In Microsoft Advertising’s Agentic Playbook, Laurie Sullivan of MediaPost looks into Microsoft’s “agentic commerce blueprint to guide businesses, retailers, and developers when AI agents make purchases on behalf of humans.”

Meaning agents are out there shopping for customers already. Intentcasting anyone?

Laurie explains,

Microsoft’s “Agentic Playbook” focuses on three priorities:

• Getting discovered by the agent (which many brands struggle with today).

• Ensuring the purchase becomes seamless.

• Having the tools to optimize performance of the intended purchase.

Part of the blueprint details a path for marketers to build a 90-day structure for agentic.

Microsoft’s agentic, that is. She goes on:

One Microsoft product marketing director on the call focusing on product feeds said she can already see a major change in consumer behavior — the way people shop….

Microsoft Copilot runs on the same Universal Commerce Protocol (UCP) that many of its larger partners run on, the company said.

The framework connects Copilot with retail, including giants like Target, Ulta Beauty, and Stripe.

UCP founding partners include Google and Shopify.

UCP is new to me. Wikipedia too. But it does have a website: UCP.dev. There it says, “Universal Commerce Protocol (is) the common language for platforms, agents, and businesses (and) provides building blocks for agentic commerce across industries—from discovery to checkout and beyond—allowing the ecosystem to operate through one standard, without custom builds.”

The page goes on to say UCP is “co-developed by industry leaders,” and “built by the industry, to enable seamless agentic experiences. It solves fragmented user journeys that lead to frustrated users and conversion drop off.”

Solves for the seller, that is. Not for the buyer. Yet.

In Under the Hood: Universal Commerce Protocol (UCP), Amit Handa, Google’s Director of Engineering, Google Commerce, and  Ashish Gupta,  VP/GM Merchant Shopping and Engineering Fellow at Google, write,

By establishing a common language and functional primitives, UCP enables seamless commerce journeys between consumer surfaces, businesses, and payment providers. It is built to work with existing retail infrastructure, and is compatible with Agent Payments Protocol (AP2) to provide secure agentic payments support. It also provides businesses flexible ways to integrate via APIs, Agent2Agent (A2A), and the Model Context Protocol (MCP).

UCP is developed by Google in collaboration with industry leaders including Shopify, Etsy, Wayfair, Target, and Walmart endorsed by over 20 global partners across the ecosystem like Adyen, American Express, Best Buy, Flipkart, Macy’s Inc, Mastercard, Stripe, The Home Depot, Visa, Zalando and many more.

Then,

UCP is built to benefit the entire commerce ecosystem

• For businesses: UCP empowers you to showcase your unique product and service offerings at shopping touchpoints across consumer interfaces such as AI Mode in Google Search and Gemini app, and others in the future. With UCP, you own your business logic, and you remain the Merchant of Record. UCP is built for retailer flexibility, and provides an ’embedded option’ that allows you to maintain a fully customized checkout experience from day one.

• For AI platforms: With UCP, you can enable agentic shopping for your audiences. You can simplify business onboarding using standardized APIs while giving them flexibility to use MCP, A2A and existing agent frameworks of their choice.

• For developers: UCP is an evolving open-source standard designed to be community-driven. We invite you to build the next generation of digital commerce with us.

• For payment providers: UCP’s open, modular payment handler design enables open interoperability and choice of payment methods. Through this design, UCP enables universal payments that are provable. Every authorization is backed by cryptographic proof of user consent.

• For consumers: When your favorite brands adopt UCP, it removes friction from product discovery to decision, so you can shop the brands you love, with peace of mind, ensuring you get the best value inclusive of your member benefits.

The last bullet is bullshit, but ignore that. Look at it the consumer side as an empty space where independent customers operate with agents of their own. These agents will roam and engage in the open market. They won’t just be “members” trapped in coercive “loyalty” programs. (Although smart agents can take advantage of whatever privileges might appear in those places too.)

Personal agents are VRM tools. They are the first VRM tools with real power since we started this project two decades ago.

In AI shopping gets simpler with Universal Commerce Protocol updates, Ashish Gupta writes,

Thanks to our partners and community contributors, UCP now provides new optional capabilities including:

• UCP can help make online shopping more intuitive and convenient, thanks to a new Cart option that will let agents save or add multiple items to a shopping cart at once from a single store — just as a shopper typically would.

• UCP adopters will be able to access a new Catalog capability that lets agents retrieve select real-time product details from a retailer’s catalog where necessary — like variants, inventory and pricing.

• Building on existing standards, UCP will also support Identity Linking. That allows shoppers on UCP-integrated platforms to receive the same loyalty or member benefits they would on a retailer’s site when they’re logged in — like pricing or free shipping — making shopping more connected across the web.

Good, but again still just for retailers. Nothing in there addresses a question my wife asked when she first encountered e-commerce in 1995: Why can’t I take my shopping cart from site to site?

Back to Laurie:

On Thursday, Microsoft officially began rolling out “AI Max,” its full suite of features for search advertising campaigns, to all accounts. It optimizes performance across Copilot Search and Bing.

The product provides search term matching that expands reach beyond keyword lists.

It uses keywords, ads, and landing pages, along with intent and contextual signals to find relevant searches campaign might not reach.

It also customizes text by using a campaign’s existing assets and website content to generate and test variations on messages.

The system then selects the most appropriate combinations at auction time.

URL expansion sends people to the page on a brand’s website that best matches their intent.

Instead of always sending traffic to a static landing page, it can route people to the page that best matches what they seek.

With AI Max features turned on, advertisers importing existing search campaigns from Google, for example, will seamlessly carry over into the corresponding Microsoft campaign.

I boldfaced intent because that’s the main force customers bring to the market’s table.

Add intelligence to that. Big AI today has far more market intelligence for customers than it does for companies, because customers are free to roam the whole world’s marketplace, while retailers and their third parties are trapped inside the walls of their own self-interest, offerings, and situations. Also their old mentality: the one that assumes that the best customer is a surveilled and captive one.

We started ProjectVRM twenty years ago next month with a thesis to prove: that free customers are more valuable than captive ones—to themselves and the marketplace. Turns out we couldn’t prove that until AI came along.

AI puts customers at an extreme advantage.  Roger Dunn, Chief Commercial Officer of Thrad, talks about this in a recent  Microsoft Advertising blog post:

When someone asks ChatGPT, Copilot, or Gemini for a product recommendation, the AI assembles a shortlist, usually three to five options, and that shortlist becomes the only consideration set that matters…

The vast majority of consumers still verify AI recommendations before buying. They take that shortlist to Google, to Bing, to a brand website, to YouTube. The verification stage is a confirmation exercise, not an open-ended one. They’re searching for the specific brands the AI mentioned, not starting from scratch…

So trust now operates in two layers.

First, there’s machine trust. From a retailer’s perspective – can an AI agent find you, understand what you sell, and have confidence that your product data is accurate and current? That’s about structured data, reviews, fulfillment reliability, pricing consistency. It’s operational, not emotional.

Second, there’s human trust. When the consumer arrives to verify, does your brand have the credibility, the reputation, the experience to close the deal? That’s the brand equity layer, and it’s not going away.

The brands that win will be the ones who treat product data as a strategic asset while continuing to invest in the emotional signals that make humans want to buy. The mistake is thinking you have to choose.

Product truth comes first signal to matter most, and it’s non-negotiable. AI agents reason over structured attributes: dimensions, compatibility, features, use cases. If those attributes don’t exist as machine-readable data, you’re not even a candidate. In the old world, poor data meant lower conversion. In the agentic world, poor data means you never enter consideration. Consumers aren’t prompting “what’s a good shoe brand.” They’re saying “I’m running a 5K this weekend on mixed terrain and my feet run narrow.” If your catalogue can’t answer that level of specificity, the agent recommends someone who can.

Reviews and third-party signals come second. AI systems synthesise review sentiment to answer highly specific questions. One detailed review explaining how a product performed in a real scenario is worth dozens of generic five-star ratings. Third-party endorsements, expert mentions, and certifications act as trust multipliers that AI increasingly weights.

Fulfillment reliability is third and rising fast. As we move up the automation curve, especially when consumers start authorising agents to purchase within preset rules, delivery reliability becomes a make-or-break signal. If an agent places an order and the delivery fails, the agent learns. Your logistics will become your trust score.

Brand authority is fourth. Still vital, but its mechanism is shifting from emotional halo to verifiable digital identity. Your reputation is increasingly a technical credential that agents use to evaluate trustworthiness.

That’s today, when all customers have to work with are Big AI agents. What happens when people get truly personal AIs, in addition to what the giants give them? These will be AIs that give them knowledge and control over the whole corpus of their personal data, meaning everything in this image:

What you’re looking at in that image is a far more empowered and agentic customer than one who operates only inside the milieu Roger describes. Because personal AI is by the person, not just for the person. This completely changes the game—especially when the customer comes with her own terms of engagement and  her own identity, credentials, policies, and engagement mechanisms. Both will happen. As Joe Mandese put it in MediaPost last November, Imagine Consumers Delegating Their Relationships With Marketers To Agents.

Nothing in marketing as we’ve known it contemplates the implications of full and independent customer agency, because marketing still lives inside the business-as-usual box to which we addressed The Cluetrain Manifesto twenty-six years ago.  Cluetrain said a lot of stuff to that box, but here was the summary statement:

Chris Locke wrote that. Wish he was still around to see personal AI’s reach break corporate grasp.

