In the age of AI, I have no loyalty.

Looking at the subscription and migration discussions of several AI products recently, the most obvious change is not “who is stronger”, but “how difficult it is to replace it”. Under the premise that the model capabilities are close, whether a user will stay or not is less determined by the brand mind and more determined by details such as context, memory, permissions, export and audit.

Switching costs are more real than loyalty

If one assistant is only responsible for chatting, there is almost no cost to switch. Put commonly used prompt words, preferences and context into markdown files, change the input box, and many experiences can be connected. The so-called loyalty basically does not exist in this scenario. When the gap in capabilities is not large, users will only choose the one with fast response, low price, and stable online availability.

This is also a fact that will be exposed on the first day of many subscription products: pricing can change the trial threshold, but cannot change the difficulty of replacement. As long as the basic skills are sufficient, the real decision to stay is not “whether you remember your preferences”, but “whether you will break up a whole set of work habits after changing.”

Memory is only migratory state

Many products like to talk about “memory” as stickiness, which sounds like users can’t leave because they remember their preferences. It’s actually closer to the opposite: the easier the memory is to externalize, the less likely the user will be locked out. As long as prompt words, common tool configurations, personal rules, and conversation summaries can be exported to local files, the switching cost will be very low.

What is really difficult to transfer is not the memory itself, but the action links bound to the memory. For example, a set of fixed prompt templates, commonly used project contexts, always-open workspaces, default attachment processing methods, and verified reply formats. Once these things are put into text or configuration, the differences between products will quickly shrink.

This is why it is difficult for pure chat products to form a long-term lock-in. The chat content itself is not important enough, and at most a little sense of history will be lost during migration. A sense of history does not mean work dependency, and leaving a conversation window has no substantial side effects. Without side effects, there is no real pressure to retain.

The deeper the tool link, the more stable the product will be

Scenarios such as Coding, Agent, knowledge organization, and email processing are different. Once warehouses, documents, mailboxes, calendars, groups, permissions and attachments are connected, the product is no longer just a model shell, but a stateful execution system. Once the status is scattered in multiple places, migration is no longer as simple as “changing an account”, but moving the history, constraints and side effects together.

This is also the misjudgment point of many AI products. Products like to talk about “memory” as sticky. What really sticks with people is often not the memory, but the execution chain. A completion tool, an agent, a code review assistant, if it only provides smarter answers, can be replaced quickly; if it starts to take over warehouse permissions, change records, task status, CI results and rollback paths, retention will suddenly become heavy.

The reason why people stay is not that they are “reluctant to part with the model”, but that work has been organized around it. The moat here is no longer model parameters, but state management, execution boundaries and recovery capabilities after failure. As long as these layers are made thin, no matter how strong the model is, it will just be a more expensive input box.

Charging does not automatically create loyalty

Same goes for subscriptions. Charging does not automatically create loyalty, it just raises the threshold for trial and error from zero to dozens of dollars. As long as the alternatives are near the same level, users will still move, just more cautiously. Products that can truly retain people often do not make chats more lively, but tighten up transferable things into a work chain that is difficult to translate.

Therefore, “In the AI ​​era, I have no loyalty.” This sentence is more like a product judgment than an emotional statement. Once the model capabilities are close enough, loyalty will quickly fade away, leaving only switching costs. Whoever can make the status, permissions, evidence chain and recovery path more complete will be able to retain users more easily. Anyone who only makes his answers more human-like will only see others replace the input boxes.