About six weeks in the past, I despatched an electronic mail to Satya Nadella complaining in regards to the monolithic winner-takes-all structure that Silicon Valley appears to ascertain for AI, contrasting it with “the structure of participation” that had pushed earlier expertise revolutions, most notably the web and open supply software program. I suspected that Satya may be sympathetic due to previous conversations we’d had when his e-book Hit Refresh was printed in 2017.
I made the case that we’d like an structure for the AI trade that permits cooperating AIs, that isn’t a winner-takes-all market, and that doesn’t make current corporations in each trade merely the colonial domains of extractive AI conquerors, which appears to be the Silicon Valley imaginative and prescient.
Little did I do know that Microsoft already had one thing within the works that may be a demonstration of what I’m hoping for. It’s known as NLWeb (Pure Language Internet), and it’s being introduced as we speak. Satya supplied O’Reilly the prospect to be a part of the rollout, and we jumped at it.
Embracing the Early Stage of Innovation
My concepts are rooted in a notion about how expertise markets evolve. We’ve lived by three eras in computing. Every started with distributed innovation, went by a interval of fierce competitors, and ended with monopolistic gatekeepers. Within the first age (mainframes), it was IBM, within the second (PCs) Microsoft, and within the third (web and cell) the oligopoly of Google, Amazon, Meta, and Apple.
The error that everybody makes is a rush to crown the brand new monopolist at the beginning of what’s basically a wide-open subject initially of a brand new disruptive market. They usually envision that monopoly largely as a substitute for what went earlier than, quite than realizing that the paradigm has modified. When the non-public laptop challenged IBM’s hardware-based monopoly, corporations raced to turn into the dominant private laptop {hardware} firm. Microsoft gained as a result of it realized that software program, not {hardware}, was the brand new supply of aggressive benefit.
The story repeated itself initially of the web period. Marc Andreessen’s Netscape sought to switch Microsoft as a dominant software program platform, aside from the web quite than the PC. AOL realized that content material and neighborhood, not software program, was going to be a supply of aggressive benefit on the web, however they made the identical mistake of assuming the tip sport of consolidated monopoly quite than embracing the early stage of distributed innovation.
So right here we’re initially of the fourth age, the age of AI, and as soon as once more, everyone seems to be speeding to crown the brand new king. A lot of the chatter is whether or not OpenAI or one in every of its rivals would be the subsequent Google, when it seems to me that they’re extra doubtless the subsequent Netscape or the subsequent AOL. DeepSeek has thrown a bomb into the coronation parade, however we haven’t but absolutely realized the depth of the reset, or conceptualized what comes subsequent. That’s sometimes found out by a interval of distributed innovation.
We Want an Structure of Participation for AI
The time period “the structure of participation” initially got here to me as an evidence of why Unix had succeeded as a collaborative challenge regardless of its proprietary license whereas different initiatives failed regardless of having open supply licenses. Unix was designed as a small working system kernel supporting layers of utilities and functions that might come from anybody, so long as they adopted the identical guidelines. Advanced behaviors may very well be assembled by passing data between small packages utilizing customary knowledge codecs. It was a protocol-centric view of how complicated software program programs must be constructed, and the way they might evolve collaboratively. Linux, after all, started as a re-implementation of Unix, and it was the structure of participation that it inherited, as a lot because the license and the neighborhood, that was the inspiration of its success. The web was additionally developed as a distributed, protocol-based system.
That idea ran by my internet advocacy within the early ’90s, open supply advocacy within the late ’90s, and Internet 2.0 within the aughts. Participatory markets are modern markets; prematurely consolidated markets, not a lot. The boundaries to entry within the early PC market had been very low, entrepreneurship excessive. Ditto for the Internet, ditto for open supply software program and for Internet 2.0. For late Silicon Valley, fixated on untimely monopolization by way of “blitzscaling” (assume Uber, Lyft, and WeWork as examples, and now OpenAI and Anthropic), not a lot. It’s turn into a sort of central planning. A small cadre of deep-pocketed traders choose the winners early on and attempt to drown out competitors with large quantities of capital quite than permitting the experimentation and competitors that enables for the invention of true product-market match.
And I don’t assume now we have that product-market match for AI but. Product-market match isn’t simply getting a number of customers. It’s additionally discovering enterprise fashions that pay the prices of these companies, and that create worth for greater than the centralized platform. The issue with untimely consolidation is that it narrows the main focus to the enterprise mannequin of the platform, typically on the expense of its ecosystem of builders.
As Invoice Gates famously informed Chamath Palihapitiya when he was operating the nascent (and finally failed) Fb developer platform, “This isn’t a platform. A platform is when the financial worth of all people that makes use of it exceeds the worth of the corporate that creates it. Then it’s a platform.” To be clear, that isn’t simply worth to finish customers. It’s worth to builders and entrepreneurs. And meaning the chance to revenue from their improvements, to not have that worth instantly harvested by a dominant gatekeeper.
Now after all, Sam Altman talks about creating worth for builders. In a latest look at Sequoia Capital’s AI Ascent occasion, he stated his hope is to create “like simply an unbelievable quantity of wealth creation on the earth and different folks to construct on that.” However he makes use of the language of “an working system” that others construct on high of (and pay OpenAI for the usage of) quite than a shared infrastructure co-created by an ecosystem of builders.
That’s why I’ve been rooting for one thing completely different. A world the place specialised content material suppliers can construct AI interfaces to their very own content material quite than having it sucked up by AI mannequin builders who supply up companies based mostly on it to their very own customers. A world the place software builders can supply new sorts of companies that allow others in a cooperative cascade.
We’re Simply Getting Began
Anthropic’s Mannequin Context Protocol, an open customary for connecting AI brokers and assistants to knowledge sources, is step one towards a protocol-centric imaginative and prescient of cooperating AIs. It has generated numerous well-deserved enthusiasm. Google’s A2A takes that additional with a imaginative and prescient of how AI brokers would possibly cooperate. NLWeb provides to that a straightforward method for web content material websites to affix the occasion, providing each a conversational entrance finish to their content material and an MCP server in order that it’s accessible to brokers.
That is all going to take years to get proper. However as a result of it’s a protocol-centric quite than a platform-centric imaginative and prescient, options can come from all over the place, not simply from a dominant monopolist.
Each new wave of computing has additionally had a brand new consumer interface paradigm. Within the mainframe period, it was the teletype terminal; for the PC, the Graphical Person Interface; for the web, the online’s document-centric interface; for cell, contact screens. For AI (for now no less than), it seems to be conversational interfaces.
Firms corresponding to Salesforce and Bret Taylor’s Sierra are betting on conversational brokers which might be entrance ends to corporations, their companies, and their enterprise processes, in the identical method that their web site or cell app is as we speak. Others are betting on client-side brokers that can entry distant websites, however typically by calling APIs and even performing the equal of display screen scraping. MCP, A2A, and different agent protocols level to a richer interplay layer made up of cooperating AIs, ready to hook up with any website providing AI companies, not simply by way of API calls to a dominant AI platform.
All corporations want no less than a begin on an AI frontend as we speak. There’s a wonderful line from C. S. Lewis’s novel Until We Have Faces: “We can’t see the gods nose to nose till now we have faces.” Proper now, some corporations are capable of supply an AI face to their customers, however most don’t. NLWeb is an opportunity for each firm to have an AI interface (or just “face”) for not simply their human customers however any bot that chooses to go to.
NLWeb is absolutely suitable with MCP and gives current web sites a easy mechanism so as to add AI search and different companies to an current internet frontend. We put collectively our demo AI search frontend for O’Reilly in a couple of days. We’ll be rolling it out to the general public quickly.