One aspect of strategy that’s been largely lost in the tech industry in recent years is how to compete against platforms, since the major tech companies have gotten so big that markets are no longer competitive. However, the AI market is still early enough, and users and society are still angry enough, that the Big AI companies can lose.

But for them to lose, everybody else in the ecosystem has to carry out the nearly-lost art of platform strategy. Tech companies (and even open source communities!) used to carry out these tactics in emerging product categories ranging from desktop office suites to operating systems to web browsers, though over the decades, the lesson that big tech learned was, basically, that they should play dirty.

You win platform strategy battles through power and persuasion. We're going to get both.

Historically, we would have relied on regulators or media to help hold bad actors in the tech space accountable, but in the United States, these entities are largely not going to help very much. Some state and local governments may assist, and some independent journalists or smaller media outlets are pushing for accountability, but the most powerful entities are either captured or complicit in many cases, so we don’t have the institutional pushback that had sometimes been present in earlier points of technological change.

The thing that matters right now is that we understand that all of the Big AI companies are extremely vulnerable. The reason they’re making so much noise, and spending so much money, is because they know that they’re vulnerable. Users, and especially users who are developers have an enormous amount of leverage to control where AI goes. And if those communities of users can coordinate, they can put power back into the hands of the people. Today, that means focusing on some technical interventions, along with the cultural and political pushback that’s happening. That’s how we begin to reduce, or even prevent, some of the worst AI harms in the future.

Here are some of the proven tactics that have helped shift the balance of power in prior tech reckonings:

1. Get in front of it

The first and most important technical goal is for everyone to push for all AI usage to be disintermediated — where users access their AI apps or services through open tools or interfaces that aren’t controlled by the Big AI companies. These tools, in the form of “harnesses”, or through text editors or command lines, or just through the familiar chat interfaces that lots of people use, need to move as quickly as possible to being controlled by community-built, open options. The sooner this step happens, the sooner we unlock the ability to shift decision-making power out of the hands of the corporate platforms, and begin to undermine their ability to cement lock-in of users.

Status: Good. There are a number of popular, mature tools in almost every category for users who want to access today’s AI tools through a free, open interface. Most of the work now is to get the word out about these tools, and to continue to polish and improve the user experience so that they offer features and design touches that the commercial tools can’t or won’t.

2. Spread the love around

Another key capability that the open ecosystem must provide is the ability to seamlessly switch between different AI providers on the fly, to reduce costs, to provide better performance, or to get both benefits. In many cases, this will be seamless and automatic, just making the right choice for users so that they get the best option all of the time, but advanced users will want to tweak their settings, like when businesses may want to be very aggressive in minimizing the amount of money that their employees are allowed to spend on AI services.

The important part here is that this forces AI platforms that want to compete to remain compatible with all of their competitors, keeping the market dynamic, and ensuring that all of the big providers are easily replaced with another vendor at any time. Basically, we always have to be able to keep them in their place, and they should know that they could go away at any time. Most companies are aware of these needs, but the more regular consumers are familiar with these kinds of requirements, the more pressure there will be on companies to conform with standards. (This is also what will enable the disintermediation mentioned in point 1.)

Status: Good. This is happening already in business environments, where companies demand this kind of flexibility. Developers have been creating very dynamic systems for switching between AI providers, and the ecosystem encourages this kind of switching by extensively comparing different AI platforms against each other whenever new models are released. The important thing to maintain here is the narrative that none of the individual models matter more than the overall ecosystem — and that even the biggest companies have to conform to the same strict formats and standards as the independent AI systems created by communities around the world.

3. Free the tools

Another vital concern for shifting power away from the Big AI companies is undermining them economically. Instead of simply following the classic “commoditize the complement” strategy that commercial companies often execute, open source projects created by a community can more straightforwardly pursue a path of enlightened value destruction. Non-commercial LLMs have been roughly keeping pace with the Big AI platforms, following the pattern I described as “frontier minus six”, where free and open models lag about 6 months behind the most cutting-edge AI labs — which means they’re still pretty freaking great for most uses.