From inside that old box, what Microsoft talks about looks like this:

retailer → machine-readable offers → agent → customer

The customer’s side looks like this:

customer → machine-readable intentions/terms/preferences → agent → market → company

The view from above is this:

customer → agent ←  market → agent ← company

Just three things happen in markets:

• Transactions
• Conversations
• Relationships

In the industrial age, which is finally ending, business was focused almost entirely on transactions. Still is, for good reason: without transactions we wouldn’t have markets. It was strong there, but weak in the other two.

Conversations were kept to a minimum because they looked like overhead: costly in time and money. Service was pushed off to call centers, and now call center workers are being replaced by AI robots.

Relationships were about “loyalty” programs in which customers were held captive and milked.

In the agentic world, the opportunities for conversation and relationship are immense—and will drive many more transactions.

Customers and companies can collaborate on countless benefits for each other when imarket ntelligence flows both ways. Products, services, and experiences by customers and companies can all improve together. Guesswork is minimized. So are the operational and moral costs of surveillance.

Lots to work on here.

Bonus linkages:

• Jamie Smith (who mentions UCP  here)
• Iain Henderson
• Nitin Badjatia
• The Cluetrain angle

MyTerms is both a privacy signal and a privacy agreement. Moreover, it is a contractual one, and backed by plain old contract law.

As conversations about MyTerms grow more vigorous and expand across business, policy circles, and the academy, two big questions are starting to come up. There are surely more, but le’ts focus on the first two:

1. Why will businesses agree to MyTerms? Meaning: How will MyTerms be good for them? And what are the incentives?
2. How does MyTerms harmonize with GPC (Global Privacy Control) and GPP (Global Privacy Platform/Protocol)?

Here are some answers to #1:

• MyTerms replaces guessing with asking.
• The shortest path to trust is agreement.
• The best personalization happens by customer invitation rather than presumed or grudging consent.
• The best customer data is volunteered, not harvested.
• Businesses win when customers arrive with clear intentions.
• The best terms are ones that work for both customers and companies.
• Privacy is cheaper than surveillance.
• MyTerms turns personal privacy from a bug (the surveillance view) into a feature.
• Trusting customers reveal better information than tracked ones.
• The best agents working on both sides can do more when full trust is established.
• Far more product and service improvements are possible when abundant market intelligence flows both ways.
• Free customers are more valuable than captive ones (a claim that has been our mission to prove since day one, almost twenty years ago)
• Accepting MyTerms gives sites and services more flexibility than they would have now inside the surveillance fecosystem toward which privacy policies have and the GPC have tried to fight and the GPP works to sustain.

To answer #2,  GPC is a simple signal sent by a browser to a website, while GPP is the adtech industry’s (IAB’s) protocol for encoding and carrying personal choices downstream to publishers, ad networks, and other participants in the weird world of pre-MyTerms privacy signaling,  By design, GPP is meant to carry consents rather than contracts, but so far I can’t see any reason the GPP can’t carry information about contracts as well, even though MyTerms excludes or obsolesces the whole surveillance-based adtech fecosystem.

Here is a chart that might help:

Protocol / Standard	Origin / Layer	Primary Role
MyTerms (IEEE 7012)	Personal Agency Layer	Defines machine-readable contracts proffered by the individual to a site/service before further engagement. These contracts, aka agreements, support genuine and binding privacy commitments and bases for mutually respectful and trustful interactions from that point forward.
GPC (Global Privacy Control)	Browser Layer	A simple, binary universal opt-out signal sent in HTTP headers or DOM properties expressing “Do Not Sell/Share My Data.”
GPP (Global Privacy Protocol)	Ad-Tech / Vendor Supply Chain	An encoding and transport framework that ingests signals (including GPC) and translates/transmits them to ad networks and third parties. It might also carry signals that specify MyTerms privacy agreements made by services with individuals

I haven’t added any links yet, because I want to make sure I have all this right first

Nitin Badjatia has been laying out more and more reasons, and ways, that enterprises will adapt to customers, rather than the reverse. Read his work and you can start to see what the middle name of both VRM and CRM will mean in the agentic era that is upon us.  His latest three:

• Nobody Owns the Customer (16 July)
• On Knowledge Graphs and Context Graphs (13 July)
• The Customer’s Contribution in the Agentic AI Era (20 July)

From the latest:

The reason the customer contribution matters most is straightforward. The customer is the only body in the relationship that experiences the full arc of it. The organization knows what it built and why. The product knows how it is being used. Only the customer knows what any of it actually means. What they were trying to accomplish, whether they succeeded, and what they wished the enterprise had asked them about before making the decisions it made. All of that is context, and it has never been available to the enterprise on terms either party could trust.

That is about to change. Customer-side agents, operating under a trust protocol like MyTerms, will make the customer’s own account of the relationship available to the enterprise as a first-class contribution to the context layer. MyTerms provides the missing piece the industry has been circling for years. A bilateral agreement, machine-readable and enforceable, that specifies what the customer is willing to share, what the enterprise is allowed to do with it, and what the customer expects in return. With that protocol in place, the customer’s agent will share context the enterprise has never had access to at any point in the history of customer experience.

What the enterprise will receive is not another data feed. It will be a structured account of the relationship from the customer’s own perspective. Why the product was purchased. What problem it was meant to solve. Whether that problem was solved. What has changed in the customer’s circumstances since. What competing options are being considered. What the enterprise could do to strengthen its standing over time. That is a completely different order of information from anything the enterprise’s own instruments have ever produced, because it is the customer’s own account rather than the enterprise’s interpretation of behavior. The customer will have latitude, through a MyTerms contract, in the depth and breadth of the information to share with both the enterprise and the product/service.

The context also compounds in ways the enterprise-side context cannot. The customer’s agent will remember every interaction with every vendor the customer engages with. It will compare experiences across the customer’s full commercial life and surface patterns the customer might never have articulated on their own. When it shares context with the enterprise, it is offering not just what the customer knows about this relationship, but what the agent has learned across many.

But it won’t happen without MyTerms. So let’s build that out.

The EU’s new Digital Omnibus proposal aims to update and expand the GDPR, notably with Article 88b, which includes this:

A new Article 88b Regulation (EU) 2016/679 (General Data Protection Regulation), for automated and machine-readable indications of individual choices and respect of those indications by website providers once standards are available.

That was written in June 2025. (I’ve boldfaced the phrases that matter.) We now have a standard for exactly what the EU wants and needs: IEEE 7012-2025—Standard for Machine-Readable Personal Privacy Terms. It is nicknamed MyTerms (much as IEEE 802.11 is nicknamed Wi-Fi) and was published by the IEEE in January 2026 after nine years in the making. Here’s the PDF.

Article 6 of the GDPR lists six bases for the  Lawfulness of Processing:

1. the data subject has given consent to the processing of his or her personal data for one or more specific purposes;
2. processing is necessary for the performance of a contract to which the data subject is party or in order to take steps at the request of the data subject prior to entering into a contract;
3. processing is necessary for compliance with a legal obligation to which the controller is subject;
4. processing is necessary in order to protect the vital interests of the data subject or of another natural person;
5. processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;
6. processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child.

I’ve boldfaced the three that matter, and italicised their core distinctions.

The entire adtech business relies on the first and last of these, consent and legitimate interests, as their excuses for tracking people, allowing them to obey the letter of the GDPR while screwing its spirit.

We see consent at work with every cookie notice we click on or click past. And we have no faith that clicks on consent “choices” provide any privacy protection at all. Reasons:

1. Most sites ignore cookie choices.
2. Many sites set cookies even before a cookie choice is made.
3. It’s obvious that adtech is a personalised guesswork business that relies on surveillance, so most of these “choices” are misdirections away from corporate hunger for personal data.
4. We have no record of the “choices” we make (and in many cases, no choice is offered), or any way to audit or dispute compliance.
5. Uninvited and unwanted surveillance is by now so far out of control that cars, TVs, and AI chatbots are all in on the game (and hardly bother with consent notices).

The legitimate interests are advertising and surveillance, which Google, Facebook and the IAB say the world needs, because it funds so much of what happens online.

To the adtech business, personal privacy is a bug, not a feature. The whole business is incentivised to violate privacy, because violating privacy pays. No amount of regulatory oversight will fix that. To adtech, paying fines for privacy violations is just a cost of doing business.

The only fix that will work is what people—customers and citizens—bring to the market’s table. With MyTerms, they can do that.

MyTerms addresses the second of the GDPR’s six legal bases: contract. Put simply, here is what  the MyTerms standard says:

• The person (not a mere data subject) is the first party, and the site or service is the second party.
• The person proffers a contractual agreement chosen from a limited roster posted on the public website of a disinterested nonprofit, such as Customer Commons (which was created to do for personal contracts what Creative Commons does for personal copyrights—and which the IEEE approached with the idea for making MyTerms a standard).
• When the second party agrees, both parties keep an identical record, which supports compliance auditing and dispute resolution. (By preserving evidence, this also creates an infrastructure for dispute avoidance as well.)

The GDPR succeeded by recognising natural persons as holders of rights, but it left intact the industrial age convention in which organisations are the exclusive originators of terms at scale. That’s one reason why persons have remained mere data subjects rather than contractual parties.

Fortunately, the Internet’s base protocols are peer-to-peer. Treating people on the Net as mere “users” and “data subjects” limits their agency. With MyTerms, people acquire a status they yielded when industry won the industrial revolution. (Before the industrial age, surnames—Baker, Müller, Weaver,  Lefebvre, Smith, Marchand, Farmer—signified agency: what people did in the world. That’s just one thing we lost when we became workers, executives, consumers, and users.)

