Most chatbots forget everything the second a conversation ends. Ask it
something on Monday, come back Tuesday, and you're a stranger again.
Walrus Sessions 8: "Chatbots That Remember" is a live hackathon
session tackling exactly that — building (or retrofitting) a chatbot
that uses Walrus Memory to persist context across sessions, users,
and devices.
Build or retrofit a chatbot that:
Any use case counts: customer support, onboarding, tutoring, sales,
community bots, even game NPCs.
I spent a few days going deep on the underlying open-source SDK
(MemWal) — not just building with it, but actually reading through the
codebase: the auth layer, the on-chain contract, the sample apps. It's
a genuinely well-built system (constant-time auth checks, on-chain delegate-key verification, careful quarantine/replay protection), and
digging into how persistent memory is implemented securely taught me
more than most tutorials do. Ended up finding and reporting a couple of
real bugs along the way, which the maintainers fixed fast.
If you've ever wanted an excuse to actually understand how persistent, encrypted agent memory works under the hood instead of just calling an
API — this is a good one to dig into, whether you build the full
chatbot or just go bug-hunting in the SDK.