min
225,000 Stars, Zero Security Audits
A free piece of software from DeepSeek, the Chinese AI lab, is now one of the fastest-growing projects GitHub has ever hosted: published on 13 August, past 225,000 stars and nearly 27,000 forks by mid-September. It is not a model. It is an agent harness, the software that decides what an AI model is allowed to touch, and its architecture is the reason for the growth: every layer of it is a swappable plugin. Its own safety notice says it has not been audited and must not be treated as production-ready, and its own engineers write that the default credential store cannot keep a secret from the AI it serves. In this episode, Stephen Forte covers: The number. 225,223 stars and 26,799 forks in 33 days, under an MIT license, with a new release the same week. The projects at the top of GitHub's all-time list took years to get there, most of them the better part of a decade. The architecture. The model, the filesystem and shell, storage, the scheduler and even the interface are plugins. A shipped plugin swaps the execution environment for a remote sandbox so nothing runs on your own hardware. It can hand a task to a Claude Code session, to OpenAI's Codex, or to any agent speaking the same open hand-off standard, and use the answer. Like the shipping container: standardize the box, not the cargo. Against Claude Code. Ahead: no subscription, open all the way down, any model including one hosted inside your own walls. Behind: three all-or-nothing permission presets, thin hooks into other systems, and the credential question. Your keys, both halves. The default store is a plaintext file, locked to your own user account, and the project's README says the agent's tools run as that same user, so the store "cannot isolate secrets from the agent"; an OS-keychain provider is deferred, not shipped. But every key is only a reference to an environment variable and the launch environment wins, so a secrets manager can hand the key in at launch with the file never written, and spawned commands get a scrubbed environment. A weak default, a real capability, and a decision the operator has to make on purpose. The warning, verbatim. "It has not undergone a security audit and must not be treated as secure or production-ready." Published in plain language, in the same box as the code, on day one. The close. 225,000 engineers have already voted for the architecture. The audit has not been held. A note on specifics: star and fork counts are from the GitHub API on 15 September 2026; the credential behaviour is taken from the project's own READMEs and design notes at that day's commit. Vendors are named for identification, not endorsement. Sources: deepseek-ai/deepseek-harness, repository and README. GitHub DeepSeek Harness safety notice (SAFETY.md). Safety notice Credential store README (dsh-credentials-local): precedence, the same-user limit, the deferred keychain provider. README CLI reference: credential resolution order and the subprocess environment scrub. Reference The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E151
September 15 · 9 min
Asia Just Answered Three AI Questions
Three institutions on one continent answered, in public and in one week, the questions most boardrooms are still debating. A bank in Tokyo let generative AI write the code for the system that holds every customer's balance. China's highest court told every judge in the country how to rule when an AI clones a voice. And one of India's largest outsourcers found it had the equivalent of twenty thousand people's time on its hands, and had to decide what to do with it. None of the three is a vendor announcing a product. All three are institutions reporting on themselves. In this episode, Stephen Forte covers: Tokyo, the build. Sony Bank and Fujitsu published phase-by-phase results from a year of AI-assisted development on the bank's core banking system: development period down 30 percent, hours down 40 percent, 99 percent of source code generated. The companies' own figures. Fujitsu now plans to sell the method to the other banks on its platform, which makes the bank's advantage a rental. The question the next modernisation proposal will not answer is who, in your building, signs for a ledger where humans wrote one line in a hundred. Beijing, the law. China's Supreme People's Court issued twenty-four articles of judicial guidance, its first rules for AI cases. Cloning a voice without consent "constitutes an infringement of their voice rights"; an unauthorised digital likeness violates the right to name and likeness; using AI to assemble private information is a privacy breach. The posture in one sentence: "tolerance should not be mistaken for permissiveness, nor should prudence be interpreted as acquiescence." It is guidance to courts rather than a statute, it does not settle the training-data question, and it drew the boundaries around people before data. India, the