Compact a summary of a summary and you get generational photocopy loss' — anyone who's run a week-long agent project has felt exactly this. The gist survives, the why turns to soup. Trying this out today.
Compaction amnesia is why you keep re-explaining
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The phrase that stuck with me was:
"The agent survives, but the work does not."
I think that's a useful way of describing the difference between retaining context and retaining memory.
What you're describing feels less like a context-window problem and more like a Memory as Infrastructure problem. The expensive part isn't usually losing facts. It's losing decisions, tradeoffs, rejected approaches, architectural reasoning, and unresolved work that must later be reconstructed.
What's interesting is that compaction doesn't eliminate that cost. It simply transfers it. The model forgets, and the human becomes responsible for rebuilding the missing context.
In the Sovereign Systems Specification, I describe a related anti-pattern as a "Digital Attic", the assumption that dumping large amounts of information into storage will somehow preserve understanding. What often matters most isn't the raw conversation history. It's the durable record of why particular decisions were made and what evidence supported them at the time.
The challenge, in my view, isn't building better summaries. It's deciding which information should never be dependent on a context window in the first place.
That's where concepts like Reasoning Ledgers and Memory as Infrastructure start becoming interesting. The goal isn't to preserve every token. The goal is to preserve the work.
@[Ken W. Alger] This is the part I’ve been circling around too: the context window is the wrong place to store anything that will become load-bearing later.
Raw transcript feels safe, but it quickly becomes an attic. You still need someone to recover the decision, the rejected path, the evidence, and the next move.
That’s why I’m leaning toward small explicit artifacts instead of bigger summaries — memory as a working surface, not just more storage.
@[Vinh Nguyen] I like the "load-bearing" framing.
Once a piece of information becomes necessary to explain future decisions, coordinate future work, or avoid repeating past mistakes, it starts looking less like context and more like infrastructure.
That's also why I think the Digital Attic pattern shows up so often. We keep accumulating transcripts because they're easy to store, but the load-bearing pieces are usually much smaller: decisions, rejected approaches, assumptions, evidence, open questions, and next actions.
The artifact idea is interesting because it shifts the goal from preserving conversation to preserving intent. A transcript tells us what was said. A well-designed artifact tells us what mattered.
At that point, the question becomes less "How do we keep more context?" and more "What information deserves to become durable memory in the first place?"
That feels like a much more scalable problem to solve.
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