I’ve been using LLM-based AI in some capacity for roughly half a decade, and in that time, the industry has changed significantly. Not only have newer competitors like Gemini and Claude arrived on the scene, but older tools like ChatGPT have also evolved dramatically. We’ve seen better third-party app integration, increased reasoning capabilities, and countless other advancements. However, I would argue that the ability to retain memories matters most.
Retaining context from previous conversations helps the AI better anticipate your needs within a single session. It also allows the tool to learn more about you, ensuring that future conversations are tailored to your preferences. However, there is a real downside to memory accumulation that not everyone considers. I’ve found that starting with a new AI usually requires significant input to generate the responses I need and fully understand my user profile. Once it reaches this data “sweet spot,” the AI becomes much more pleasant to use. Yet, slowly over time, the experience often seems to degrade again.
