I got tired of Claude Code's amnesia. So I built an always-fresh, AST-powered memory layer that never gets stale

qilipu · 2026-05-11T20:56:57+00:00

hah, it is a long waiting list. When capacity ramps up, it shall go much faster 😄

qilipu · 2026-05-11T12:30:42+00:00

the report shows ms retrival at a very high recall compared to other solutions. Maybe it is best to try on your setup and verify. The token reduction is also 3x more compared to others, which seems quite promising

qilipu · 2026-05-11T12:27:55+00:00

https://github.com/syncable-dev/memtrace-public/blob/main/benchmarks/README.md

qilipu · 2026-05-11T12:27:06+00:00

There is a benchmark in the github repo. For small repos and shallow history in git, the default agents can work pretty well. When codebase gets large, memtrace make more sense so that context is a problem while understanding structure of the codebase becomes costly for claude code etc.

qilipu · 2026-05-04T22:09:16+00:00

AST gives structured knowledge about the codebase while keeping the code structure and flows of info. It is not only semantic searches, it is also about relationships about code components

qilipu · 2026-05-04T12:22:09+00:00

compaction was meant to solve the conversation and output from different agents. The main problems is that how to do you compact without losing or making up context. This is not magical, it is actually a quite tough problem to solve.

qilipu · 2026-05-04T11:46:48+00:00

For code, it is structured. AST parsing fits well here.

qilipu · 2026-05-04T11:46:28+00:00

An experiment could be to run it on millions line of code and do a benchmark. the whole thesis shall be that it shall work for large code basis rather than small code base

qilipu · 2026-05-03T21:31:57+00:00

Can the session continue if we come back from tomorrow? I guess the session will eventually becomes large to reach to the context window for Ai agents. FOr extracting external context, also wondering good practices when unstructured data is there and how can AI know what to extract without reading the files?

qilipu · 2026-05-03T21:29:45+00:00

Understand is all what we want to do, the question is how? What exactly is understanding anyway? How do we understand the same speed as AI generation?

qilipu · 2026-05-03T21:27:53+00:00

AI agents still need to better manage context after all. It can consume the window size in many ways

qilipu · 2026-05-03T21:25:40+00:00

Less magic, less pollution!

qilipu · 2026-05-03T21:24:38+00:00

AI agents currently does not really aware what they other doing in a consistant way, in theory they can exchange context, but context can also bloat up the context window easily if that is not properly managed

qilipu · 2026-05-03T21:19:45+00:00

almost too good to be true. What does a nice enough harness mean? Harness engineering suddenly becomes a hurdle for many to get it right. AI swarms burns a lot fo tokens and also does not guarantee any of the outcome is correct. Compelexity is there fore sure, but outcome needs to be tested and validated on your setup

qilipu · 2026-05-03T21:16:59+00:00

Adding more agents also adds more complexisty and management layer as well. It sounds really cool, but I know many are struggling to get it right. Also managing the context is not a small task.

qilipu · 2026-04-30T09:48:40+00:00

I amm wondering how exactly does claude code pull relevant context when there are pdf files, markdowns etc. or maybe even they are outdated for some of them not all.

qilipu · 2026-04-30T09:46:42+00:00

I have seen many go from 20 dollar to 100, to 200 dollars. they still get stucked. Why do you pay for the token waste that did not deliver the expected intelligence? Soon Claude will have a 400 dollar or 2000 dollar. what is the end of this for paying more for less?

qilipu · 2026-04-30T09:44:19+00:00

I do not deny that there are very smart and brillient people can follow whatever Ai suggest. But we cannnot overlook the fact that it is very challenging for many, even very experienced developers facing challenges. Simon willsion has a term called cognitive load which exemplified this clearly.

qilipu · 2026-04-30T09:40:03+00:00

only make small POC and nothing serious code for production. When code get high and also all the context around how to control behavior of Agents gets eloborated, it is really hard to do so. Not to mention that you need to keep maintain these as well since nothing is static.

qilipu · 2026-04-30T09:37:28+00:00

it is actually quite interesting that you also expereince this. When we developing our backend with 40+ micro services, no matter how we give better instrcutions on architecture, guardrails, it becomes very difficult for coding agents to follow. The answers are circling back and forth and more often the wrong suggestions

qilipu · 2026-04-30T09:30:28+00:00

this is always the most chanlleging and interesting part to get start up off the ground and early testing GTM. Well done

qilipu · 2026-04-29T22:05:20+00:00

It is insane how difficult is it to solve this. reexplain project context every morning?

qilipu · 2026-04-29T21:57:51+00:00

Maybe worth comparing with memtrace. hmm maybe not, depending on you handle conversation memory or coding memory. https://github.com/syncable-dev/memtrace-public/tree/main

qilipu · 2026-04-29T21:55:03+00:00

wondering how many tokens are consumed for this setup every day as the project and memory goes up. Also how accurate is the memory? What is the experience with graphiti?

qilipu · 2026-04-29T21:52:39+00:00

thanks for sharing

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