Context management for AI systems

Make AI systems trustworthy by giving them exactly the right context.

Let's talk

Mid-talk, turning to gesture at a projected slide of a UMAP scatter plot.

Worked with:

  • Maccabi Healthcare Services
  • IDF
  • Ono Academic College
  • TensorOps
  • VLU
  • Int Unit
  • The Inference Hub
  • RS Law Office

Writing

noteCM-007

How agent memory gets written: hot path versus background

Either the agent writes during the turn and the user waits, or it writes afterwards and the memory is not there for the next question. Each choice hands you a different set of problems.

Read

guideCM-006

The three types of agent memory: semantic, episodic, procedural

Facts, events, and how-to. The split is borrowed from human-memory research, and two public sources already disagree about what belongs in the third category.

Read

noteCM-005

What agent memory actually is, and why the context window isn't it

The model remembers nothing between calls. The context window is the working area for one call, not a store — so anything that persists lives outside the model and has to be re-supplied.

Read

guideCM-001

Do 95% of AI projects actually fail?

No. The study everyone cites says something much narrower, and four of the field's other most-repeated statistics do not survive contact with their sources either.

Read

The whole archive

New pieces by email

Want the agent reading your mail to know how to better manage its context? Subscribe.

Close portrait, smiling.

About

Ori is a founder, keynote speaker, and AI consultant. With more than a decade of experience working with data — from data science to agentic systems and the infrastructure they run on — he deeply understands how data behaves in the wild, and how to harness it to build intelligent, scalable solutions.