jums

Hesitation is defeat.

[jums @devjumzzz]

L

[Muratcan Koylan @muratcan]

The problem is how memory gets into the context window and what happens when compaction wipes it.

OpenClaw loads MEMORY[.]md plus the last two days of daily logs at session start. Static injection. Everything gets stuffed into the context window upfront. When the window fills up, compaction fires and summarizes your loaded memories away. The agent silently writes durable memories to disk before compaction hits. But after the window resets, the agent can't systematically browse what it flushed. It runs search queries and hopes the right chunks surface. The memory exists on disk. The agent just lost the ability to walk through it.

This is a context delivery problem.

Everything is a file. Mount memory, tools, knowledge, and human input into a single namespace. Give the agent list, read, write, and search operations. Let it pull what's relevant per turn instead of dumping everything at boot.

Cursor validated this in production with their "dynamic context discovery" approach, which stores tool responses, chat history, MCP tools, and terminal sessions as files that the agent reads on demand. When compaction fires in Cursor, the agent still has the full chat history as a file. It reads back what it needs instead of losing it to summarization.

Markdown memory files exist in OpenClaw. SQLite-backed hybrid search exists. memory_search and memory_get tooling exists. What's missing is the abstraction layer that turns static file loading into dynamic file system access.

Here's what that actually means in practice.

All agent context goes under one predictable namespace. Immutable interaction logs at /context/history/ are the source-of-truth timeline, spanning agents and sessions. Episodic memory at /context/memory/episodic/ holds session-bounded summaries. Fact memory at /context/memory/fact/ stores atomic durable entries like preferences, decisions, and constraints that rarely change. User memory at /context/memory/user/ tracks personal attributes. Task-scoped scratchpads at /context/pad/ are temporary working notes that can be promoted to durable memory or discarded. Tool metadata lives at /context/tools/. Session artifacts at /context/sessions/.

This three-tier split (scratchpad, episodic, fact) replaces OpenClaw's current binary between "today's log" and "forever file." MEMORY[.]md conflates atomic facts like "user prefers dark mode" with episodic context like what happened in last week's project. Daily logs conflate scratchpad work with session notes. Separating them gives each tier its own retention policy and promotion path.

The agent gets explicit file operations at runtime. It can discover what context is available before loading anything. It can pull only the exact slice needed. It can grep by keywords, semantics, or both. It can persist new memory with retention rules and promote validated context from temporary to durable storage. Memory stops being a preload and becomes something the agent discovers, fetches, and evolves per turn.

Between the filesystem and the token window, you need an operational layer. Before each reasoning turn, a constructor selects and compresses context from the filesystem into a token-budget-aware input.

It queries recency and relevance metadata, applies summarization, and produces a manifest recording what was selected, what was excluded, and why.

When memory fails silently, there's no way to ask "what did the agent load and what did it skip?" During extended sessions, an updater incrementally streams additional context as reasoning unfolds, replacing outdated pieces based on model feedback instead of stuffing everything upfront.

After each response, an evaluator checks outputs against source context, writes verified information back to the filesystem as structured memory, and flags human review when confidence is low.

Here's why this changes memory behavior.

Compaction stops being destructive. After the window resets, the agent can still list and read context files directly. Search-based retrieval still works, but now it's paired with structured browsing.

Token usage becomes demand-driven. The agent loads only what the active task requires.

Memory gets a real lifecycle. Scratchpad notes graduate to episodic summaries. Episodic summaries harden into durable facts. Each transition is a logged, versioned event with timestamps and lineage. No more binary split between "today's log" and "forever file."

Human review becomes native. Not just "you can open the Markdown file and check." Every mutation is a traceable event. Humans can diff memory evolution, audit what was promoted and why, and inject corrections that the agent discovers alongside its own memories.

Context assembly becomes debuggable. The manifest records what the constructor selected for each turn. When the agent gets something wrong, you can trace whether it had the right context, loaded the wrong slice, or never found the relevant file.

If you're hitting the same problem, here's the upgrade path that doesn't break existing workflows.

Start by returning file references before snippets and emitting manifests that log what was loaded per turn.

Then expose context sources under /context/* paths and enable list and read at runtime so the agent can browse what's available without loading everything.

After that, shift boot-time injection to minimal preload plus on-demand fetch and decompose MEMORY[.]md into fact and episodic stores with separate retrieval.

The final step adds promotion, archival, retention policies, and audit logs so every state transition is versioned and reversible.

Your system needs to let the agent access context on demand instead of blindly inheriting it at startup.

[jums @devjumzzz]

@aramh More like the former. I like to see ∃x in D as some subset in D that follows some property.

[jums @devjumzzz]

@nodlimax @RossTweetsGames Wrong

[jums @devjumzzz]

@arfa2706 imo that actually makes his attacks more predictable. i tend to get off balanced on projectiles that are being released one-by-one.

[jums @devjumzzz]

@Oxlie_2 playing it without previous sh games in mind is the best way to play it.

[jums @devjumzzz]

@YorchTorchGames @iloveairbagged Bro shut up your games are literally for babies

[jums @devjumzzz]

@xlr8harder it’s a shame EM largely benefited in positioning himself as a boss who prioritizes “hardcore engineering” over managerial/mba shenanigans. it turns out the latter is a safer poison after-all.

[jums @devjumzzz]

@DionysianAgent In Information Theoretic Lens, Entropy is maximized in Uniform Distribution (in discrete case), and in Normal Distribution given fixed mean/var (continuous case) — these two are clearly not chaotic so they’re really two distinct things.

[jums @devjumzzz]

@theo so this is what you meant by "packaging" your videos right

[jums @devjumzzz]

@amritwt If you’re bad at math, then your foundations are shaky. Pick up Spivak’s Calculus and grind on his problems. Rinse and repeat.

[jums @devjumzzz]

@chaitinsgoose Ah yes the “perfect prompts” that’s full of hand holding sub prompts

[jums @devjumzzz]

@DaveShapi you’re terribly wrong last year (agi at sept 2024). you’ll be terribly wrong again by the end of the year.

[jums @devjumzzz]

@xlr8harder @ylecun The funny thing with Yann’s (1-e)^n is it assumes independence. NTP clearly isn’t.

[jums @devjumzzz]

@kilomanjaroe @iamgingertrash Even Einstein needs something concrete to reason out things. That’s why his thought experiments involved real life objects.

[jums @devjumzzz]

@ludwigABAP Been on a similar journey since last yr but its more of relearning math from scratch due to weak fundamentals. Picked up Spivak’s Calculus and after filling up 5 notebooks, im finally at Ch 9. I’ve learned to write proofs from this book and will also start working on Baby Rudin.

[jums @devjumzzz]

@ludwigABAP Not to mention contradictions that hides in plain sight. They’re so much satisfying once you find them.

[jums @devjumzzz]

@ChombaBupe Speaking of shortcuts, this one fallen too short.

[ksa 🏴‍☠️ @kosa12m]

>muh agi

[François Chollet @fchollet]

@xpasky Don't make do it Petr. Don't make me do it.

[roon @tszzl]

everyone is always afraid they’re living in a “bubble”. the natural state of mankind is an archipelago of cultural villages. you need to be in a bubble for your own health and optimal performance. everything good that’s ever happened happens in a bubble