memory is core to how you get enhanced output. it is key to defensibility across AI products: 1. increase personalization and therefore lock…

memory is core to how you get enhanced output. it is key to defensibility across AI products: 1. increase personalization and therefore lock-in 2. benefit from distribution through multiplayer-AI interactions; compounded when you onboard colleagues, team-members, and other members in your circle 3. provides your product with defensibility inherently, you can boil down to memory to: "enhance context to get the best output." this is core to how we built our three-layer stack from the ground-up at Decasonic in building our AI-native venture fund. a big part of agent harnesses is how they interact with context memory is just context its therefor impossible to separate harness from memory - as @sarahwooders says, "memory isn't a plugin (it's a harness)"

managed agents are the right form factor but the lock-in is real if your agent harness lives inside a model provider, you dont own the memor…
Model providers don’t lock you in with the API. They lock you in with your own data. Memory is the moat. If you don’t own your agent’s harne…
memory lock-in doesn't kick in when you adopt the harness. it kicks in 6 months later when leaving means starting over from zero. by then th…
Relying on model providers' stateful APIs or harnesses creates lock-in: switching models means losing your agent's memory -- a cost that onl…
Agent harnesses dominate agent building and tie intimately to memory. Closed harnesses behind proprietary APIs force yielding control of age…
Most illuminating graph I have seen for definition of harness. Memory and context are deeply coupled with harness. In my humble opinion, how…

Source: Harrison Chase (X) | 2026-04-12

Related