Inside the hard problems
The hard problems.
The people
solving them.
Firsthand accounts from the engineers
building AI that has to work in the real world.
FIG. 01Every system holds a story.
01 / The premise
A model sees tokens.
A system needs
context.
What should an agent remember? What should it forget? Who can it trust? The difficult questions begin where the demo ends.
We follow the connections between memory, knowledge, permissions, and the decisions that hold a system together.
Observation 01
Understanding lives
between the pieces.
02 / In practice
What broke?
What changed?
What did you learn?
Conversations with the people who made the call, debugged the failure, and stayed to make it work.
Real constraints. Honest trade-offs. The kind of detail you only get from being there.
Observation 02
The most useful stories
leave the rough edges in.
03 / Our purpose
Make the hard-won
knowledge
common ground.
Conversations become articles. Shared experience becomes field manuals. One engineer’s hard problem becomes another’s starting point.
ConversationsArticlesField manuals