In the natural world, privacy is maintained mostly by tacit agreements. In the digital world there is no tacit, so agreements must become explicit and programmable. This is why contracts are the only way we’ll get real personal privacy in the digital world.

It should also be clear by now that polite requests also don’t work. We tried that with Do Not Track, and by the time it finished failing, the adtech lobby had turned it into Tracking Preference Expression—as if we wanted to be tracked all along.

That main pro-consent lobby is the Interactive Advertising Bureau, or IAB. Among its recommendations for the Digital Omnibus are deleting 88b and  improving consent in various ways, such as  “Revise the proposed stricter consent rules.”

The IAB is blind to the simple fact that people hate being spied on and do what they can to stop it—mainly by turning off ads. By 2015, ad blocking was already the biggest boycott in human history. That boycott rose in direct response to obvious tracking, especially with retargeting. (That’s how one ad or advertiser keeps following you from site to site and app to app.)  And the boycott is much bigger now:

• By Q2 2023, there were 912M active ad-blocking users worldwide, up 11% from Q4 2021. (Source: e/yeo, with more here)
•  1.77 billion people worldwide were blocking ads by Q2 of 2026. (Source: Backlinko, citing DataReportal and e/yeo).
• Privacy-focused browsers (like Brave, Safari, and Firefox) automatically block advertising elements and behavioural tracking scripts by default. This is in clear response to market demand.

The IAB earned all of that. Yet they still see ad blocking and tracking protection as problems to solve rather than clear and constructive signals from the marketplace.

So it should be clear by now that the old brownfield of consent has become a toxic wasteland of surveillance, lost privacy, and minimised human agency—led by an industry that has been hostile to privacy from the start.

In fact, consent is required for what Shoshana Zuboff calls Surveillance Capitalism. That form of capitalism is based on inferred or extracted consent. The only way we can defeat that regime is by re-basing e-commerce on contractual agreements in which customers take the lead. After all, it’s their privacy that needs protection.

The surveillance economy is limited entirely by its methods, which are built around grabbing attention, harvesting data, and guessing at people.

We can replace it with an intention economy that’s based on what customers actually want. The range of those wants far exceeds what companies and their systems can guess at. Far more business, and business improvement, opens up when market intelligence can flow both ways. In the consent/surveillance regime, it can’t, because all relationships are silo’d in sellers’ separate systems, all built to minimize customer interactions, by design. But relationships built on respectful contractual agreements can be far more capacious when those relationships start with forms of mutual trust that whole markets share. That’s what MyTerms makes possible.

Here is a quick outline of some additional benefits.

For customers, the most obvious one is getting rid of cookie notices, which are annoying and not worth the pixels they are printed on.  If a company really does care about personal privacy, it’ll respect personal privacy requirements. This is how things work in the natural world, where tracking people like marked animals has been morally wrong for millennia. In the digital world, however, agreements need to be explicit, so programming and services can be based on them. MyTerms does that.

For business, MyTerms has lots of advantages:

• Reduced or eliminated compliance risk
• Competitive differentiation
• Lower customer churn
• A basis for real rather than coerced relationships
• A basis for better signalling in both directions
• Reduced or eliminated guesswork about what customers want, how they use products and services, and  how both might be improved

Lawyers get a new market for services on both the buy and sell sides of the marketplace. Companies in the CMP (consent management platform) business (e.g. Admiral and OneTrust) have something new and better to sell to enterprises (and perhaps to people as well).

Lawmakers and Regulators can start looking at the Internet and the Web as places where freedom of contract prevails, and contracts of adhesion (such as what you “agree” to with cookie notices) are obsolete.

Developers can have a field day (or decade). Look for these categories to emerge

• Agreement Management Platforms — an evolutionary step forward from consent management platforms.
• Customer Relationship Management (CRM) – Make its middle name finally mean something.
• Customer Data Return (CDR) – Give, sell back, or share with customers the data you’ve been gathering without their permission since forever. Talking here to car companies, TV makers, app makers, and every other technology product with spyware onboard for reporting personal activity to parties unknown.
• Vendor Relationship Management (VRM) Tools and services — a customer hand for CRM to shake.
• Platform Relief –  Free customers from the walled gardens of Apple, Microsoft, Amazon, and every other maker of hardware and software that currently bears the full burden of providing personal privacy to customers and users. Those companies can also embrace and help implement MyTerms for both sides of the marketplace.
• Personal AI (pAI)– Till and plant a vast new greenfield for countless companies, old and new. This includes Apple (which can make Apple Intelligence truly “AI for the rest of us” rather than Siri in AI drag), Mozilla (with its Business Accelerator for personal AI) , Kwaai (for open source personal AI), and everyone else who wants to jump on the train.
• Big meshes of agents, such as what these developers are all working on.

In the marketplace, we can start to see all these things:

• VRM + CRM will flourish, as described by Iain Henderson (one of MyTerms’ authors) in Towards Network-Based Ecosystems.
• We should expect improvements to digital public infrastructure, as relationships move out of Big Tech’s silos and into distributed relationship frameworks based on the Internet’s base peer-to-peer protocols.
• Predictions I made in The Intention Economy: When Customers Take Charge (Harvard Business Review Press, 2012) and Tim Berners-Lee made in the Attention vs. Intention chapter of This Is for Everyone: The Unfinished Story of the World Wide Web (Farrar, Straus and Giroux, 2025) will finally come true.
• There will be new dances between customers and companies. (“The Dance” is a closing chapter of The Intention Economy.)
• New commercial ecosystems can grow around a richer flow of useful information in both directions, based on shared interest and trust between customers and companies.
• Surveillance capitalism will be obsolesced — and replaced by an economy aligned with personal agency and mutual respect from contractual partners.

And much more.

So it would be helpful for the European Commission to expand its scope from protecting data subjects to empowering first parties. They can do that by welcoming MyTerms in the Omnibus Directive, expanding human agency into a new greenfield where boundless positive outcomes can flourish.

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Drafts of myterms agreements are currently posted at MyTerms.info, which is a project of Customer Commons and MyData Global. You can also read more about MyTerms in writings by Iain Henderson, Nitin Badjatia, and me.

We also invite you to join the ProjectVRM list, where we can converse and collaborate on moving MyTerms forward.

Last month, Devon Loffreto shared some takes on how this website might look with some big tweaks. Check ’em out:

One post.

On MyTerms.

I think they’re brilliant.

We do need a refresh, and I’ve been working with our friends at WordPress on that. The main constraint is that we need to base the site on a WordPress theme of some kind. I invite suggestions.

A recent post by Simon Taylor on X expresses something important about AI agents and markets: if an AI agent arrives in a market with a clear mandate—

Get me X. Budget Y. Constraints Z.

—it obsolesces business-as-usual for digital marketing.

See, all of martech and adtech starts with the assumption that human intent is fuzzy and manipulable—and that the best customers are captive and manipulated. Let’s look at this from three angles, which are also the three things that happen in markets:

• transactions
• conversations
• relationships.

On the transaction side, companies invest heavily in tracking people, analyzing their behavior, targeting ads at them, and then (in many cases) rationalizing extremely wasteful results. Plus, of course, discounting or ignoring boundless negative externalities, such as the annoying people to new extremes and massively abusing personal privacy. (In fact, the system treats absent personal privacy as a base feature.) Anyway, the entire surveillance-based advertising fecosystem exists to guess what people want, or to influence what they might want.

On the relationship side, all we have so far is on the sell side: CRM, for Customer Relationship Management, and CX, for Customer Experience. We’ve been trying here to build (or to encourage building) systems for VRM, for Vendor Relationship Management, to give CRM customer hands to shake. But, in VRM’s absence, CRM is all we’ve got. One hand clapping. Or slapping. Or pushing prospects into a funnel.

What many of us, including Simon Taylor, suggest is facilitating conversation through AI agents. Simon’s case, specifically, is that an agent representing a person doesn’t need to be guessed at. It already knows the user’s intent. So there is no attention to capture and no desire to manufacture or manipulate. The demand signal is clear from the start. That’s why he says agents can collapse the attention economy.

The underlying shift in this direction has been visible for a long time. In The Intention Economy: When Customers Take Charge (Harvard Business Review Press, 2012), I argued that markets work best when customers drive them with clear signals of demand, rather than when sellers try to infer demand through surveillance and unwelcome persuasion. I also said markets can be far richer and more vital when customers and companies operate as equals, with relationships based on mutual interest rather than forms of coercion (such as “loyalty” programs that aren’t).

The work of Vendor Relationship Management (VRM) has been about correcting that imbalance.

Instead of companies managing relationships with customers through CRM (Customer Relationship Management) systems, we need customers able to manage relationships with vendors through VRM (Vendor Relationship Management) tools.

Note that relationship is the middle name of both CRM and VRM. Markets are not just about transactions. They are about relationships that continue over time.

That’s why a working intention economy will involve far more than simple buying transactions.

As Esteban Kolsky once put it, companies often focus almost entirely on the “buy cycle.” But customers live mostly in the “own cycle”—the long period of using, maintaining, fixing, improving, and learning from the products and services they already have:

In an intention economy, intelligence about that experience flows both ways between customers and companies. I wrote about this recently here:

Market intelligence that flows both ways.