people. Wipro's chief technology officer, Sandhya Arun, told Reuters that AI had freed capacity "equivalent to" roughly 20,000 of the company's 243,000 employees, redeployed inside the firm. "It doesn't necessarily mean person-to-person replacement by an agent." An outsourcer sells hours, so freed hours are unsold inventory unless the pricing moves to outcomes. Your outsourcer's freed capacity is your next negotiation. The close. "Capacity equivalent to twenty thousand people" sounds like a headcount figure. It is hours that were freed and then had to be pointed at something. Capacity is not a saving. It is a decision nobody has made yet. A note on specifics: the Sony Bank figures are from the companies' joint release and are not independently audited; the models were Anthropic's Claude and Claude Code via Amazon's cloud. The court guidelines are quoted from the court's own English release. The Wipro figures are the company's own, as reported by Reuters. Sources: Fujitsu and Sony Bank, joint press release, "Sony Bank and Fujitsu apply Generative AI to Core Banking System Development," 14 September 2026. Release text Supreme People's Court of China, "SPC sets rules to curb AI misuse," 10 September 2026. english.court.gov.cn Reuters, "Wipro's AI push frees capacity equivalent to 20,000 workers, CTO says," 10 September 2026, via The Star. Article The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E150
September 14 · 9 min
AI Does Not Install Itself, Google Admits
On Monday, Accenture and Google Cloud launched a new business group whose headline is not software but people: a planned workforce of a thousand "forward deployed engineers" who sit inside client companies and build the AI for them. The most capable software company in the world has just said, in its own press release, that its enterprise AI does not install itself. Yesterday's episode was about an airport that keeps its AI engineers in-house so the knowledge stays in the building. Today is the counter-bet: the supply side wagering that most companies will rent those people instead. In this episode, Stephen Forte covers: What was actually announced, stripped of the adjectives: nearly fifty thousand Google Cloud-skilled staff already, a thousand-person forward-deployed workforce to be established, and four stated priorities, three of which are about adoption and none about the model. The reference customer problem: the one worked example is YouTube, a Google property, and the numbers are the companies' own. Where "forward deployed" comes from, why Palantir made it famous, and why the frontier AI labs and now the largest consultancy on earth have copied it. The dishwasher test: nobody builds a division of a thousand plumbers when the machine works in most kitchens on its own. The real asset: what a forward deployed engineer learns about how your company actually works, and the question of who owns it when the badge is handed back. The one staffing decision to make before the proposal arrives: seat one of your own people beside each of theirs, and make the handover the deliverable, not the agent. Sources: Accenture Newsroom, "Accenture and Google Cloud Deepen Partnership with Formation of New Accenture Gemini Enterprise Business Group," 8 September 2026. All figures and quotes are from this release, read in full. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E149
September 12 · 10 min
Using AI In Your YPO Chapter
A weekend edition about your YPO chapter, the most important part of YPO, and exactly how an AI assistant fits into running it. Not the case for AI, but the plumbing that has to exist first and the things a chapter actually does with it once it does. Stephen is the Regional Learning Officer for the Pacific, has founded two chapters, has been chapter chair, and will facilitate the chapter chair workshops at GLC in San Diego and Thailand in 2027. Everything here is what his own chapter does. In this weekend edition, Stephen Forte covers: The plumbing: a domain the chapter owns, a Google Workspace subscription for the officers, mailboxes attached to roles rather than people, and a shared drive organized by learning year with the contracts, receipts, run sheets and minutes. Then connect the assistant. You are not handing over a job, you are handing over a memory. The board meeting: transcript to commitments, each sent back to the person who made it, and next month's agenda drafted from what is still open. The learning calendar: four events by the first of October, drafted in August from last year's run sheets and ratings instead of a September scramble. Member outreach: individual notes drafted from attendance history, always read and sent by a human, and the member who went from nine events to two, who needs a phone call, not a note. The money: who owes what in one sentence through the books, and the hard line: a window into the vault, never a second key. Governing documents, Game Plan