Why your smart AI turns stupid mid-conversation

Have you ever been deep in conversation with an AI when it suddenly forgets important details you shared earlier? Or starts giving vague, generic answers after being so helpful initially? It's not just annoying — it's a productivity killer, and there's a specific reason it happens.

The three signs your AI is overloaded

1. Increasingly "stupid" responses

The most infuriating symptom is when your AI assistant starts ignoring critical information you provided earlier, contradicts itself, or completely misses the point of your questions.

2. Dangerous hallucinations

As context grows overwhelming, AI models begin inventing information — citing non-existent sources, making up statistics, or creating false "memories" of your previous instructions that never actually happened.

3. Rapidly depleting usage limits

Whether you're paying per token or hitting monthly limits, bloated contexts mean you're getting fewer useful responses for the same cost.

Why this happens

When you chat with AI, it processes:

• Your current question
• All previous messages
• Any special instructions or settings
• Uploaded files or images
• External information like web search results

AI models can only handle a limited amount of information at once. This creates two problems:

1. Even before hitting the limit, your AI gets less accurate as conversations grow longer — like a person trying to remember too many details at once.
2. When you finally exceed the hard limit, the AI either stops responding or drops your earliest messages, causing it to "forget" important information from the beginning of your conversation.

Five easy fixes (that actually work)

1. Start fresh conversations for new topics

The single most effective solution: When shifting focus, begin a new chat rather than continuing an existing one.

Example: Finished discussing marketing strategy? Start a new conversation for content creation rather than continuing the same thread.

Why this works: Starting fresh gives the AI a clean slate, just like your memory works best when you focus on one topic at a time, the AI responds more clearly when it doesn't have to sort through unrelated information from previous discussions.

2. Use a platform that lets you delete irrelevant messages

Services like loqus.ai allow you to delete no longer useful messages, keeping only what matters without starting over completely.

Why this works: Selectively removing messages keeps your critical information intact while clearing out the "noise."

3. Create purpose-specific AI assistants

Rather than one all-purpose assistant, create specialized helpers for different tasks. In loqus.ai, you can create custom assistants in seconds that are pre-configured for specific roles.

Why this works: Just as you'd choose a right person for the job, assistants with specialized instructions do better at their task than a general assistant.

4. Choose the right model for your task

Not all tasks require the same processing power:

• Use models with larger context capacity for information retrieval
• Use thinking models for complex analysis
• Select smaller cost-efficient models for simple queries

Why this works: Some models excel at maintaining engaging dialogue but struggle with deep analysis of large contexts, while others process information more thoroughly but at higher cost.

Check out the article comparing different kinds of models to understand how your model choice impacts the answers you're getting.

5. Store reference materials outside conversations

Instead of repeatedly sharing the same documents, use platforms with knowledge base features that keep reference materials separate from your active chat.

Why this works: Rather than carrying each document between conversations, knowledge bases act like a reference library that the AI can quickly search for just the specific information it needs.

In loqus.ai, you can create knowledge bases that hold far more information than would ever fit in a single conversation, making your AI interactions more context-efficient.

Real-world applications

Information research and analysis

When researching across multiple sources, a two-step conversation approach works best: an initial conversation to identify and organize relevant sources, followed by separate chats for analyzing each important source individually. This structure keeps your research synthesis accurate by maintaining clear boundaries between different sources.

Content creation

For marketing projects, dedicated conversations for different creative phases help maintain clarity throughout the process. Separating your strategy development, content outlines, and revision cycles into distinct chats gives you the advantage of keeping your AI focused on the specific task at hand.

Programming support

When troubleshooting code, creating separate conversations for each component or bug dramatically improves results. Sharing only relevant code snippets in focused chats prevents the AI from trying to connect unrelated parts of your application, resulting in more precise solutions.

Context management cheatsheet

Next time you notice your AI assistant acting "stupid," remember this quick checklist:

• Is this conversation getting lengthy? Start a fresh one
• Am I mixing too many topics? Separate them
• Could I delete old messages I don't need anymore?

At loqus.ai, we make context management simple for you:🧹 Edit and delete messages🧠 Create task-focused assistants in a few clicks👑 Use all the best AI models on the market💎 One subscription — no need to pay to multiple model providersWith loqus.ai, your AI stays smart and on-topic, even in long conversations.