VRM has long described one key mechanism for this: intentcasting, where customers signal their needs directly to the market rather than being targeted by guesses and ads.

Agents may make this far more feasible than it was when we first started talking about VRM nearly two decades ago.

But there’s an important point that often gets missed in current AI discussions.

The agency that matters most is the person’s, not the agent’s.

A personal AI agent is an instrument—like a phone, a computer, or a car. It acts on behalf of the individual, but the intention behind it must be the person’s own.

And that leads to another requirement:

The only truly personal agents will be owned and operated by individuals.

We don’t have that yet.

What we have instead are assistants that live inside corporate systems—helpful, sometimes impressive, but ultimately operating within feudal structures run by very large companies.

They are, at best, friendly suction cups on the tentacles of giants.

Individuals may well rent or borrow AI models from those giants. But the agents that represent us should operate inside our own environments, in our exclusive interest, rather than inside corporate systems whose interests may diverge from ours.

In other words, our agents should live in our own castles, not inside someone else’s kingdom.

When that happens—when individuals can show up in markets through tools they control—then the deeper shift becomes possible: from guesswork based on surveillance of captive customers to servicing self-qualified leads from free customers in the open marketplace.

Markets then begin to work the way markets are supposed to work: with demand and supply meeting in the open, in relationships that can last far beyond a single transaction.

This is also where work like MyTerms and the emerging ecosystem around personal AI becomes important. If individuals are to operate in markets through their own agents, those agents need ways to assert the person’s terms, preferences, and boundaries in forms that other systems can recognize and respect.

That is the direction VRM has been pointing for nearly twenty years: toward a world where individuals can arrive in markets with their own tools, their own data, and their own terms—and where markets can finally listen.

When that happens, markets will stop guessing what customers want—and start hearing them.

[Later… I actually wrote this post about a month ago, and put off publishing it while I worked on other things. Meanwhile, Adrian Gropper posted A Fork in the Road, which is required reading. I thank him for reminding me in the comments below, and for being a founding participant in ProjectVRM—going back to our earliest meetings almost 20 years ago.]

Interesting how old posts get new traffic. The heaviest traffic this morning is to Health Care Relationship Management, which ran almost nineteen years ago. That post concerned a Steve Lohr story in the NY Times titled Google and Microsoft Look to Change Health Care.  The gist:

The Google and Microsoft initiatives would give much more control to individuals, a trend many health experts see as inevitable. “Patients will ultimately be the stewards of their own information,” said John D. Halamka, a doctor and the chief information officer of the Harvard Medical School.

The initiatives were Google Health  and Microsoft Healthvault. Never mind why they died. Those links will tell you. What matters more is what I said way back then: The key, as with all VRM projects, is that the solution needs to be anchored on the customer side — in this case the patient side — of the relationship.

As it happens, Adrian Gropper, techie and MD, was on this case long before Google and Microsoft showed up to waste $billions failing to solve a problem they could only compound. And he’s still at it, with HIE of One and related efforts. Here is his Substack. These subjects will be on the floor at VRM Day and IIW later this month. VRM for healthcare will save the world $billions, in addition to countless lives.

Here’s Adrian’s latest.

There is no organisation on Earth with a more audacious purpose than this one:

This isn’t shooting for the Moon. It’s shooting for the whole world of business.

What Customer Commons wants to restore isn’t just what was lost when the Internet got real. (For example, privacy.) Customer Commons also wants to restore personal agency that was lost when Industry won the Industrial Revolution. That’s when jobs replaced work, labour replaced teams, and customers became consumers.

That last shift, Jerry Michalski explains, was from human beings to “gullets with wallets and eyeballs.” After that shift, freedom of contract in marketplaces was enjoyed only by businesses. Not by gullets.

Customer Commons was created to change that. It was spun out of ProjectVRM as a 501(c)3 nonprofit in 2013, shortly after Harvard Business Review Press published  The Intention Economy: When Customers Take Charge. That book specifically gave Customer Commons the job of doing for personal privacy terms what Creative Commons did for personal copyright.  And to do it by making privacy a contract between customers and businesses, rather than a “consent” to whatever the hell businesses wanted to shove down our gullets. (For example, with interruptive cookie “choices” that really aren’t and leave no audit trail.)

Work on that began in 2017, when the IEEE approached Customer Commons with an offer to host development of a standard for machine-readable personal privacy terms. That standard, officially called IEEE 7012-2025, and nicknamed MyTerms, was published this past January, concluding nine years of work.

Now what?

MyTerms is a great start toward completing Customer Commons’ audacious mission. Here are some goals we will achieve when that mission is accomplished:

1. VRM will be a business category, welcomed and engaged by CRM and CX functions on the sell sides of markets.
2. We will have proof that free customers are worth more than captive ones—to companies they engage, to whole markets, and to themselves. This was ProjectVRM’s original mission in 2006.
3. The intention economy will materialize when voluntary signaling from customers to companies outperforms and obsolesces surveillance as the primary means for companies to obtain data about customers.

MyTerms is required for all three, because a contract is the only way for companies to commit to respecting personal privacy, and MyTerms is the standard for doing that.

So the first challenge is to make Customer Commons viable as the first mover in establishing MyTerms in the world.

The second challenge is to make Customer Commons substantial enough to lead work toward all three of the challenges listed above. Customer Commons won’t be the only entity working on those. In the U.S., Consumer Reports has already stepped forward as a natural ally.  MyData Global is partnering with Customer Commons in standing up the MyTerms Alliance, which is HQ’d in Europe. There are many other potential partners, such as Mozilla and the EFF.

There is development work on MyTerms already. You can learn more about those at VRM Day, IIW, and AIW, which run M-F through the last week of this month (April 27 to May 1) at the Computer History Museum in Silicon Valley.

Here are other ideas that have been floated in the past for Customer Commons:

1. Customers Union. Being for customers what the AARP is for retired people. Only bigger, because it would include everybody who is a customer of anything. This isn’t far from Consumers Union, which begat Consumer Reports, and is now its advocacy group.
2. CustomerCon. A trade show with company booths run by customers, to which companies are invited as guests. Key feature: no complaining. Guest companies are treated only to positive and constructive ideas. HT to Tim Hwang for helping come up with that one.
3. Omie. A tablet with apps free of Google and Apple. HT to Iain Henderson.
4. The ByWay, a new path for local e-commerce.
5. The Free Customer Award. This would be given to companies that value free customers and do nothing to entrap them. The canonical example described in The Intention Economy is Trader Joe’s. But there are others. In-N-Out Burger, for example.

I share those only to give you an idea of how big and influential Customer Commons might be, and how it’s possible to have fun making a new and better economy happen.

We’re not at Square One. Customer Commons is an extant nonprofit, has an energetic board, and a huge accomplishment by getting MyTerms finished. What it needs now is to build out a working organisation. How can we do that?

Let’s look at how Creative Commons got rolling in 2002 and kept moving after that. Here is what I’ve found in diggings so far—

• The History of Creative Commons in Wired (December 2011) says, “An hour after the court’s decision was announced, the William and Flora Hewlett Foundation presented Creative Commons with $1,000,000 to launch the movement.” The case was Eldred v. Ashcroft.
• In 2008, there was a successful funding challenge from Hewlett: “The 5×5 challenge, issued in honor of Creative Commons’ fifth birthday, called for the organization to find five funders to each promise five years of support at $500,000 per year. In addition to the Hewlett Foundation, Creative Commons received pledges of $500,000 in yearly support for five years from Omidyar Network, as well as from an anonymous European trust. Google has pledged $300,000 in support renewable for five years, while Mozilla and Red Hat have each pledged to contribute $100,000 annually for five years. The final block of support comes from the board of Creative Commons, which has promised to personally raise or contribute $500,000 to the organization annually for five years.”(Source: Creative Commons Newsletter No.5, February 2008)
• A Creative Commons  announcement in April 2008 said, “We’re thrilled about a major new grant of $4 million from the William and Flora Hewlett Foundation, consisting of $2.5 million to provide general support to Creative Commons over five years, as well as $1.5 million to support ccLearn.”
• A MacArthur grant search reports a total of $3,225,000 provided between 2002 and 2022:
  • $750,000 in 2005 to support general operations for three years
  • $500,000 in 2007 to support Science Commons for two years
  • $700,000 in2008 to support general operations and an endowment campaign for three years
  • $25,000 in 2015 to provide travel and other support for attendees of the Creative Commons Global Summit in South Korea, for two months. The meeting was also funded in part by the Institute for Museu m and Library Services and th e Gates Foundation, and by the Korean Ministry of Culture, Sports and Tourism ($25,000), Mozilla ($10,000), and the Wikimedia Foundation ($10,000).
  • $50,000 in 2022 to support dedicated programming on open journalism issues at the 2023 Global Summit, “which is an annual event that brings together educators, artists, technologists, legal experts, and activists to promote the power of open licensing and global access.”

So, by inference, the phases were roughly this:

• Launch (2001–2002) $1M of initial funding
• Early build-out (2002–2004) +$1–3M with  additional foundation support
• Continuous operations (2005 onward) at ~$1–3M/year

That gives us an idea of what we need to raise. (Given inflation, multiply those numbers by 1.5x.)

I’ll tell you more when I find out more. Meanwhile, watch this space. Better yet, jump in and help out.

 

 

 

Nor can CRM. Not really. The middle name of both is Relationship, and those require respect for each other’s boundaries. We don’t have that yet online, and can’t without working standards (hello MyTerms), tech, and norms. In fact, the opposite prevails: extreme exploitation of absent personal privacy.