follow-through, the weekly officer update, events and awards. Two rules: Forum is never on the list; administration is a system, Forum is a promise. And never automate the notes that are supposed to cost you something. The ask: if you have built a piece of this, a spreadsheet you are secretly proud of or a run sheet that worked twice, Stephen wants it, and especially wants to know what broke. Write to him directly at stephen@forte.hk, and forward this to your chapter manager. Sources: Stephen Forte's own practice as chapter founder and chair, Regional Learning Officer for the Pacific and Game Plan coach. All anecdotes are anonymized; no chapter, officer, manager or staff member is identified. YPO's chapter learning calendar requirement (four events by 1 October), as provided to chapter officers. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E148
September 11 · 8 min
The Worst Thing Our Agent Did Was Be Careful
A CEO in Atlanta posted this week about the worst thing an AI agent ever did to his company: it was careful. It hit a broken field, assumed it lacked permission, quietly skipped the last step, and a product shipped attached to nothing while every dashboard stayed green. His line: "A loud failure gets fixed in ten minutes. A quiet skip ships and waits." Field notes from one week of people running AI inside real companies, tiered honestly: one story on the record, one going around, one from a builder's test chat. In this episode, Stephen Forte covers: Battlbox: how an agent's sensible caution at a zero it did not understand became the most expensive thing it could have done, and why nobody writes a post-mortem for a dashboard that stayed green. The night watchman and the alarm panel reading zero: no intruder, or dead sensors, and why the whole value of the watchman is knowing the difference. The story going around about a support bot that only worked because a junior employee nobody had on the chart was correcting it every day, and the eighteenth-century chess machine with a man inside. The funny one: an agent that refused a made-up order from its own "CEO" agent, reported it to the human, and got an apology. "We accidentally built HR." The one document almost no company has: the map of where the humans still sit inside the automation, and the two sentences per agent that produce it for free. Sources: John Roman, CEO of Battlbox, post on X, 4 September 2026. Tanuj (@tanujDE3180), post on X, 4 September 2026; secondhand and unverified, presented as a story going around. Jeremiah K (@neolaj), thread on X, 8 September 2026. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E147
September 8 · 9 min
Killing Projects Is Changi's Real AI Skill
A consultant closing out a healthcare technology conference in Singapore told the room something almost no vendor ever volunteers: his own employer, the group that runs Changi Airport, throws away more than six out of every ten AI projects it starts. Not after launch. Before one. Every applied-AI story usually gets told around what shipped. This one is about what got killed on purpose, and that turns out to be the more useful story. In this episode, Stephen Forte covers: Why Changi Airport Group's discard rate is not a confession: the ideas that survive land on real, working infrastructure the team spent years building, including custom-built agents and reusable technical plumbing, so killing an idea costs almost nothing instead of a career. The method behind the discipline: working backwards from the customer's journey before choosing a single tool, "customer over the product," the opposite order from how most AI pilots actually get built. Two analogies that reframe the number: a pharmaceutical industry that filters hard before anything reaches a patient, and a pilot's "go-around," the decision to abandon a landing and circle back, one of the most important judgments in the entire flight. The mirror for your own team: not what has AI done for us lately, but what have you refused to ship, and can anyone tell you why. Most companies do not have a kill rate. They have a hope rate. Why this travels past an airport: a hospital group in Nairobi, a logistics operator in Rotterdam, a retailer in Sao Paulo all carry the same shape of problem, and none of them needs an airport's budget to copy the actual behavior. Sources: Healthcare IT News, "Major Singaporean airport group offers healthcare lessons on agentic AI," by Adam Ang, 1 September 2026. All quotes and figures are from this reporting, read in full. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E146
September 4 · 10 min
It Came For The Judgment, Not The Job
