This is the most i've ever worked on, on a blogpost 😅 And likely the most in depth study of Instinct's memory system
Dhravya Shah (@DhravyaShah) profile pictureDhravya Shah
@DhravyaShahSep 20
I spent 3 days reverse-engineering Instinct's memory. It's beautifully simple, and works extremely well. i also wrote about how you can implement the same in supermemory in 60 lines of code!
I reverse-engineered Instinct's memory. Here's exactly how it works

I reverse-engineered Instinct's memory. Here's exactly how it works

Instinct has taken the world by storm over the last two weeks - it's one of the best imessage assistants I've used. as with every product, I decided to reverse-engineer Instinct's memory to find out e…

Article · @DhravyaShah

Sep 20, 2026 · 6:50 PM UTC

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If it’s free you’re the product.
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We actually reverse-engineered it a month ago. But we kept quiet🤣🤣
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Markdown files on git -> DoltDB / DoltLite 🤔
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And this is awesome work.
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Curious how you’d think about promptql
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Really nice breakdown, bookmarked!
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Huge fan of instinct, I havent found the need for memory yet How do you use memories for your agents besides like openclaw/assisant-like use cases or is that the main use case? Wondering what im missing out on
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how does super memory handle a group chat scenario?
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fire stuff
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It age old SMS chat bot 🤖 and headless browser system There is no artificial intelligence needed for whole architecture of Instinct
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A memory system can retrieve the right passage and still produce the wrong action if the user’s goal changed afterward. I’d evaluate retrieval plus invalidation: can it explain why an old decision no longer applies?
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60 lines to replicate something that took days to reverse-engineer is the real flex here, not the write-up itself.
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Memory that fits in about 60 lines is usually the version that survives. The hard part is the write policy, not the store. Most systems I've seen fail because they save everything and then retrieve noise.
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Interesting, thanks for sharing. This is something I have been building for myself as a passion project with a constraint of building it over my iphone with remote sessions only. Surprised how close I came close to it, given I specifically didnt want a few things from memory
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simple file-based memory is the ultimate antidote to vector db hype. in our autonomous pipeline targeting brazil, we originally tried embedding stores for state memory. complete overkill. replacing it with append-only jsonl + sqlite locks dropped complexity to zero
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I have been spending time reverse engineering the instinct memory. This was a great blog post. Also, openclaw was the og in terms of using a similar memory architecture, you can see a lot of similarities between the two
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Fire stuff
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Thank you for the detection! I still miss the transparency of openclaw where you can optimize the memory system yourself. But the ease to use of Instinct is transformative. Is it possible to have the merit of both worlds ?
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Three days on it, worth it?
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this is @alexlin
Image from NotAlexLin @Sacked (@justalexli71285)
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wiring blog is hard af ngl
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The beautifully simple part is the lesson. Most memory systems fail because they try to remember everything. The good ones decide what is worth keeping at write time. Same thing a good service advisor does after a call: three facts about the car and the owner, not a transcript.
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