Helen Nissenbaum has been teaching us that for decades, and working on solutions. One is Adnauseum, which may be on your browser already.  It works (says that last link) “by automating ad clicks universally and blindly on behalf of its users. Built atop uBlock Origin, AdNauseam quietly clicks on every blocked ad, registering a visit on ad networks’ databases. As the collected data gathered shows an omnivorous click-stream, user tracking, targeting and surveillance become futile.” In another word, obfuscation.

And that’s what Helen will unpack when she speaks in our salon series here at Indiana University next Tuesday at 4 pm Eastern, and on Zoom. Her title is Why Obfuscation is (still) Needed (more than ever). Here’s the flyer, with the registration and Zoom links:

And in case you don’t click on that, here it is again.

See you there.

In the dawning decades of our new Digital Age, the news business has shrunk from a galaxy of bright stars to a loose collection of white dwarfs glowing in otherwise dark empty spaces. The empty spaces are called  “news deserts.”

In the meantime (at least in the US), the redstream is the new mainstream, while more and more people get news (or what passes for it) from social media and each other. Countless sources are also faked up by AI.

Less metaphorically, the news business has de-institutionalized. How can we re-institutionalize it in digital ways that can also be trusted?

I suggest we start by spinning up News Commons that work with the fewest possible intermediaries between people and sources, and value exchanges that reward everyone.

Some background:::

1) The Dying Galaxy

Here’s how bright stars have turned into white dwarfs:

1. Stopped Presses: There are now fewer than 1,000 daily newspapers left in the U.S. Over 50 million Americans now live in news deserts.
2. Radio Silence: CBS News Radio—the oldest and most august of all the syndcated broadcast news sources— will be gone in May 2026 after a 99-year run. Meanwhile, Public Radio (NPR et al.) faces a “shrinking pie” problem: ratings (dig around here) remain steady or are growing only because stations hold larger shares of a rapidly dwindling over-the-air audience.
3. Cut Cables: Cord-cutting continues, as viewing moves from cable to Internet, and from live to on-demand streamed entertainment. In the midst of this shift, cable news is morphing from mainstream to redstream. Specifically, CNN is moving rightward under the Ellisons, while Fox News stays as right as they were, and MSNBC under its new MS NOW brand continues to glow dimly at the left end of the ratings. None come close in popularity to any of the top news commentary podcasts. Anyway, cable news is transitioning from a collection of leanings (center, left, and right) to highly partisan amen corners with shrinking audiences.
4. Thinning Air: Over-the-air TV (what we still call stations, with channel numbers) is now called “linear,” whether it’s from a connected antenna or from a cable screwed into the same jack on the back of a TV. That category is also in decline, a victim of the same viewing shift to streaming services (now less often called over-the-top, or OTT, now that the bottom—linear TV—is fading away).
5. Babes in New Woods: News is still being consumed, though it’s hardly hard  news or from the media we knew when all the stars were bright and mostly trusted. Especially for young people. Lots of stats at both those links. The bottom line is that none of that flow is from the old stars. At least not directly.

Nearly all coverage of changes in the dimming news galaxy concerns one or more of the five factors listed above. Some of that coverage (most notably from the Nieman Journalism Lab) is about innovations. To mix metaphors a bit, while some of these innovations look like greenfields, none of them look very large. (More credit where due: At least these efforts, as the Quakers say, improve on the silence.)

2) MyTerms (IEEE 7012) and the Agentic Shift

Today, the news world is mostly hidden behind permission walls. Inside those walls, absent personal privacy is exploited to extremes almost nobody will contemplate or admit to.  (Here’s a PageXray of Wired.com—one of the “good” guys.) For a fig leaf over the hard-ons walled garden barons have for personal data, visitors knocking on front doors must yield to demands in the form of misleading cookie notices and in crap like this:

The ProjectVRM community has written a lot about this over many years. But now, thanks to our work with Customer Commons since 2012 and the IEEE since 2017, we have IEEE 7012 (MyTerms): a standard that flips the script on privacy-as-bullshit by giving individuals a way to proffer their own damn privacy terms as binding contracts, with agents working for both parties. Specifics:

• Personal AI Agents: Under MyTerms, individuals operate through agents that can range in complexity from browser plug-ins to private AI agents. These agents have a sole responsibility to the person, proffering and signing agreements, and keeping auditable records of them.
• Reciprocal Agency: On the other side, news providers use their own agents tto choose from the person’s roster of privacy agreement choices (on the Creative Commons model). This machine-to-machine handshake replaces the deceptive, unfair, and un-auditable non-agreements we get with cookie notices and shit such as we see in the image above.
• Unlocked Possibilities: Unlike corporate AI agents designed to keep people inside a walled garden (one cause of the zero-click problem), a personal AI agent can get the requested news item after a MyTerms agreement is signed, and then participate in a whole new value exchange system that works for everyone. For example, should a further agreement be reached (such as one for a micropayment or an acceptable subscription (also built atop MyTerms) the personal AI agent can both obtain the requested news and work out forms of compensation. In this new system, personal data will be shared on an as-needed and trusted basis that continues to assure personal privacy. This can be done in ways that preserve the open Web and create settlement systems that work for all involved (and not just for sellers and the platforms that trapped them in the past).
• Downstream Economic Benefits: When use-value and sale-value are both exchanged on terms that work for all involved, a news ecosystem can be built that rivals the old news galaxy, but with many more bright stars and fewer dark spaces. It will also obsolesce the current all-dwarf system, which is based on customr capture, constant surveillance, and algorithmic guesswork that annoys or offends everyone involved.

3. The New News Commons

To maximize both use-value and sale-value, our goal here is an ecosystem with maximized agency on both sides, and the fewest and simplest intermediaries.

• From redstreams and bluestreams to wide open mystreams: Partisan news at the personal level (look at all those podcasts and blogs) has proven that decentralized, on-demand media are highly resilient. The task now is to multiply and disintermediate both consumption and production. This is required especially at the local level, where realities on the ground (e.g., weather and potholes) tend not to be partisan. What we want here is a common space governed by shared standards (and Ostrom’s principles) rather than algorithmic guesswork by unaccountable giants and their grudging dependents.
• The Nonprofit Pivot: Local digital-first nonprofits now represent over 50% of the Institute for Nonprofit News (INN), providing a model for news as a public good.
• The New Frontier: When you zero-base service and business models on agreed-upon privacy that starts with personal agency and respect for it, anything is possible. (By the way, this is what we’ve had in the natural world since we traded stones for fish. Just because we are still as naked on the Net as we were in Eden doesn’t mean we can’t clothe ourselves and get on with business.)

Feature	Dying Star News System	Bright Star News Commons
Privacy	Corporate “consent” (tracking)	MyTerms (User-Proffered Contract)
Agency	Dependent “users”	Independent readers, listeners, and viewers with loyal agents
Distribution	Centralized walled gardens with paywalls and coerced subscriptions	Open and independent consumers and producers creating use-value and sale-value exchanges that reward both sides

I could go on, but I want to get this up before I get on another airplane. Meanwhile, contact me by email (first name at last name dot com) or in the comments with ways to improve this. Thanks!

You’re reading this on a machine with an operating system: Linux, Windows, MacOS, iOS, or Android.

But that’s not your OS. It’s your machine’s.

How about one for you, that runs on your machine but is entirely yours? Let’s call it a Personal OS, or a POS.

The POS will have a kernel onto which abilities (not just applications) can be added. An extreme example of how this might work is Neo learning ju jitsu in The Matrix:

That OS amplified Neo’s own intelligence, in his own head. We’re far from that today. But we can at least add abilities to a POS of our own. Those too can give us more agency of many kinds.

To my knowledge, there is only one POS so far. It’s called pAI-OS (Github code), and it’s led by Kwaai.* To my knowledge, pAI-OS is the first and only truly personal operating system. (If others do the same, let me know and I’ll talk those up too.) And it is built to run our own AIs. Let’s call them PAIs, where the A can mean amplified or augmented (sourcing Doug Englebart for the latter).

So, what kind of abilities are we talking about?

Let’s start with something that could hardly be more mundane and important: memory.

In Laws of Media, Marshall McLuhan said (five decades ago) that computing promises “perfect memory—total and exact.” For many millennia, our species has been outboarding memory through speech, the written word, and collecting all of that in libraries and museums. And now, in the digital age that dawned with microcircuits and the Internet, we now occupy a digital world where everybody can publish whatever they want. To peruse that, we made search engines. Those ruled from the late ’90s until approximately yesterday, when AIs took over servicing our interest in answers to questions. Google, Microsoft, ChatGPT, Perplexity.ai, and others have moved into a space we might call AI answerware.

Running all that answerware are corporate AIs. Lets call them CAIs. Nothing wrong with CAIs, but also nothing personal, because they are not ours. I explain the difference in Personal vs. Personalized AI. Here’s a graphic from that post showing a bit of what abilities might run on your PAI:

PAIs can extend our own memories by accumulating personal stuff we need to know better, and our ability to meet, access, and use the external abilities of the CAI world. So we’ll have our agents + their agents, working together.