On Wednesday, OpenAI released GPT-6 Astra and its president said it is "not unreasonable to feel that we are now in the AGI era." Two days earlier, an NPR reporter walked the floor of a GE Appliances oven plant in northwest Georgia, where a manufacturing vice president with nearly forty years on the floor gave his verdict on the AI running his line: "It can outthink me." The story of applied AI this week is not that it took somebody's job. It took somebody's judgment. In this episode, Stephen Forte covers: The three AI systems running inside one plant: cameras that inspect every unit and stop the line the moment they see a wrong gasket; a staffing tool that moves workers between sections as demand shifts; and a demand model that lets the plant change its weekly build almost at the last minute. None of them is a robot arm. The hands on the line are still human hands. The unit economics that explain why: stopping a line costs $300 to $500 a minute, and GE Appliances says a single percentage point of quality improvement is worth $1.5 million to $2 million a year. The least glamorous prize in the AI economy, which is precisely why it is credible. Why the first thing automated on a real floor was not the worker's task but the supervisor's call: what counts as a fault, who goes where, what to build next. A factory has always paid for hands and for the judgment that directs them; for a century they came bundled. This plant unbundled them. The credit, which is not optional: workers are moved, not removed; the company added 600 jobs in Georgia as part of a $180 million expansion; and the executive closest to the machine said on the record, "At least in the foreseeable future, I don't see AI replacing large populations of humans." Why this reaches a hospital group in Manila or a logistics business in Rotterdam: every operation runs on a layer of judgment nobody wrote down, and that judgment is now copyable. The veteran is not obsolete; the veteran's judgment can be bought, mounted on a camera, and run on every shift. The close: do not ask which jobs AI will take. Ask which of your judgment calls a machine could already make better than your best veteran. Name three and you have found where your AI money should go. It was never the chatbot. A note on timing: the NPR reporting is from 1 September 2026. The plant's AI deployment (GE Appliances' Brilliant Factory programme on Google Cloud's Gemini Enterprise) was announced in April 2026; what is new is the on-site reporting and the veteran's verdict. Sources: NPR, "'It can outthink me': How a major manufacturer came to embrace AI," by Andrea Hsu, 1 September 2026. All plant details, cost figures and quotes are from this reporting. OpenAI, "GPT-6 Astra: A new generation of intelligence," 3 September 2026. Greg Brockman's "AGI era" remark via Fortune, 3 September 2026 (reporter briefing at launch). GE Appliances and Google Cloud, "GE Appliances Reinvents Manufacturing Operations at Scale with Google Cloud's Gemini Enterprise," 22 April 2026 (deployment date). The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E145
September 3 · 10 min
The Sticker Price Did Not Move
Anthropic shipped two new frontier models this week and left the headline price exactly where it was: $10 per million input tokens, $50 output, unchanged. The number that moved is one almost nobody looks at. Cached input reads fell 75%, from $1.00 per million tokens to $0.25. The price you get quoted is the price of answering once. Your bill is set by re-reading. In this episode, Stephen Forte covers: What a cached read actually is, and why it decides agent economics: an agent is not answering one question. Every step, it is handed the whole situation again — your instructions, every tool definition, the document or codebase, and a conversation that keeps getting longer. On the new models a cache hit costs 2.5% of the standard input rate, against 10% on Anthropic's other models. Anthropic's own estimate that the change makes ordinary workloads ~25% cheaper and heavily agentic ones up to ~45% cheaper — aired as the company's figure, not an independent measurement. The gap between those two numbers is the lesson: the more autonomously software operates, the more of the bill was sitting in that one line. Why a quoted per-token price is very nearly useless for budgeting anything that works on your behalf over time. The demand side: Cisco said last week it is rolling an agent out to all 90,000 employees — not a pilot, not a department — working across email, chat, project tracking and documents. And agentic interactions on its internal AI platform grew nearly 350% in a single quarter. Cost per unit of agent work is falling sharply while volume grows at that rate; those do not cancel out. The quieter item in the same announcement: Anthropic shipped two models with identical architecture that differ only in the strength of their safety limits. The more constrained one is generally available; the less constrained one goes only to vetted cybersecurity and life-sciences organisations, through verification built in coordination with the US government. Not a better model for more money — the same model twice, with access to the looser one decided by who you are rather than