reference
Living

Field notes

Field notes start from the symptom — the sentence you’d actually type when your AI stops remembering — and work down to the mechanism, never the other way round.

Most explanations of AI memory open with a definition and wait for you to recognize your situation inside it. These seven pages open with the situation: the AI went blank mid-task, the reply got slower, the bill spiked for no reason you can see. Read the one that matches, then decide whether you want the mechanism or the fix.

§01 · start here

Find the sentence you'd type at midnight.

Seven pages, split by what you're actually feeling: the AI went blank mid-task, or the same work is quietly costing more than it used to.

Every number cited across the seven is pulled from production telemetry or a public bug report, not invented for the page. Each one also names what people try first, and where that stops working, before it says what actually helps.

§02 · why it happens

The forgetting, mechanism by mechanism.

What you're seeingThe mechanism
compaction fired, then it went thinThe recap keeps the conclusion and drops the work behind it, every time, on purpose. read the mechanism →
you don't know what got deletedMostly tool results, and you pay for the loss twice — once in the summary, once in the cache miss. see what goes →
it's worse than it was an hour agoNothing has dropped yet. The decay starts before compaction ever fires. read the decay curve →
the context bar won't moveThe ceiling where /compact stops being a choice and starts being forced. read what to do →
§03 · what it costs

The same problem, priced.

What you're seeingThe cost
every reply feels slower than the lastRe-sending a growing transcript on every call compounds. The bill grows like a triangle, not a line. read the bill shape →
the bill spiked and the work didn't changeAn idle gap, a model switch, a bad automation interval — any of them breaks the cache, and the next turn prices in full. find the break →
caching is on and it's still expensiveCaching taxes repetition. It never lowers what the model has to read, and the prompt keeps growing underneath it. read what caching misses →
§04 · the manual

Where AI failure modes fits.

The seven pages above each explain one mechanism. AI failure modesis a different kind of page: ten foundational facts and ten operator practices for the working relationship itself, each cited to a real logged incident. Read it when the question isn’t “why did this happen,” but “how do we work together so it happens less.”

§05 · common questions

Common questions.

Is this the same as retrieval or RAG?

These seven stay inside one conversation. How memory works across sessions is the encyclopedia’s question — start with substrate memory, its cornerstone.

Does a bigger context window fix this?

It raises the ceiling inside one session. The record still lives only in that session, so a fresh one starts blank again. the longer version is here.

Are these specific to Claude Code?

The receipts happen to be measured there — it's where the loudest bug reports are. The mechanism, a stateless model re-reading a growing transcript, is the same everywhere a conversation gets compacted or summarized.