For an example of how that might work, take a look at The most important standard in development today: P7012: Standard for Machine Readable Personal Privacy Terms, which “identifies/addresses the manner in which personal privacy terms are proffered and how they can be read and agreed to by machines.” After seven years with a working group, it is now in the IEEE editing and approval mill, edging toward becoming a finished standard by next year. It works like this:

Here your agent (a PAI, represented by the ⊂ symbol) proffers your privacy terms (here is one example) to a corporate agent (which might or might not be a CAI, but is still represented with the reciprocal symbol ⊃. (This should be familiar to ProjectVRM veterans as the r-button. We may finally get to use it!)

The ceremony here is the exact reverse of what we have today with the cookie popovers on most website home pages. This can and should be done ⊂ to ⊃. So should signing and recording the agreement, or the choice of the site, should it tell you to screw off. (An agent running on your PAI will record that diss.)

I also bring this up because it will be a key required ability—not just for you and me but for the world, starting with Europe, where the GDPR lists six lawful bases for processing personal data. They begin—

(a) Consent: the individual has given clear consent for you to process their personal data for a specific purpose.
(b) Contract: the processing is necessary for a contract you have with the individual, or because they have asked you to take specific steps before entering into a contract.

By now everyone knows that (a) Consent has failed. It’s an expensive and meaningless dance, with high cognitive (mostly cynical) overhead, and almost no accountability. Now they’re ready for (b) Contract, especially in ceremonies where the individual (not a mere “user”) takes the lead.

I believe there is less limit to what each of us can do with a PAI than there is to what we can do with a laptop or a phone. Because our PAI is our own. It runs on a deeper machine OS, but is not limited by that. Your PAI, running on your POS, may prove to be the first truly personal layer ever put on a machine OS.

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*Full disclosure: I am now the Chief Intention Officer there. At this stage, it’s a voluntary position.

On a scale of one to ten, how do you rate the  Customer Experience Management (CEM) business?

I give it a zero.

Have you noticed that every service comes with a bonus survey—one you answer on a phone or fill out on a Web page? And that every one of those surveys is about rating the poor soul you spoke to or chatted with, rather than the company’s own crappy CEM system?

I always say yes to the question “Was your problem resolved?” because I know the human I spoke to will be punished if I say no.  Saying yes to that question complies with Don Marti‘s tweeted advice: “5 stars for everyone always—never betray a human to the machines.”

The main problem with CEM is that it’s all about getting service to scale across populations by faking interest in human contact. You can see it all through McKinsey’s The CEO Guide to Customer Experience. The customer is always on a “journey” through which a company has “touchpoints.”

Oh please.

IU Health, my primary provider of health services, does a good job on the whole, but one downside is the phone survey that follows up seemingly every interaction I have with a doctor or an assistant of some kind. The survey is always from a robot that says it “will only take a few minutes.” I haven’t counted, but I am sure some of those surveys last longer than the interaction I had with the human who provided the service: an annoyingly looooong touchpoint.

I wrote Why Surveys Suck here, way back in 2007. In it, I wrote,  “One way we can gauge the success of VRM is by watching the number of surveys decline.”

Makes me cringe a bit, but I think it’s still true.

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The image above was created by Bing Creator and depicts “A hellscape of unhappy people, some on phones and others filling out surveys.”

Most AI news is about what the giants (OpenAI/Microsoft, Meta, Google/Apple, Amazon, Adobe, Nvidia) are doing (seven $trillion, anyone?), or what AI is doing for business (all of Forbes’ AI 50). Against all that, personal AI appears to be about where personal computing was in 1974: no longer an oxymoron but discussed more than delivered.

For evidence, look up “personal AI.” All the results will be about business (see here and here) or “assistants” that are just suction cups on the tentacles of giants (Siri, Google Assistant, Alexa, Bixby), or wannabes that do the same kind of thing (Lindy, Hound, DataBot).

There may be others, but three exceptions I know are Kin, Personal AI and Pi.

Personal AI is finding its most promoted early uses on the side of business more than the side of customers. Zapier, for example, explains that Personal AI “can be used as a productivity or business tool.”

Kin and Pi are personal assistants that help you with your life by surveilling your activities for your own benefit. I’ve signed up for both, but have only experienced Pit,” or “just vent,” when I ask it to help me with the stuff outlined in (and under) the AI-generated image above, it wants to hook me up with a bunch of siloed platforms that cost money, or to do geeky things (PostgreSQL, MongoDB, Python on my own computer. Provisional conclusion: Pi means well, but the tools aren’t there yet. [Later… Looks like it’s going to morph into some kind of B2B thing, or be abandoned outright, now that Inflection AI’s CEO, Mustafa Suleyman is gone to Microsoft. Hmm… will Microsoft do what we’d like in this space?]

Open source approaches are out there: OpenDAN, Khoj, Kwaai , and Llama are four, and I know at least one will be at VRM Day and IIW.

So, since personal AI may finally be what pushes VRM into becoming a Real Thing, we’ll make it the focus of our next VRM Day.

As always, VRM Day will precede IIW in the same location: the Boole Room of the Computer History Museum in Mountain View, just off Highway 101 in the heart of Silicon Valley. It’ll be on Monday, 15 April, and start at 9am. There’s a Starbucks across the street and ample parking because the museum is officially closed on Mondays, but the door is open. We lunch outdoors (it’s always clear) at the sports bar on the other corner.

Registration is open now at this Eventbrite link:

https://vrmday2024a.eventbrite.com

You can also just show up, but registering gives us a rough headcount, which is helpful for bringing in the right number of chairs and stuff like that.

See you there!

 

I’m in a discussion of business constituencies. On the list (sourced from the writings of Doug Shapiro) are investors, employees, suppliers, customers, and regulators.

The first three are aware of their membership, but the last two? Not so sure.

Since ProjectVRM works for customers, let’s spin the question around. Do customers have a business constituency? If so, businesses are members by the customer’s grace. She can favor, ignore, or more deeply engage with any of those businesses at her pleasure. She does not “belong” to any of them, even though any or all of them may refer to her, or their many other customers, with possessive pronouns.

Take membership (e.g. Costco, Sam’s Club) and loyalty (CVS, Kroger) programs off the table. Membership systems are private markets, and loyalty programs are misnomered. (For more about that, read the “Dysloyalty” chapter of The Intention Economy.)

Let’s look instead at businesses that customers engage as a matter of course: contractors, medical doctors, auto mechanics, retail stores, restaurants, clubs, farmers’ markets, whatever. Some may be on speed dial, but most are not. What matters in all cases is that these businesses are responsible to their customers. “The real and effectual discipline which is exercised over a workman is that of his customers,” Adam Smith writes. “It is the fear of losing their employment which restrains his frauds and corrects his negligence.” That’s what it means to be a customer’s constituent.

An early promise of the Internet was supporting that “effectual discipline.” For the most part, that hasn’t happened. The “one clue” in The Cluetrain Manifesto said “we are not seats or eyeballs or end users or consumers. we are human beings and our reach exceeds your grasp. deal with it.” Thanks to ubiquitous surveillance and capture by corporate giants and unavoidable platforms, corporate grasp far outreaches customer agency.

That’s one reason ProjectVRM has been working against corporate grasp since 2006, and just as long for customer reach. Our case from the start has been that customer independence and agency are good for business. We just need to prove it.

Now that we’ve hit peak subscription, and paywalls are showing up in front of formerly free digital goods (requiring, of course, more subscriptions), perhaps the world is ready for EmanciPay, an idea that has been biding its time on our wiki since 2009.

So, rather than leave it buried there, we’ll surface it here. Dig:::

Overview

Simply put, Emancipay makes it easy for anybody to pay (or offer to pay) —

1. as much as they like
2. however they like
3. for whatever they like
4. on their own terms

— or at least to start with that full set of options, and to work out differences with sellers easily and with minimal friction.

Emancipay turns consumers (aka users) into customers by giving them a pricing gun (something which in the past only sellers used) and their own means to make offers, to pay outright, and to escrow the intention to pay when price and other requirements are met. And to be able to do this at scale across all sellers, much as cash, browsers, credit cards, and email clients do the same. Payments themselves can also be escrowed.

In slightly more technical terms, EmanciPay is a payment framework for customers operating with full agency in the open marketplace, and at scale. It operates on open protocols and standards, so it can be used by any buyer, seller or intermediary.

It was conceived as a way to pay for music, journalism, or what any artist brings into the world. But it can apply to anything. For example, [subscriptions], have become a giant fecosystem in which every seller has separate and non-substitutable scale across all subscribers, while subscribers have zero scale across all sellers, with the highly conditional exceptions of silo’d commercial intermediaries. As [Customer Commons] puts it,

There’s also not much help coming from the subscription management services we have on our side: Truebill, Bobby, Money Dashboard, Mint, Subscript Me, BillTracker Pro, Trim, Subby, Card Due, Sift, SubMan, and Subscript Me. Nor from the subscription management systems offered by Paypal, Amazon, Apple or Google (e.g. with Google Sheets and Google Doc templates). All of them are too narrow, too closed and exclusive, too exposed to the surveillance imperatives of corporate giants, and too vested in the status quo.

That status quo sucks (see here, or just look up “subscription hell”), and it’s way past time to unscrew it.) But how?

The better question is where?

The answer to that is on our side: the customer’s side.

While EmanciPay was first conceived by ProjectVRM as a way to make live payments to nonprofits and to provide a new monetization method for publishers. it also works as a counterpart to sellers’ subscription systems in what Zuora (a supplier of subscription management systems to the publishing industry, including The Guardian and Financial Times) calls the “subscription economy“, which it says “is built on ever-changing relationships with your customers”. Since relationships are two-way by nature, EmanciPay is one way that customers can manage their end, while publisher-side systems such as Zuora’s manage the other.

