May 1, 2026

Why Provider Changes Are Absorbed in the Adapter: 5BY.AI's Multi-LLM Architecture Principle

ChatGPT, Claude, Gemini, Copilot, Perplexity, DeepSeek, Mistral, and Grok each have different screens and conversation structures.

Even the same AI service can change how it displays messages, the structure of the input field, and information that distinguishes conversations through updates.

If 5BY.AI, which connects conversations from multiple AIs, is directly shaken by these changes, then every time a specific service's screen changes slightly, storage, connection, search, and graph could all be affected together.

So 5BY.AI separates each AI Provider's changes from core functionality.

The basic principle is that parts that differ per Provider are absorbed in the Adapter, and Core handles the user's thinking and context in a consistent way.

AI Provider Changes Are Inevitable

AI services evolve rapidly.

New models and features are added, conversation screens and button positions change, and the internal structure for displaying messages also changes.

What looks like a small screen change to the user can be a significant change for tools that recognize conversations in the browser.

For example, the following parts can change.

How user messages and AI responses are distinguished
The screen structure in which conversations are displayed
The process by which messages are added or modified
The position of the input field and send button
Conversation addresses and identification methods
How regenerated responses are displayed

These changes occur naturally as each Provider improves its service.

The problem is not the changes themselves.

How far the impact of one Provider's change reaches across the entire 5BY.AI structure.

Adapter Handles Parts That Differ Per Provider

Adapter is the boundary that understands each AI service's screen and conversation structure.

The method for reading ChatGPT's screen and the method for reading Copilot's screen might differ. Claude's message structure and Mistral's message structure cannot be assumed to be the same either.

Adapter processes these differences within each Provider.

Its main roles are as follows.

Identifies which AI Provider is current.
Detects user messages and AI responses.
Interprets screen structures that differ per Provider.
Organizes needed conversation information into a common format.
Passes the organized result to the next layer.

The important point is that Adapter is not where the user's thinking is evaluated or important conversations are determined.

Adapter focuses on the role of detecting and translating Provider differences.

Core Must Know the Provider but Not Depend on It

What 5BY.AI's Core needs to know is roughly which Provider did this message come from.

But it should not know the specific Provider's screen structure, selectors, and button positions.

For example, if the following judgments increase inside Core, problems arise.

When ChatGPT, process this way.
When Claude, find different screen elements.
When Gemini, save only when a specific button exists.
When Copilot, use a separate message structure.

If these per-Provider conditions keep accumulating in Core, the core structure must be modified together every time a new AI is added or an existing service is updated.

A small screen change could affect storage units, context connections, and Graph View.

So 5BY.AI separates per-Provider differences so they do not penetrate Core.

Core processes the user's thinking flow based on the common format information delivered by Adapter.

One Provider's Change Should Not Affect Other Providers

The most important purpose of Adapter separation is limiting the scope of changes.

For example, suppose Perplexity's conversation screen changed.

In a properly separated structure, the modification target should be concentrated in the Perplexity Adapter.

The following features should not be modified together due to this change.

ChatGPT conversation detection
Claude message storage
Anchors created in Gemini
Handoff continuing from DeepSeek
Saved from Mistral conversations
Graph View of Copilot records
Connections of thoughts generated in Grok

Even if one Provider changes, the remaining Providers and 5BY.AI's common features should be maintained as-is.

This is what it means for Adapter to absorb the impact of change.

Without Adapter, Core Easily Becomes Contaminated

When supporting only one or two AIs initially, putting per-Provider conditions directly into core code might appear faster.

But as supported targets increase, the same problem repeats.

New exceptions are added for each Provider, and when modifying one feature, conditions for multiple services must be checked together.

Over time, Core might become not an area that processes the user's thinking flow but an area that collects per-Provider exceptions.

In this state, the following problems arise.

It is difficult to predict the impact scope of a small change.
Modifying one Provider might break another.
Complexity increases rapidly as new Providers are added.
The boundary between common features and Provider-specific code blurs.
It becomes difficult to distinguish whether the cause of a failure is a screen change or a Core problem.

Adapter separation is not simply a way to organize code.

It is a structure that protects 5BY.AI's core functionality from being contaminated by Providers' frequent changes.

Anchor and Handoff Must Not Depend on Provider Screens

5BY.AI's important features are not features for a specific AI service's screen.

Anchor leaves reference points for thinking worth continuing.

Saved selects important conversations to check again later.

Handoff connects the context of goals and judgments formed so far to a new AI conversation.

Graph View lets users explore relationships among different conversations and thoughts.

The meaning of these features should not change whether used in ChatGPT, DeepSeek, or Grok.

How each Provider displays messages might differ.

But the thinking the user selected as important and the context to continue next must be handled with a common structure.

Adapter processes screen differences, and Core handles the user's thinking flow consistently beyond those differences.

The Same Principle Is Needed When Adding New AIs

Supporting a new Provider in a multi-LLM service is not simply adding a website address.

Each service must be understood in how it displays conversations, how messages are generated, and how users continue conversations.

But if adding a new Provider requires changing the existing Core, expansion cost and risk keep growing.

In a good separation structure, a new Provider follows this process.

The new Provider's screen and conversation structure are understood by the Adapter.
Detected information is organized into 5BY.AI's common format.
Existing Core and storage structure process it the same way.
Anchor, Saved, Handoff, and Graph View maintain their existing meaning.

Even when supporting a new AI, users should not need to learn a completely different way to use 5BY.AI.

Providers can increase, but 5BY.AI's core behavior must remain consistent.

What Matters to Users Is Stability, Not Internal Structure

Users do not need to understand the difference between Adapter and Core.

What users expect is simpler.

Even if AI services update, important conversations can continue to be saved.
A specific Provider's problem should not ruin the experience of using other AIs.
Regardless of which AI is used, the meaning of Anchor and Handoff should be the same.
Even if new AIs are added, connections between existing records and thoughts should be maintained.
Even when moving across multiple AIs, 5BY.AI's usage method should be consistent.

Adapter separation is an internal design to protect this user experience.

It is an invisible structure, but it determines how stably the service can respond to changes.

Providers Change but the User's Thinking Flow Must Continue

AI Providers keep changing.

Screens change, features are added, and conversation structures and usage methods can change.

5BY.AI continuously evolving to adapt to those changes is necessary.

But what does not need to change should not be shaken together.

Per-Provider screens and detection methods can change in the Adapter.

Meanwhile, the core experience of selecting important thoughts, leaving context, continuing in other AIs, and re-examining relationships must be stably maintained.

Provider changes are absorbed by the Adapter, and Core protects the user's thinking flow.

This principle is the fundamental design for 5BY.AI to support multiple AIs without being dependent on a specific Provider.

AI services can keep changing.

But there is no need for the important thoughts the user has left and the coordinates to continue next to be shaken together.