Topic
Agent memory & context
How agents remember: context folding, continuity, and state that survives beyond a single conversation.
Fold, don't forget
An agent is a long-term member of your team. The conversation never ends, but the context window never grows. Here's how we solved it: by folding history into a tree that can always be unfolded again.
A User Message Is More Than a User Message
When a user types a message in an AI-native workspace, the system sees far more than text. We unpack Kylon's activation architecture and show how a single message becomes a structured execution contract.
Browse other topics
All posts →AI workspace architecture
What makes an AI-native workspace different from a chat tool or a productivity app: activation, execution, and how work actually gets done.
Comparisons & alternatives
How Kylon differs from other AI tools and agents — architecture, not feature checklists.
Privacy & trust
Data boundaries, permissions, and security when agents can read, remember, and act across your work.
Integrations & connections
How Kylon works with the tools you already use — enrichment, scraping, voice, image, video — through real connections, not screenshots.