Linear Chat Is a Terrible Interface for Complex Thinking

I’ve had hundreds of great conversations with AI.

I’ve forgotten almost all of them.

Not because the answers were bad. Many were genuinely insightful. But once the chat ended, the thinking disappeared with it. Buried in a scroll. Lost to time. Never revisited.

That’s not an AI problem.
It’s an interface problem.

Chat is good for conversation, not thinking

Chat interfaces are optimised for one thing: linear exchange.

You ask.
It answers.
You respond.
The thread grows downward forever.

This works well for quick questions, customer support, and casual back-and-forth. But complex thinking doesn’t happen in straight lines.

Real thinking is branching, iterative, spatial, and referential. Ideas connect sideways. Insights resurface later. Old thoughts gain new meaning in new contexts.

A chat log doesn’t support that. In many ways, it actively works against it.

The illusion of progress

Chat creates a powerful illusion: it feels like progress.

The responses are fluent. Confident. Often well-structured. Sometimes genuinely brilliant.

But progress isn’t the same as understanding.

Understanding requires revisiting ideas, connecting concepts across time, holding multiple threads at once, and building a mental model you can return to later.

In chat, everything is disposable. Once you scroll past it, it’s effectively gone.

This is why so many people say:

“I had an amazing AI conversation… but I can’t remember what it said.”

The problem isn’t memory.
It’s lack of structure.

AI didn’t break thinking. Interfaces did.

When people say “AI makes us lazy” or “AI replaces thinking”, they’re pointing at the wrong thing.

AI models are capable of extraordinary reasoning.

What’s broken is how we contain that reasoning.

We’ve taken the most powerful thinking engine ever created and forced it into a user interface originally designed for instant messaging.

That mismatch has consequences:

• No spatial memory
• No persistent structure
• No sense of progress over time
• No way to build on past insights

Every session starts fresh, even when the problem doesn’t.

Thinking is a graph, not a log

If you look at how humans actually think, it resembles a graph, not a conversation.

Ideas branch.
Questions lead to sub-questions.
Concepts connect across domains.
Old notes resurface with new relevance.

This is why whiteboards, canvases, and mind maps have always been powerful tools for deep work. They externalise thought, make relationships visible, and allow ideas to coexist instead of replacing each other.

Chat, by contrast, is a log. Once written, it moves on. Nothing truly stays present.

The missing layer in AI tools

Most AI tools focus on better models, faster responses, and longer context windows.

Those things matter, but they don’t solve the core issue.

What’s missing is a thinking layer:

• a place where ideas persist
• where conversations become artefacts
• where insights can be revisited, connected, and evolved

Without that layer, AI remains impressive but shallow.

Useful in the moment.
Forgotten soon after.

A different approach

Jam AI is built around a simple belief:

AI should support how humans actually think, not force thinking into a chat box.

Instead of a single linear conversation, Jam AI uses a canvas-based approach where:

• thoughts become nodes
• ideas branch naturally
• conversations remain visible
• insights accumulate over time

The goal isn’t more answers.

It’s better thinking.

Why this matters now

As AI becomes more capable, the bottleneck shifts.

The limiting factor is no longer intelligence.
It’s organisation, memory, and structure.

The people who benefit most from AI won’t be those who ask the most questions. They’ll be those who can build on their thinking over time.

That requires better interfaces.

A quiet invitation

If you’ve ever felt like your best AI ideas disappear, your thinking resets every session, or chat isn’t quite enough for real work, you’re not alone.

We’re exploring a different way of working with AI through Jam AI, and we’re still early.

If this way of thinking resonates, you can join the waitlist and explore it as it evolves.