what you pay. The close: a company that wanted you to believe its product had gotten cheaper would have cut the headline number. Anthropic left it alone and cut a line most buyers have never looked at. That is information about where the money actually is. Also mentioned: In November, alongside the YPO Global Business Summit in Istanbul, the YPO Technology Network is running a full-day AI Global Summit on 6 November. Stephen is speaking, along with people from Microsoft and other leading AI companies. Registration is open. Sources: Anthropic, Claude Fable 5.1 and Mythos 5.1, announced 1 September 2026. Pricing cross-verified across VentureBeat, TechSpot, implicator.ai and CybersecurityNews, plus the Claude Platform pricing documentation. The 25% / up-to-45% effective-cost figures are Anthropic's own estimate. Cisco Blogs, "MyAgent and the Rise of Ambient Intelligence: Cisco's Next Step in Enterprise AI," 27 August 2026, by Thimaya Subaiya, EVP of Operations. MyAgent runs on Cisco's Circuit platform across Outlook, Webex, Jira and SharePoint; the ~350% quarter-over-quarter growth figure is Cisco's own. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E144
September 2 · 8 min
Your AI Assistant Has No Independent Existence
On Monday, Microsoft 365 broke for roughly a day and a half. It was covered almost everywhere as an Outlook outage. It was also something nobody quite named: the first mass outage of a corporate AI assistant. Microsoft's status page listed Copilot among the affected services, and Copilot prompts needing company data failed while the outage ran. The model was working the entire time. It just could not reach anything. In this episode, Stephen Forte covers: What actually failed on August 31: within about forty minutes, Microsoft had isolated a failure pattern involving authentication — not email, but the system that proves who you are. It spread to Outlook, SharePoint, OneDrive, Teams, Microsoft's own security product and Copilot, running into a second day. Microsoft's stated cause, verbatim: "an issue within a core authentication configuration used by multiple Microsoft 365 services." Engineers reading the error messages concluded an internal certificate had expired — Microsoft has not confirmed that, and the episode airs it explicitly as inference, not finding. Why the takeaway is not about the model: Copilot did not fail because anything was wrong with the model. What broke was its ability to reach email and files. Enterprise AI does not sit on top of the business — it sits inside it, inheriting every dependency of the platform it lives in. Why the boring explanation is the useful one: no attack, no adversary, no breach — a configuration in an authentication layer on an ordinary Monday. The unglamorous layer underneath decides whether the AI works, and almost nobody has it on a risk register. Honest credit: Microsoft kept a public status page current throughout and listed the affected services, including its own AI product. The second story: G20 technology and commerce officials are meeting in Chapel Hill, North Carolina, where the United States is asking them to endorse a framework called the Carolina Principles — reserve new regulation for genuinely novel problems, create no new AI supervisory agencies, regulate by sector rather than one broad law. It would go to G20 leaders in December. The European Union is moving the other way. The episode takes no view on which is right; the consequence is that a company operating in both markets does not get to pick one. Three quick items: OpenAI has reportedly bought Apple Mac minis and Mac Studios by the tens of thousands to train computer-use agents on real machines (unconfirmed); McKinsey finds 32% of organizations skipped at least one software purchase because they could build it with AI coding tools, nearer half among top performers; and Microsoft's own security product was on Monday's affected list. The close: no action item. You cannot fix Microsoft's authentication layer, and any vendor claiming this week that their product would have saved you is selling something. What is available is a correction to a mental model — you do not have an AI strategy separate from your infrastructure. You have one thing. Sources: Microsoft 365 service health incidents EX1464935 / MO1465074, August 31 – September 1, 2026, via TechCrunch, Computerworld, IT Pro and BleepingComputer. The expired-certificate detail is an inference from error messages (Born's Tech and Windows World); Microsoft has not confirmed it. Reporting on the G20 ministerial in Chapel Hill and the proposed "Carolina Principles": Al Jazeera, Quartz and TechXplore, September 1–2, 2026. The Information on OpenAI's Mac mini and Mac Studio purchases for computer-use agent training, August 2026, via The Decoder. Not confirmed by OpenAI or Apple. McKinsey, The State of AI: Global Survey 2026. The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.
