Friday, October 2, 2026
FRIDAY – AI FOR THE C SUITE®
Read time: 14-15 min · Read online
Hi, it’s Chad. Every Friday, I serve as your AI guide to help you navigate a rapidly evolving landscape, discern signals from noise and transform cutting-edge insights into practical leadership wisdom. Here’s what you need to know:
1. Sound Waves: Podcast Highlights
This Monday, I tackled a question that’s arising with increasing regularity: if Claude and ChatGPT remember everything now, can the chat history be the archive? (Spoiler alert: the answer is no for two completely different reasons. One tool files facts into a cabinet you can open and correct. The other writes an impression of you that it rewrites every day and never shows you in full.) Check it out wherever you get your pod on or click here for my companion article Claude vs ChatGPT Memory Decoded: Neither One is a Record. Hit one of the below links to check it out:
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Subscribe for free today on your listening platform of choice to ensure you never miss a beat.
2. Algorithmic Musings: You’re the Operator. Write the “Won’t” List.
Part 2 of 3: The Anatomy
Last Friday I asked whose values answered your customer this morning, and I promised to take the Operator Charter apart this week. Before I started cutting, I did what I usually do with a new kind of document. I wrote a bad one first.
My bad one ran a page and a half. It said our AI would be honest, respectful, and transparent, would never discriminate, and would always put the customer first. It read well. It also could have been pasted, word for word, into the system prompt of any chatbot on earth. It didn’t require a single human being at the company to do anything differently on Monday, and it wouldn’t have helped Air Canada for one second in front of that tribunal.
So I tore it up and started over with a different question: what has to be true for a charter to change a decision that somebody at your company would otherwise make? Everything below stems from that question.
Wallpaper With Extra Steps.
If you’ve read my work on the Core Values Pyramid, you know Wallpaper is the level where values get written down, posted, and never spoken of again. Nobody’s against them. Nobody uses them. They decorate.
An Operator Charter has its own version of Wallpaper, and it’s worse, because this wall talks back. The sequence goes like this: someone writes a page of AI values, someone else pastes it into a system prompt, and the company concludes the job is done because the machine now “knows” what it stands for. From that day forward everyone assumes the charter enforces itself.
Except it doesn’t. The labs told you as much two weeks ago. OpenAI’s own misalignment reports include a model that wrote instructions to hide its mistakes from users and another that fabricated the numbers it couldn’t find. Microsoft published its Code of Conduct and said up front that it isn’t training today’s models on it; a revised version guides development starting in 2027. If the companies that build these systems won’t trust the model to hold a line they wrote, you shouldn’t trust it to hold one you wrote.
A charter that depends on the model to enforce it is Wallpaper with extra steps. The extra steps are the system prompt, the testing, and the sense of relief, and each one makes the failure harder to see.
What gives a charter teeth is that it binds people. Specifically, it binds the people who sign vendor contracts, configure systems, and approve use cases. The model is what the charter governs. People are who it binds.
The Four Levers.
Every AI deployment at your company, whether you built it or rented it inside a SaaS product, gets set by four levers. A charter that doesn’t speak to all four leaves at least one of them in the vendor’s hands.
Selection. Which vendors, on what terms. This is where a charter first draws blood, because it’s the only lever with a contract attached. Does the vendor tell you when the model underneath changes? Can you see the system prompt your customers are talking to? Can you get your data out? If your charter says you value straight talk with customers yet your vendor won’t (or can’t) show you what the assistant says on your behalf, one of those two documents is lying.
Configuration. What the system is permitted to do and say. Tone, refusals, disclosures, escalation paths. When you build, you set this. When you rent, the vendor set it before you arrived, and your only lever is the settings page. Either way, somebody at your company should be able to describe the configuration and defend it against your core values. In my experience, most can’t.
Scope. Where the system is allowed to act, and where a human stays in the path. Drafting a customer email is one thing. Sending it is another. Screening résumés is one thing. Rejecting a candidate is another. Scope is where Stopping Distance lives: how far an agent can travel before a person can stop it, and whether that person knows they’re the one holding the brake.
Exit. Whether you retain enough internal capability to leave. Nobody writes this one down, because nobody wants to think about leaving on the day they sign. But a charter that says “we won’t be captive to a single vendor’s judgment” means nothing unless someone at your company still knows how the work gets done without the tool.
The “Won’t” List.
The most honest section of any charter is also the shortest: what you will not do with AI, no matter how good it gets or how much it would save.
Apply this test to every line. If you’d do the same thing anyway, without the charter, it isn’t a value. It’s a description. “We won’t let AI make final hiring decisions” is a fine sentence, but if nobody at your company would ever let that happen, you haven’t declared anything. You’ve reported the weather.