Emancipay economic case

EmanciPay provides a new form of economic signaling not available to individuals, either on the Net or before the Net became available as a communications medium. EmanciPay will use open standards and be comprised of open-source code. While any commercial fourth parties can use EmanciPay (or its principles, or any parts of it they like), EmanciPay’s open and standard framework will support fourth parties by making them substitutable, much as the open standards of email (SMTP, POP3, IMAP) make email systems substitutable. (Each has what Joe Andrieu calls service endpoint portability.)

EmanciPay is an instrument of customer independence from all of the billion (or so) commercial entities on the Net, each with its own arcane and siloed systems for engaging and managing customer relations, as well as receipt, acknowledgment, and accounting for payments from customers.

Use Case Background

EmanciPay was conceived originally as a way to provide customers with the means to signal interest and the ability to pay for media and creative works (most of which are freely available on the Web, if not always free of charge). Through EmanciPay, demand and supply can relate, converse, and transact business on mutually beneficial terms, rather than only on terms provided by the countless different siloed systems we have today, each serving to hold the customer captive, and causing much inconvenience and friction in the process.

Media goods were chosen for five reasons: 1) because most are available for free, even if they cost money, or are behind paywalls 2) paywalls, which are cookie-based, cannot relate to individuals as anything other than submissive and dependent parties (and each browser a users employs carries a different set of cookies) 3) both media companies and non-profits are constantly looking for new sources of revenue 4) the subscription model, while it creates steady income and other conveniences for sellers, is often a bad deal for customers, and is now so overused (see Subscriptification) that the world is approaching a peak subscription crisis, and unscrewing it can only happen from the customer’s side (because the business is incapable of unscrewing the problem itself 5) all methods of intermediating payment choices are either siloed by the seller or siloed by intermediators, discouraging participation by individuals.

What the marketplace requires are new business and social contracts that ease payment and stigmatize non-payment for creative goods. The friction involved in voluntary payment is still high, even on the Web, where one must go through complex ceremonies even to make simple payments. There is no common and easy way either to keep track of what media (free or otherwise) we use (see Media Logging), to determine what it might be worth, and to pay for it easily and in standard ways — to many different suppliers. (Again, each supplier has its own system for accepting payments.)

EmanciPay differs from other payment models (subscriptions, newsstands, tip jars) by providing customers with the ability to choose what they wish to pay and how they’ll pay it, with minimum friction — and with full choice about what they disclose about themselves.

EmanciPay will also support credit for referrals, requests for service, feedback, and other relationship support mechanisms, all at the control of the user. For example, EmanciPay can provide quick and easy ways for listeners to pay for public radio broadcasts or podcasts, for readers to pay for otherwise “free” papers or blogs, for listeners to pay to hear music and support artists, for users to issue promises of payment for stories or programs — all without requiring the individual to disclose unnecessary private information or to become a “member” — although these options are kept open.

This will scaffold genuine relationships between buyers and sellers in the media marketplace. It will also give deeper meaning to “membership” in non-profits. (Under the current system, “membership” generally means putting one’s name on a pitch list for future contributions, and not much more than that.)

EmanciPay will also connect the sellers’ CRM (Customer Relationship Management) systems with customers’ VRM (Vendor Relationship Management) systems, supporting rich and participatory two-way relationships. In fact, EmanciPay will by definition be a VRM system.

Micro-accounting and Macro-distribution

The idea of “micro-payments” for goods on the Net has been around for a long time and is often brought up as a potential business model for journalism. For example in this article by Walter Isaacson in Time Magazine. It hasn’t happened, at least not globally, because it’s too complicated, and in prototype only works inside private silos.

What ProjectVRM suggests instead is something we don’t yet have, but very much need:

1. micro-accounting for actual uses. Think of this simply as “keeping track of” the news, podcasts, newsletters, or music we consume.
2. macro-distribution of payments for accumulated use (that’s no longer “micro”).

Much — maybe most — of the digital goods we consume are both free for the taking and worth more than $zero. How much more? We need to be able to say. In economic terms, demand needs to have a much wider range of signals it can give to supply. And give to each other, to better gauge what we should be willing to pay for free stuff that has real value but not a hard price.

As currently planned, EmanciPay would –

1. Provide a single and easy way for consumers of “content” to become customers of it. In the current system — which isn’t one — every artist, every musical group, and every public radio and TV station has his, her or own way of taking in contributions from those who appreciate the work. This can be arduous and time-consuming for everybody involved. (Imagine trying to pay separately every musical artist you like, for all your enjoyment of each artist’s work.) What EmanciPay proposes, however, is not a replacement for existing systems, but a new system that can supplement existing fund-raising systems — one that can soak up much of today’s MLOTT: Money Left On The Table.
2. Provide ways for individuals to look back through their media usage histories, inform themselves about what they have been enjoying, and determine how much it is worth to them. The Copyright Arbitration Royalty Panel (CARP), and later the Copyright Royalty Board (CRB), both came up with “rates and terms that would have been negotiated in the marketplace between a willing buyer and a willing seller.” This almost absurd language first appeared in the 1995 Digital Performance Royalty Act (DPRA) and was tweaked in 1998 by the Digital Millennium Copyright Act (DMCA), under which both the CARP and the CRB operated. The rates they came up with peaked at $.0001 per “performance” (a song or recording), per listener. EmanciPay creates the “willing buyer” that the DPRA thought wouldn’t exist.
3. Stigmatize non-payment for worthwhile media goods. This is where “social” will finally come to be something more than yet another tech buzzmodifier.

All these require micro-accounting, not micro-payments. Micro-accounting can inform ordinary payments that can be made in clever new ways that should satisfy everybody with an interest in seeing artists compensated fairly for their work. An individual listener, for example, can say “I want to pay 1¢ for every song I hear,” and “I’ll send SoundExchange a lump sum of all the pennies wish to pay for songs I have heard over a year, along with an accounting of what artists and songs I’ve listened to” — and leave dispersal of those totaled pennies up to the kind of agency that likes, and can be trusted, to do that kind of thing. That’s the macro-distribution part of the system.

Similar systems can also be put in place for readers of newspapers, blogs, and other journals. What’s important is that the control is in the hands of the individual and that the accounting and dispersal systems work the same way for everybody.

I was listening to the latest Pivot Podcast when Kara Swisher played a clip from Sam Altman‘s keynote at OpenAI’s Developers Day, earlier this week. Spake Sam (at the 35:18 mark),

We believe that AI will be about individual empowerment and agency on a scale we’ve never seen before

Whoa! That’s what we’ve been working toward here at ProjectVRM since 2006.

Shall we call it IEASWNSB? (Pronounced “Eewasnib,” perhaps?) We might have better luck with that than we’ve had with VRM, Me2B, and other initialisms and acronyms.

For fun, I asked Bing Image Create, which uses OpenAI’s DALL-E to produce images, to make art with its boss’s words. It gave me the images above. Here’s the link.

Those are a little too Ayn Randy for me. So I tried just “Empowered individuals,” and got this—

—which is almost the ulta-woke opposite of the first one.

But never mind that. Let’s talk about individual empowerment with AI help. Here’s my personal punch list:

1. Health. Make sense of all my health data. Suck it in from every medical care provider I’ve ever had, and help me make decisions based on it. Also, help me share it on an as-needed basis with my current providers. (On my own terms, about which more below.)
2. Finances. Pull in and help me make sense of my holdings, obligations, recurring payments, incomes, whatever. Match my orders and shipments from Amazon and other retailers with the cryptic entries (always in ALL CAPS) on my credit card bills. I want to run every receipt I collect through a scanner that does OCR for my AI, which will know what receipt is for what, where it goes in the books it helps me keep, and yearly helps me work through my taxes. The list can go on.
3. Property. What have I got? I want to point my phone camera at everything that a good AI can recognize, and make sense of all that too. Know all the books on my shelves by reading their spines. Know my furniture, the stuff in my basement. Help me keep records of my car’s history after I give it the VIN number I photographed under the windshield, and run all the records I’ve kept in the glove box through the same scanner I mentioned above. Whatever. Why not?
4. Correspondence. I have half a million emails here, going back to 1995. (Wish it went back farther.) Lots of texts too, in lots of systems. Help me do a better job of looking back through those than my various clients do. Help me cross-reference those with events I attended and other stuff that may be relevant to some current inquiry.
5. Contacts. Who do I have in my various directories? How many entries are wrong in one way or another? Go through and correct them, AI butler, using whatever clever new algorithm works for that, supplied by corporate entities whose knowledge of me remains as close to zero as I allow.
6. Crumb trail. What did I buy from Amazon (or anybody) and when? Where do Google and Apple know I’ve been and what I’ve been doing? How about my late model car, which at the very least knows lots about my driving, and may even know what I’ve said, to whom, or even if sexual activity was going on? How about my TV, the maker of which gets paid to snitch on what I’ve watched and when—and may even be watching me and others, sitting and staring at it. All that information is far more useful to me than it is to them.
7. Calendar. Tell me where I was on a given day, what I was doing, and who I was with. Knowing all that other personal data (above) will help too.
8. Business relationships. Look into all my subscriptions and help me fight the fuckery behind nearly all of them. Make better sense of all the “loyalty” programs I’m involved with, and help me unfuck those too since most of them are about entrapment rather than real loyalty. (Bonus links here and here.)
9. Other involvements. What associations do I belong to? How deeply am I involved with any or all of them? Can we drop some? Add some? Have some insights into how those are going, or should go?
10. Travel. I have 1.6 million miles with United Airlines alone. Where did I go? When? Why? What did I pay? Are there ways to improve my relationships with airlines and other entities (e.g. car rental agencies, Uber/Lyft, Airbnb, cruise lines)? Are there ways I can help them that don’t require enduring yet another of those annoying surveys that seem to follow every contact with them?
11. Shopping. We’ve been talking about (and working toward) intentcasting since the late aughts, with lots of developers on the case, but not big breakthroughs. But with AI it’s easy to imagine countless possibilities that begin with one’s intent to buy rather than retailers’ intent to sell. Words to wise sellers: A) Make it as easy as possible for customers’ personal and privacy-guarding AI agents to find what you’ve got and know as much about it as possible, and B) Fire every marketer and marketing system that wants in any ways to trap, milk, coerce, and otherwise fuck over customers. Meanwhile, customers should have AI capacities that keep them from getting screwed, to know when the screwing happens, and to help do something about it.
12. My own personal data collection. There have been many of these, by many names, tried over the years. The current leading candidate (IMHO) is Sir Tim Berners-Lee‘s Solid project.

