Why your AI assistant stops making sense (and the 30-second fix)

I was chatting to some construction project managers over the weekend and I asked them how they’re using AI in their line of work.

One of them said to me they use it mainly for research, “until it starts to lose its mind after a few messages”.

I replied that he was right, AI actually starts to lose its mind after a long conversation.

Let’s run through what to do about it.

The Hidden Performance Killer in AI: Understanding Context Windows

I said to my new project manager friends:

“Imagine you have a book, and each time you turn a page, some of the earlier pages vanish from your memory. This is exactly what happens in AI chats when you hit context window limits - and it's the root cause of one of the most common frustrations users face: declining chat quality.”

And this is not something they teach you when you sign up to a tool or read the news, but understanding how to work within these restrictions will improve your AI outputs more than any prompt engineering trick.

Here's what you need to know:

While AI assistants can handle lengthy conversations, you'll typically start to notice degradation in their responses and context awareness after several dozen exchanges. This isn't a flaw - it's a deliberate design choice to balance performance with computational resources.

And to complicate things further, the limit isn't just about message count - it's about content density. A conversation with 20 detailed messages discussing complex topics may hit cognitive limits faster than 50 shorter, simpler exchanges.

Here's the single most powerful technique I've discovered for managing this limitation:

Every 15-20 messages I create context checkpoints by asking Claude to summarize the key decisions and direction so far. This isn't just note-taking - it's a diagnostic tool. When Claude provides the summary, you'll see what information is still "in view" and what's fallen out of the context window.

If crucial details are missing from the summary, that's your signal that important context has slipped out of the window and needs to be refreshed or reintroduced.

These checkpoints are your early warning system. When key information starts vanishing from an AI chat summary, you have two options:

• Reintroduce the missing context in your next message

• Start fresh with a new conversation that leads with the critical points

It's a simple but powerful technique that turns a frustrating limitation into a manageable process.

Next time you're deep in conversation with Claude, just ask "Can you summarize our key points so far?" - you might be surprised by what has slipped out of view.

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FACTS TO IMPRESS PEOPLE AT PARTIES

LLM stands for Large Language Model. Claude, ChatGPT, Gemini, and all your other AI chat friends are LLMs - basically very large AI systems trained on massive amounts of text.

They process patterns in this training data to predict and generate human-like text responses based on the input they receive.

At their core, these models use an attention mechanism that allows them to weigh the importance of different words in context window, helping them understand relationships between distant parts of text and generate coherent responses.

And seeing you are now a context window expert, you can see how words falling out of the context might break the attention mechanism.

You never fail to impress me.