About six weeks in the past, I despatched an e mail to Satya Nadella complaining in regards to the monolithic winner-takes-all structure that Silicon Valley appears to examine for AI, contrasting it with “the structure of participation” that had pushed earlier know-how revolutions, most notably the web and open supply software program. I suspected that Satya is likely to be sympathetic due to previous conversations we’d had when his ebook Hit Refresh was revealed in 2017.
I made the case that we want an structure for the AI trade that permits cooperating AIs, that isn’t a winner-takes-all market, and that doesn’t make current firms 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 could be a demonstration of what I’m hoping for. It’s referred to as NLWeb (Pure Language Net), and it’s being introduced at the moment. Satya provided 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 know-how markets evolve. We have now lived by way of three eras in computing. Every started with distributed innovation, went by way of 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 initially of what’s basically a wide-open subject firstly of a brand new disruptive market. They usually envision that monopoly largely as a substitute for what went earlier than, relatively than realizing that the paradigm has modified. When the private pc challenged IBM’s hardware-based monopoly, firms raced to turn out to be the dominant private pc {hardware} firm. Microsoft received as a result of it realized that software program, not {hardware}, was the brand new supply of aggressive benefit.
The story repeated itself firstly of the web period. Marc Andreessen’s Netscape sought to exchange Microsoft as a dominant software program platform, apart from the web relatively than the PC. AOL realized that content material and group, 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 recreation of consolidated monopoly relatively than embracing the early stage of distributed innovation.
So right here we’re firstly of the fourth age, the age of AI, and as soon as once more, everyone seems to be dashing to crown the brand new king. A lot of the chatter is whether or not OpenAI or one among its rivals would be the subsequent Google, when it seems to me that they’re extra possible 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 usually discovered by way of 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 undertaking 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 purposes that might come from anybody, so long as they adopted the identical guidelines. Complicated behaviors could possibly be assembled by passing data between small applications utilizing commonplace information codecs. It was a protocol-centric view of how complicated software program methods must be constructed, and the way they may evolve collaboratively. Linux, in fact, 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 group, that was the inspiration of its success. The web was additionally developed as a distributed, protocol-based system.
That idea ran by way of my net advocacy within the early ’90s, open supply advocacy within the late ’90s, and Net 2.0 within the aughts. Participatory markets are progressive markets; prematurely consolidated markets, not a lot. The limitations to entry within the early PC market had been very low, entrepreneurship excessive. Ditto for the Net, ditto for open supply software program and for Net 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 out to be a form of central planning. A small cadre of deep-pocketed traders choose the winners early on and attempt to drown out competitors with huge quantities of capital relatively than permitting the experimentation and competitors that permits for the invention of true product-market match.
And I don’t assume we now have that product-market match for AI but. Product-market match isn’t simply getting numerous 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 target to the enterprise mannequin of the platform, usually on the expense of its ecosystem of builders.
As Invoice Gates famously advised Chamath Palihapitiya when he was working 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 in fact, 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 this planet and different folks to construct on that.” However he makes use of the language of “an working system” that others construct on prime of (and pay OpenAI for the usage of) relatively than a shared infrastructure co-created by an ecosystem of builders.
That’s why I’ve been rooting for one thing totally different. A world the place specialised content material suppliers can construct AI interfaces to their very own content material relatively than having it sucked up by AI mannequin builders who provide up companies primarily based on it to their very own customers. A world the place software builders can provide new sorts of companies that allow others in a cooperative cascade.
We’re Simply Getting Began
Anthropic’s Mannequin Context Protocol, an open commonplace for connecting AI brokers and assistants to information sources, is step one towards a protocol-centric imaginative and prescient of cooperating AIs. It has generated a variety of 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 manner for web content material websites to affix the get together, 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 relatively than a platform-centric imaginative and prescient, options can come from in every single place, not simply from a dominant monopolist.
Each new wave of computing has additionally had a brand new person interface paradigm. Within the mainframe period, it was the teletype terminal; for the PC, the Graphical Consumer Interface; for the web, the online’s document-centric interface; for cell, contact screens. For AI (for now at the very least), it seems to be conversational interfaces.
Firms resembling Salesforce and Bret Taylor’s Sierra are betting on conversational brokers which can be entrance ends to firms, their companies, and their enterprise processes, in the identical manner that their web site or cell app is at the moment. Others are betting on client-side brokers that may entry distant websites, however usually by calling APIs and even performing the equal of display scraping. MCP, A2A, and different agent protocols level to a richer interplay layer made up of cooperating AIs, ready to connect with any web site providing AI companies, not simply by way of API calls to a dominant AI platform.
All firms want at the very least a begin on an AI frontend at the moment. There’s a wonderful line from C. S. Lewis’s novel Until We Have Faces: “We can’t see the gods head to head till we now have faces.” Proper now, some firms are in a position to provide 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 appropriate with MCP and gives current web sites a easy mechanism so as to add AI search and different companies to an current net 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.