Our lives are packed with too much data for our meat brains alone to fully comprehend and put to use. AI is good for that. So bring it on.

And don’t bet that any of the bigs, including OpenAI, will give you anything on the punch list above*. They’re too big, too centralized, too stuck in a mainframe paradigm. They look for what only they can do for you, rather than what you can do for yourself—or do better with your own damn AI.

Personal AI today is where personal computing was fifty years ago. We don’t yet have the Apple II, the Osborne, the TRS-80, the Commodore PET, much less the IBM  PC or the Macintosh. We just have big companies with big everything and hooks for developers. Coming soon: an app store (also announced in Sam Altman’s keynote).

Real personal AI is a huge greenfield. Going there is also, to switch metaphors, a blue ocean strategy. Wrote about that here.

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*Except by pouring all that data into their LLM. Not yours.

And privacy be damned.

See, there is an iron law for every new technology: What can be done will be done. And a corollary that says, —until it’s clear what shouldn’t be done.  Let’s call those Stage One and Stage Two.

With respect to safety from surveillance in our cars, we’re at Stage One.

For Exhibit A, read what Ray Schultz says in Can Radio Time Be Bought With Real-Time Bidding? iHeartMedia is Working On It:

HeartMedia hopes to offer real-time bidding for its 860+ radio stations in 160 markets, enabling media buyers to buy audio ads the way they now buy digital.

“We’re going to have the capabilities to do real-time bidding and programmatic on the broadcast side,” said Rich Bressler, president and COO of iHeart Media, during the Goldman Sachs Communacopia + Technology Conference, according to Radio Insider.

Bressler did not offer specifics or a timeline. He added: “If you look at broadcasters in general, whether they’re video or audio, I don’t think anyone else is going to have those capabilities out there.”

“The ability, whenever it comes, would include data-infused buying, programmatic trading and attribution,” the report adds.

The Trade Desk lists iHeart Media as one of its programmatic audio partners.

Audio advertising allows users to integrate their brands into their audiences’ “everyday routines in a distraction-free environment, creating a uniquely personalized ad experience around their interests,” the Trade Desk says.

The Trade Desk “specializes in real-time programmatic marketing automation technologies, products, and services, designed to personalize digital content delivery to users.” Translation: “We’re in the surveillance business.”

Never mind that there is negative demand for surveillance by the surveilled. Push-back has been going on for decades.  Here are 154 pieces I’ve written on the topic since 2008.

One might think radio is ill-suited for surveillance because it’s an offline medium. Peopler listen more to actual radios than to computers or phones. Yes, some listening is online; but  not much, relatively speaking. For example, here is the bottom of the current radio ratings for the San Francisco market:

Those numbers are fractions of one percent of total listening in the country’s most streaming-oriented market.

So how are iHeart and The Trade Desk going to personalize radio ads?  Well, here is a meaningful excerpt from iHeart To Offer Real-Time Bidding For Its Broadcast Ad Inventory, which ran earlier this month at Inside Radio:

The biggest challenge at iHeartMedia isn’t attracting new listeners, it’s doing a better job monetizing the sprawling audience it already has. As part of ongoing efforts to sell advertising the way marketers want to transact, it now plans to bring real-time bidding to its 850 broadcast radio stations, top company management said Thursday.

“We’re going to have the capabilities to do real-time bidding and programmatic on the broadcast side,” President and COO Rich Bressler said during an appearance at the Goldman Sachs Communacopia + Technology Conference. “If you look at broadcasters in general, whether they’re video or audio, I don’t think anyone else is going to have those capabilities out there.”

Real-time bidding is a subcategory of programmatic media buying in which ads are bought and sold in real time on a per-impression basis in an instant auction. Pittman and Bressler didn’t offer specifics on how this would be accomplished other than to say the company is currently building out the technology as part of a multi-year effort to allow advertisers to buy iHeart inventory the way they buy digital media advertising. That involves data-infused buying and programmatic trading, along with ad targeting and campaign attribution.

Radio’s largest group has also moved away from selling based on rating points to transacting on audience impressions, and migrated from traditional demographics to audiences or cohorts. It now offers advertisers 800 different prepopulated audience segments, ranging from auto intenders to moms that had a baby in the last six months…

Advertisers buy iHeart’s ad inventory “in pieces,” Pittman explained, leaving “holes in between” that go unsold. “Digital-like buying for broadcast radio is the key to filling in those holes,” he added…

…there has been no degradation in the reach of broadcast radio. The degradation has been in a lot of other media, but not radio. And the reason is because what we do is fundamentally more important than it’s ever been: we keep people company.”

Buried in that rah-rah is a plan to spy on people in their cars. Because surveillance systems are built into every new car sold. In Privacy Nightmare on Wheels’: Every Car Brand Reviewed By Mozilla — Including Ford, Volkswagen and Toyota — Flunks Privacy Test, Mozilla pulls together a mountain of findings about just how much modern cars spy on their drivers and passengers, and then pass personal information on to many other parties. Here is one relevant screen grab:

As for consent? When you’re using a browser or an app, you’re on the global Internet, where the GDPR, the CCPA, and other privacy laws apply, meaning that websites and apps have to make a show of requiring consent to what you don’t want. But cars have no UI for that. All their computing is behind the dashboard where you can’t see it and can’t control it. So the car makers can go nuts gathering fuck-all, while you’re almost completely in the dark about having your clueless ass sorted into one or more of Bob Pittman’s 800 target categories. Or worse, typified personally as a category of one.

Of course, the car makers won’t cop to any of this. On the contrary, they’ll pretend they are clean as can be. Here is how Mozilla describes the situation:

Many car brands engage in “privacy washing.” Privacy washing is the act of pretending to protect consumers’ privacy while not actually doing so — and many brands are guilty of this. For example, several have signed on to the automotive Consumer Privacy Protection Principles. But these principles are nonbinding and created by the automakers themselves. Further, signatories don’t even follow their own principles, like Data Minimization (i.e. collecting only the data that is needed).

Meaningful consent is nonexistent. Often, “consent” to collect personal data is presumed by simply being a passenger in the car. For example, Subaru states that by being a passenger, you are considered a user — and by being a user, you have consented to their privacy policy. Several car brands also note that it is a driver’s responsibility to tell passengers about the vehicle’s privacy policies.

Autos’ privacy policies and processes are especially bad. Legible privacy policies are uncommon, but they’re exceptionally rare in the automotive industry. Brands like Audi and Tesla feature policies that are confusing, lengthy, and vague. Some brands have more than five different privacy policy documents, an unreasonable number for consumers to engage with; Toyota has 12. Meanwhile, it’s difficult to find a contact with whom to discuss privacy concerns. Indeed, 12 companies representing 20 car brands didn’t even respond to emails from Mozilla researchers.

And, “Nineteen (76%) of the car companies we looked at say they can sell your personal data.”

To iHeart? Why not? They’re in the market.

And, of course, you are not.

Hell, you have access to none of that data. There’s what the dashboard tells you, and that’s it.

As for advice? For now, all I have is this: buy an old car.

 

 

We’ve been in an uphill fight to empower people—customers—in online markets where the prevailing belief is that captive customers are more valuable than free ones. (The value of free customers is well-understood, though not always respected, in offline markets.) And we’ve been in this fight for more than seventeen years.

But now AI is all the craze.

Question: Can AI help VRM? And vice versa?

Think about what would happen if people had their own AI systems, working for them and not for companies whose business is selling you something (e.g. Amazon), pushing advertising at you (e.g. Google), or trapping you in their walled garden (e.g. Apple)? Why not have our own AI, to help us make better sense of our contacts, our calendars, our health, financial, property, travel, and other kinds of data? And then, when the need arises, have our personal AI help us make well-informed decisions about what to buy, how, and where, without being biased by marketers and their bots on the other side?

Those are just a few questions we’ll be visiting two Mondays from now, October 9, at VRM Day in the Computer History Museum in Mountain View, California. The time frame will be 9am to 4pm. There is also plenty of parking (the Museum is otherwise closed on Mondays).

We’ll visit other questions that come up, of course. And participants with something to show off are free to do that as well. And some will, especially with IIW happening the following three days, also at the Computer History Museum.

Registering here isn’t necessary, but it helps to have a head count.

See you there!