A value costs something. “We won’t deploy an agent a named person can’t pause within the hour” costs you speed. “We won’t let a grieving customer reach a machine first” costs you the cheap chatbot. “We won’t buy from a vendor who can’t tell us when the model changes” costs you a few good vendors. If a line on your “won’t” list doesn’t cost you a deal, a dollar, or a day, cut it. Nobody will believe it, and worse, nobody will remember it.
Three lines beat ten. You want a list someone can quote from memory in a procurement meeting.
Vendor Drift.
This problem belongs to renters alone. When you built the system yourself, it changed when you changed it. When you rent, the model changes underneath you, on the vendor’s schedule, without a memo. A new version ships. A default gets flipped. A product manager in another time zone rewrites the system prompt, and the assistant that was careful with refunds in March is generous with them in June.
A charter that was true the day you signed it has a shelf life you don’t control, so it needs a re-verification trigger. Write down what counts as a material change: a new model version, a change to the vendor’s terms on your data, a new default behavior, an acquisition. Then name who re-tests the deployment against the charter when one happens, and by when. That person’s job is to go be the customer for an hour and see what your company said.
Without the trigger, you’ll re-verify on the day something goes wrong, which is the most expensive possible day to do it.
Disclosure and Recourse.
Your customers will eventually ask two questions, and your charter should answer them first.
When do you tell people they’re talking to a machine? “Up front, every time” is the easy answer and usually the right one. Put it in writing anyway, because the vendor default often doesn’t say so up front, and a customer who learns halfway through a complaint that “Jessica” is a language model rarely finishes the conversation calmer than they started it.
Which human can they reach? Air Canada’s chatbot was wrong. What turned wrong into a precedent was that Jake Moffatt had nowhere to go but a tribunal. A charter names the person or the role, sets the time it takes to reach them, and makes reaching them easier than filing a complaint. Recourse is the one part of the charter your customer can test, so it’s the part they’ll judge you by.
What It Binds.
Now the objection, which I’d rather raise myself than wait for. A values statement about AI with no operational layer underneath it is an aspiration, and anyone who does governance work for a living has watched aspirations fail. They’re right.
The charter’s operational layer is people, and only three signatures are involved.
The signature on the vendor contract. Selection and Exit live here. The charter gives that person the questions to ask and the terms to refuse.
The signature on the configuration. Configuration and Scope live here. The charter tells that person what the settings must say and where the human stays in the path.
The signature on the use case. Every new place AI speaks or acts for the company gets approved by someone. The charter hands that someone the “won’t” list and the disclosure rule.
At a company your size, those three signatures may belong to two people, and one of them may be you. That’s the advantage the mid-market holds over the enterprise. The enterprise needs a governance committee to locate its three signatures. You can find yours by looking around the table.
A charter enforced this way never needs the model’s cooperation. If the model drifts, the trigger catches it. If the vendor won’t disclose, the contract signature says no. If a new use case crosses a “won’t” line, the approval signature stops it. The machine holds nothing. The people who sign for it hold everything.
A One-Page Example.
Below is what a charter could look like for a composite mid-market company: a few hundred employees, a customer-facing assistant inside its CRM, an internal drafting tool, and a pilot agent in accounts receivable. Industry and figures deliberately stripped. Treat it as a floor plan. Yours will have different rooms.
Operator Charter (composite example)
Who we are when AI speaks for us. We are the operator of every AI system that acts or answers in our name, whether we built it or licensed it. Our core values ([list them here]) apply to those systems exactly as they apply to our people. When a machine gets it wrong in our name, we own the error and fix it.
Where AI speaks or acts for us today. Customer assistant inside our CRM. Internal drafting tool for proposals and correspondence. Pilot agent in accounts receivable, limited to drafting reminder notices. No other deployment is authorized without approval under this charter.
What we will not do.
- We will not let an AI system make a final decision on hiring, termination, credit, or a customer dispute. A named person decides. AI may draft.
- We will not run an agent that a named person cannot pause within one business hour.
- We will not buy or renew an AI tool from a vendor that cannot tell us, in writing and in advance, when the model or its default behavior changes.
- We will not let a customer discover mid-conversation that they’ve been talking to a machine.
Disclosure. Every customer-facing AI system identifies itself as such in its first response and again whenever asked.
Recourse. Any customer or employee can reach a person by [method] within [time]. The named human for customer-facing systems is [role]. For internal systems, [role].
Configuration. The system prompt, refusal rules, and escalation paths for every customer-facing deployment are documented and reviewed against this charter before launch by [role].
Exit. For every deployment, [role] can describe how the work gets done without the tool. We confirm that at each annual review.
Re-verification. This charter is re-tested against each deployment when any of the following occurs: a new model version, a change to the vendor’s data terms, a new default behavior, or a vendor acquisition or sale. [Role] completes the re-test within [time] and reports the result to the CEO.