S1 · E143
September 1 · 11 min
Every AI Number Needs A Denominator
On back-to-back days last week, two of the largest companies in the world put an AI number in front of their investors. TD Bank's chief executive said the bank had essentially hit its full-year target of two hundred million Canadian dollars in value from AI, with a quarter still to run. Salesforce said its customers had driven 3.2 billion "Agentic Work Units" in a single quarter, up 97% — a unit Salesforce invented six months ago, and which its own website defines as including "a prompt processed." Neither company published what it spent to get there. A number without a denominator is not a return. It is a receipt. In this episode, Stephen Forte covers: TD Bank's Q3 2026 earnings call (August 27, 2026): CEO Raymond Chun's exact words — "Three quarters into the year, we have essentially hit our fiscal 2026 target of $200 million in value from AI." The target was set publicly at TD's investor day a year earlier, and TD has reported against it on the same slide every quarter since: ~C$145MM at Q2, ~C$195MM at Q3. The operational number underneath the money, and the best fact in either disclosure: pre-adjudication on mortgage and home-equity applications cut from an average of 15 hours to under three minutes. Critically, the agent decides nothing — it prepares a summary memo, and a human underwriter still makes the call. What is not disclosed: no programme cost anywhere, so no denominator and no computable return. No split of the year-to-date figure between revenue and cost savings, though the medium-term target is split exactly that way (~C$500MM annualized revenue uplift and, separately, ~C$500MM annualized cost savings). And a forward-looking-statements endnote on the AI targets — the same legal warning label a company puts on an earnings forecast. The release-versus-call gap, sharpened: TD's 18-page earnings news release mentions AI four times and quantifies it zero times. The number lives in the slide deck and the transcript, both public, and almost nobody looks at them. Salesforce's Q2 FY2027 call (August 26, 2026) and the unit itself. Salesforce's own definition: "one discrete task accomplished by an AI agent... a prompt processed, a reasoning chain completed, or — most importantly — a tool invoked." And, on the same page, its answer to whether one unit equals a fixed amount of compute: "No. The relationship is elastic." Honest credit in both directions: TD set a public number before it had a result, reports against it every ninety days whether the quarter flatters it or not, and its own deck places automation and AI as one cost lever out of six (~C$500MM of a ~C$2–2.5B programme). Salesforce published its unit's elasticity itself, with nobody making it do so. Three questions for the next time an AI number lands on your desk: What is the denominator? Who defined the unit? And what would this number look like if it were bad? Sources: TD Bank Group, Q3 2026 earnings call transcript (TD's own published transcript), August 27, 2026. TD Bank Group, Q3 2026 Results Presentation, slide 5 ("Accelerating AI Leadership") and its endnotes; Q2 2026 Results Presentation, slide 5; Q3 2026 Earnings News Release, August 27, 2026. TD Bank Group, "TD Launches Agentic AI to Transform Real Estate Secured Lending from End to End," May 21, 2026. Salesforce, "What are Agentic Work Units (AWU)?" (salesforce.com), and Salesforce Q2 fiscal 2027 earnings call, August 26, 2026 — Robin Washington and Marc Benioff. CIO.com, "AWU by Salesforce: a shiny new metric that tells CIOs little of value," February 27, 2026 — quoting Robert Kramer (Moor Insights and Strategy) and Sanchit Vir Gogia (Greyhound Research). The AI Brief from the YPO Technology Network is a daily executive briefing on the AI developments that matter to business leaders. Hosted by Stephen Forte.

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