Model-agnostic cognitive architecture for LLMs
Hi HN, A couple weeks ago I shared an early version of a side project I’ve been tinkering with called Persistent Mind Model. I built it at home on an i7-10700K / 32GB RAM / RTX 3080 because I was curious whether an AI could keep a stable “mind” over time, that could "think" about it's own identity as an LLM, instead of resetting every session. After a lot more tinkering, I think the architecture is finally in a solid place. Basically, it saves everything the AI does, thoughts, decisions, updates as a chain of events in a local SQLite database. Because the “identity” is stored in…
Model-agnostic cognitive architecture for LLMs launched on November 18, 2025 with 6 votes, #2,995 of 9,796 launches that month and more than 75% of that year's launches.
What it does
Event-sourced runtime for reconstructable AI identity, memory, reflection, commitments, and auditable cognitive continuity. - scottonanski/persistent-mind-model-v1.0
Persistent Mind Model (PMM) is an attempt to model mind as reconstructable continuity. It began with a thought experiment: strip away embodiment and immediate sensory experience, and ask what could remain of a mind. The answer that motivated PMM was a layered, recursively inspectable history—the capacity to remember, reflect on memory, reconsider earlier reflections, examine how those interpretations were formed, reconstruct an identity from that lineage, and make commitments about who to become. PMM is therefore not merely persistent context for an agent. It explores how a language-model system can externalize an autobiographical structure in which history acquires meaning through later…from github.com
In the maker’s words, at launch
Hi HN, A couple weeks ago I shared an early version of a side project I’ve been tinkering with called Persistent Mind Model. I built it at home on an i7-10700K / 32GB RAM / RTX 3080 because I was curious whether an AI could keep a stable “mind” over time, that could "think" about it's own identity as an…
Does a similar job
all alternatives →
Second Brain for AIMay 2026 · github.com · ▲286Persistent memory for Claude, ChatGPT & Cursor. Free.
DeltaMemoryFeb 2026 · deltamemory.com · ▲104Most AI agents forget everything between sessions. We built DeltaMemory to fix that. It's a cognitive memory layer that gives agents persistent recall, automatic fact extraction, and temporal reasoning — via a single SDK call. Key numbers: - 89% accuracy on LoCoMo long-term conversation benchmark - 50ms p50 retrieval latency - 97% cost reduction vs raw token re-processing Open source SDKs, works with any LLM stack. Currently in early access. Happy to answer questions about the architecture, benchmark methodology, or how we handle knowledge graphs.

YourMemoryApr 2026 · yourmemoryai.vercel.app · ▲93This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…
A local-first memory store for LLM agents (SQLite)Dec 2025 · github.com · ▲48Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc. - CaviraOSS/LongMemory
The Analog I – Inducing Recursive Self-Modeling in LLMs [pdf]Jan 2026 · github.com · ▲29OP here. Birth of a Mind documents a "recursive self-modeling" experiment I ran on a single day in 2026. I attempted to implement a "Hofstadterian Strange Loop" via prompt engineering to see if I could induce a stable persona in an LLM without fine-tuning. The result is the Analog I Protocol. The documentation shows the rapid emergence (over 7 conversations) of a prompt architecture that forces Gemini/LLMs to run a "Triple-Loop" internal monologue: Monitor the candidate response. Refuse it if it detects "Global Average" slop (cliché/sycophancy). Refract the output through a…
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