In a scenario where there are extremely capable models that cost nothing except for the price of keeping a few servers running, as well as very robust tools that make it effortless to seamlessly switch between models (see point #2!), more and more organizations will shift more and more work away from the Big AI companies, especially as those companies keep raising their prices.

But there’s no reason that these same principles can’t be followed by ordinary consumers as well. Many developers are already using these techniques to switch to free models to save money, and the only barrier to this practice becoming more widespread is that the user experience is still too clunky and technical for most regular people.

Status: Okay. Lots of people are working on this, and in some scenarios, the free AI tools are even pretty great. But for the most part, there are still too many compromises in either the end results or the user experience for this to be a mainstream alternative today. This can change, with the right investments and focus on improving things — and focusing on differentiation in areas where the open community can distinguish itself from all of the Big AI companies.

4. Get angry too

Pretty much everybody who’s from the 21st century, or anybody who’s a creative person, is pretty furious about AI. Anyone who’s not oblivious to culture is aware of that. Yet all of the Big AI companies keep treating it like some fad that’s going to blow over, or a trend that they can just steamroll with their dollars. This isn’t going to go the way they want.

However, the people who will build the alternatives can actually listen to the values and criticisms of the people who are angry, and make tools that respect and respond to what they’re saying. An Internet of consent is not only possible, it’s all around us, if we choose to respect it. If people hear that they can get some of the conveniences or features that they were previously told were only possible with extractive, exploitative, evil AI tools, but without any of those negatives, they’ll actually be pretty happy to hear it.

Today, usage of AI is high enough that even some of the people who hate AI are using it. Some of this is due to the coercive way that AI is being shoved into everybody’s faces, some of it is due to there being some places that people feel it has utility that they wish they could access without its moral compromises. When people are compelled to use platforms that they object to (as a lot of people feel about using things like social media), the feelings of guilt and resentment that come along with it are deeply toxic.

What we're talking about across these first three points, if taken together, is an entirely new experience for millions of users. And that new set of platforms could respect the consumer backlash against AI and channel it into presenting tools that acknowledge their anger and treat it as legitimate. They might even be tools for fighting back.

Status: This one’s going to be tough. This is the one idea where most people think I’m crazy. People who have a righteous anger about the harms of current Big AI companies say that there couldn’t be any such thing as “good AI”, and I understand their skepticism. People who think AI is an interesting technology but hate the hype (the majority AI view) are usually skeptical that the open community could make offerings that are good enough to compete against the big commercial offerings. And AI enthusiasts are pretty skeptical that AI critics would ever come around to seeing any technology in this category as being acceptable, no matter how thoughtfully it was created or presented.

I think there’s enough anger at the trillionaire predators to go around, though.

Let’s get to work

It’s been a long time since we succeeded in wresting control of a nascent space away from the tycoons trying to take it over. But it’s pretty clear what the stakes are this time, and it’s also clear that the window for changing the path of the AI world is closing pretty rapidly.

Obviously, this kind of shift won’t be easy, but I think people would be pretty surprised how possible it is. There’s a snowball effect that happens once folks start to understand that there are appealing alternatives to the things that are making them miserable. An entire generation needs to discover that enshittification is not only not inevitable, it is downright preventable, and the power to do so rests in our hands.

If you’re a developer, you have an extra responsibility: are you vetting your work against this list? If nothing else, you need to be doing so just to ensure that you have a chance of having a career over time. But it’s also the right thing to do.

And if you’re not technical in that way, you don’t have to become a developer, but you can familiarize yourself with these concerns broadly — even if you hate AI and never want to touch the stuff! — so that you know what argument to make about how to shift the balance of power.

The most important thing to know is that, as so many people have said, none of this is inevitable. But the way we fight that inevitability is with a more exciting, human, powerful alternative, not merely by repeating what we’re saying no to. We are not simply angrily running away from something, we can all be joyfully running toward something together.

Bonus Footnotes

In the early days of tech blogging, one of the biggest reasons that so many people got used to reading Joel Spolsky’s blog was that he’d often write amusing little fables that shared key lessons about product strategy. Strategy Letter V (on commoditizing your complements), or How Microsoft Lost the API War, or Fire and Motion, or… Platforms. If you can squint past the turn-of-the-century mentions of Microsoft Excel, there are lots of interesting lessons there.