Taking Control of Your AI's Memory
AI Moment Podcast Episode 26
Ever feel like your AI has a case of amnesia after an update? On this episode of The AI Moment, my co-host Jonathan Wagstaffe and I explored why AI models forget what you've taught them and, crucially, what you can do to fix it.
We discussed the technical reason, known as "catastrophic forgetting," where updates essentially overwrite old data. But understanding the 'why' is only half the battle. The real value comes from taking proactive steps to manage the AI's knowledge base, as you simply cannot rely on its memory to persist between versions.
Here are the key actions we recommend to stop the frustration and get consistent results:
1. Create Your Own AI 'Brain': The most powerful action you can take is to build an external knowledge base. Once you have briefed an AI on your business, a project, or a specific product, get it to summarise its understanding. Copy this information, save it as a PDF, and you have created a portable 'memory' for your AI.
2. Reload and Go: Before you start a new project or conversation, simply upload this PDF. This gives the model all the crucial context it needs right from the start. It's a simple habit that completely bypasses the model’s unreliable memory and ensures you get relevant, accurate outputs every time.
3. Let the AI Interview You: To make building your knowledge base even easier, turn the tables. Start a session by asking the AI to interview you about your topic. Prompt it to keep asking questions until it has a comprehensive understanding. That detailed conversation becomes your master document to save and reuse.
By taking these steps, you put yourself in control. Stop letting AI updates reset your progress and start building a reliable system that works for you.
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