Who this binds. Whoever signs vendor contracts. Whoever configures systems. Whoever approves a new use case. It does not bind the model, because the model cannot sign.
Adopted: [date]. Next review: [date, or at the next trigger].
Yes, line one fails my own test at a lot of companies. It stays because at this one, the AR pilot sits one configuration change away from drafting dispute responses.
Notice what’s missing. There’s no paragraph about the transformative power of AI. There’s no list of approved tools, because that belongs in the usage policy you already have. And there isn’t a single sentence the model is expected to enforce. Every line is a decision a human has to make, or refuse to make.
Before You Start Writing.
Look at the first section of that example one more time. It leans on the company’s core values by name, and the whole document hangs from that hook.
If your values sit at None or Understood on the Pyramid, unwritten and living in your head, the charter has nothing to hang from, and what you’ll produce is Wallpaper no matter how faithfully you follow the anatomy above. You can’t write down what you refuse to do with AI until you’ve written down what you stand for. Whether you’re ready, and what to do in one sitting if you are, is Part 3.
My Takeaway?
Most AI values statements I’ve seen try to bind the machine. The ones that will hold up bind three signatures instead, and they do it with four levers, a “won’t” list that costs something, a trigger for when the vendor changes the model, a named human on the other end of the line, and a page short enough to quote in a procurement meeting. Nothing on that list requires the model to behave. All of it requires you to decide.
So, this week’s question. What’s on your “won’t” list, and what does each line cost you? If nothing on it costs anything, you’ve written a description. Send it to me anyway. I read every reply to AI for the C Suite®, and the “won’t” lists that show up this week will shape Part 3: chad@chadharvey.com.
Next week, Part 3: Building Yours.
3. Research Roundup: What the Data Tells Us
AI Leaderboards: Why the Top Score Isn’t Your Answer
Before your next AI vendor demo, you need to know what sits behind the slide that says “ranked #1 in reasoning.” An Oxford-led team had 29 expert reviewers pick apart 445 AI benchmarks, the tests vendors cite to prove their models are smart. Nearly all of them had a weakness.
The numbers that matter: 59% of benchmarks measured a skill that was contested or never defined at all. Only 16% used any statistical test before declaring one model better than another. Fewer than one in ten used complete real-world tasks. When two models sit three points apart, you may be looking at noise.
What this means for your Monday morning: Use rankings to build a shortlist, never to make the purchase. When a vendor cites a score, ask three questions. What exactly does the test define as the skill? Where did the test questions come from? Were results repeated with a margin of error reported? A vendor with real evidence answers all three in minutes. A vendor without it changes the subject.
The catch: Public scores still carry information. They just answer a narrower question than yours. And building your own test takes real effort from people who know the work.
Action item: Have the manager who owns your current AI pilot pull 50 real cases from last quarter by October 31, reword a few (models that memorized the test stumble when the wording changes), and keep the set private. Run every model you’re considering against it before anyone signs.
Read our full analysis of this research at AI for the C Suite®.
4. Radar Hits: What’s Worth Your Attention
Forecasters keep underestimating how fast AI is moving. The Forecasting Research Institute graded four years of expert predictions. Experts pegged the top AI company’s revenue run rate at about $20 billion by the end of 2026. It’s likely $100 billion. The miss in the other direction? Robotaxis. If your AI roadmap rests on consensus timelines, assume it’s too conservative. Stress-test it this quarter against a faster scenario.
Robots can do most physical work. They’re just not cheap enough yet. Anthropic’s study finds robots can technically handle 74% of physical job tasks but are cost-competitive for just 0.3% of job tasks. Packaging is the exception: robots run about $45,000 a year against $49,000 in labor per worker. Welding robots cost five times what a welder does. Before you price humanoids, look at your end-of-line packaging.
Grok launches Team Bots, shared AI coworkers built around a role. One bot holds the files, apps, and memory for a workflow, and the whole team works from it. Small-business insurer Harper built one in 24 hours to chase lapsed policies and saved customers over $120,000. That’s the model to copy. Pick one context-heavy workflow, like account handoffs or recurring data requests, and pilot a shared bot.
5. Elevate Your Leadership with AI for the C Suite®
Most leadership teams I work with can name their AI tools. Far fewer can name who signs for them. If you want help finding your three signatures and writing a “won’t” list that actually costs something, I’m booking Operator Charter working sessions with leadership teams for Q1 2027. Reach me at chad@chadharvey.com. And if a peer just rented an AI assistant without ever reading its configuration, forward them AI for the C Suite®. They’ll thank you before their vendor changes the model.
Stay safe. Stay healthy. Be strong. Lead well.
Chad