When AI Remembers: Beyond Big Models
The Next Frontier of Intelligent, Context-Aware Work
I was thinking this morning about how essential the "memory feature" is becoming in AI. It’s not just about bigger models or more tokens, it’s about truly remembering you. Once you’ve invested in training an AI with your spreadsheets, presentations, and personal preferences, it stops being a generic chatbot and becomes more like a second brain.
What’s fascinating is how this can strengthen network effects for companies building GPT-like features. The more each user adds their own data and context, the more these "fragmented islands" of hyperpersonalized knowledge grow. Eventually, you end up with a second source of truth unique to each individual, connected to the company’s primary systems. It’s pure lock-in: who wants to abandon something that’s so intimately curated?
Of course, it’s not all smooth sailing. Privacy is a concern, and AI memory can "hallucinate" or mix up past information. But if companies nail the privacy safeguards and refine how memory is stored, the payoff is huge. Every interaction continuously upgrades the AI’s understanding of you and your team. In markets where products look increasingly similar, like some B2B SaaS categories, an AI with robust memory becomes the difference between a passing novelty and a mission-critical tool.
And here’s the kicker: most of the data we’re working with is unstructured. PowerPoints, PDFs, Slack chats, random Google Docs… figuring out how to harness it is the next big thing on everyone’s roadmap. Whoever masters this combination of memory and unstructured data first won’t just have a feature, they’ll have an unbeatable moat.
Are you building something like this? Please let us know.