... Product Hunt! I m Elisa, co-founder and COO of Memoket and also a working mom of two boys. Before Memoket

... making long-running engineering tasks, multi-step workflows, and delegated agent work far more consistent. Tollecode is a local-first AI coding assistant built for real engineering work: File reads Shell commands Sub-agents Full control over execution New Memory Commands: /memory Show memory

... Self-becoming is an experimental open-source runtime that connects a long-running LLM instance to memory, self-state, reflection, rules, tools, and autonomous rhythms, exploring whether an AI can develop a functional sense of self over time. Hi Product Hunt, I m sharing Self-becoming . Most AI agents are built around tasks: answer faster, call tools better, complete workflows. Self-becoming asks a different question: What engineering conditions could allow an AI instance to maintain a functional self over ... ... time? This is not a roleplay prompt or a static character card. Self-becoming gives a long-running LLM instance: persistent autobiographical memory

... fintech startup and we've just raise $4m So we rebuilt our context system, to help Pretty Prompt give better results. (Best part, the user owns that context, and can use it across any LLM) Launching today Instructions vsMemory. Instructions Explicit rules that always apply. Examples: No em-dashes Keep answers under 512 characters Use bullet points

... Week on Product Hunt. It was a genuine surprise. We celebrated briefly and then got back to work. Because the win wasn't the point. The point was always the bigger vision: to build an open memory layer instead of restricted in one AI tool, we want to build an ecosystem where you decide where your knowledge lives and which AI model or tool gets to use it. What we validated and what we chose ... ... become. Here's what we built along the way. What we shipped Save context from anywhere.  You can now select any text on any webpage or inside any AI chat, right-click, and save it directly to your memory

... MbMc (multiband, 1 6 bands) and MbMcMsc (multiband + inter-plugin sidechain). All 4 share the same compression engine with 6 emulation types: Optical , VCA , FET , Tube , Bus and Digital . The feature I'm most proud of is the shared memory sidechain McMsc and MbMcMsc can route audio sidechain between plugin instances across tracks without any DAW routing cables, using lock-free ring buffers in shared memory

... another AI tool , but more like a layer across tools. The idea in practice: Instead of starting from zero every time, you can: Save context once reuse it across different AI tools Organize different projects into separate memory buckets Capture knowledge from webpages and bring it into AI instantly Use selected context when chatting, depending on the task Connect your memory

... Product Hunt! I'm Sourav, builder from India. Spent 6 years building AI products for others. Memoair is my first startup. The problem I kept hitting: AI has no memory

... Most spaced repetition apps are too complex. Learn why MemoRep's 30-second card rule and email reminders build better habits than feature-heavy apps like Anki or Quizlet. You want to remember what you learn. You've tried apps that promise to help, but they keep getting in the way. Let me guess: you opened Anki once. Saw dozens of options. Tags, decks, subdecks, burying intervals, custom scheduling, plugins, themes, synchronization, statistics, add-ons... and closed ... ... Quizlet. Found pre-made decks, spent hours organizing them, never actually reviewed. Here's the uncomfortable truth: most spaced repetition apps are designed by power users for power users. They've lost sight of the actual goal: remembering things. MemoRep

... massive datasets, they can be expensive, complex to query, and act as complete black boxes. If a search returns a weird chunk, diagnosing it is often a nightmare. Lately, I've been experimenting with a dead-simple alternative for smaller projects, and I'd love to know if anyone else is doing this: Dump raw data into a local folder. Use a strict markdown schema (like a CLAUDE.md or similar instruction file) to tell the LLM how to summarize ... ... Yara Simone(@yara_simone): What's the failure mode when the model misinterprets links? Comment from Jason Kim(@jason_kim18): Definitely overkill. I've been sticking to markdowns + backlinks for most of the cases. found helpful to introduce tiered memory

... live? Scattered across chat histories. Fragmented across different platforms. Sometimes contradictory, & mostly out of date. The problem is: ' . Throughout our 9 months of building, the pattern is always the same: raw memory without curation becomes noise. And noise produces worse AI outputs, not better ones. This is why we built . It's the place where your AI memory

... just launched MemoryBriefcase , a Chrome extension designed to help you stay organized without the clutter. What it does: One-Click Saving: Quickly bookmark any page or resource. Smart Organization: Categorize your links so you can actually find them later. Lightweight Performance: Built to stay out of your way until you need it. I d love to get your feedback on the UI and hear what features you d like to see next. Check it out here: MemoryBriefcase

... Every time you open a new AI chat, you start from zero. Who you are. What you're building. Your preferences. Your goals. Again. And again. And again. MemoryBriefcase fixes that. It gives every AI you use ChatGPT, Claude, Gemini, Cursor your full context instantly. No re-explaining. No copy-pasting. No repeated prompts. --- What it does - Stores your identity, work, goals, and projects in one structured place - Connects to all major AI tools - Automatically injects your context into every ... ... session Set it once every AI knows you. --- Why it matters AI tools are powerful but they forget everything. MemoryBriefcase

... OpenCut AI, and this one changes what hardware you need to run the full AI stack. The problem we had OpenCut AI runs everything locally -- LLM, transcription, voice cloning, image generation. That's great for privacy, but brutal on memory. Running the full stack needed 35+ GB RAM. Most of our users have 8-16 GB laptops, so they were stuck with tiny 1B models that gave mediocre scripts, slow commands, and limited context. What TurboQuant does TurboQuant implements ... ... algorithms from Google Research paper PolarQuant and QJL. That compress the KV cache (the biggest memory

... Extract Conversations Cross AI captures your past interactions and memory from one AI platform directly from your browser. Summarize & Prepare The extension condenses your AI memory

... After about 14 months of building, I m launching Memory Stream by CMPSBL on Product Hunt on March 13. It s an AI infrastructure layer where you can discover, package, and export working software pipelines automatically. Inside the system there are around 1000 capabilities across 40 autonomous nodes, which creates a design space larger than a million times the stars in the observable universe . The Memory

... Mnexium Integrations feel like one of the most important parts of the platform because they solve a different problem than memory. It also outlines the completion of the feature-set for the platform. I don't think any more features will offer any more utility. Memory

... This is what philosophers call the "teleportation problem." If you step into a machine that destroys you and recreates you atom-by-atom on the other side, did you travel or did you die and someone else got your memories? The fruit fly experiment makes this even more interesting. That simulated fly can't fly. It exists in an incomplete world. So even if it has some form of experience, it's experiencing a kind of sensory deprivation ... ... operations should terrify us a little. Comment from Alexey Glukharev(@alexeyglukharev): When people talk about brain cloning or creating a digital copy of a person, I always come back to the role of the body. We are not just memories

... Hello everyone, I built an open-source tool called LEAX. https://github.com/hooop/leax It s a CLI that acts as a companion to Valgrind to help understand memory leaks in C programs. It combines Valgrind analysis, GDB-based tracing, and Mistral AI to: identify the root cause of a leak explain why it happens suggest a possible fix The memory

... Mimic AI Desktop Assistant A privacy-first, AI-powered desktop assistant with voice synthesis, persistent memory, and local model inference. Mimic AI runs entirely on your local machine using Ollama for language models and supports Browser TTS and Qwen3-TTS for voice synthesis. Table of Contents Features System Requirements Installation Quick Start Architecture Overview Data Flow Component Interaction Configuration Usage Guide Troubleshooting Privacy & Security Features Core Capabilities Local AI Inference : Uses Ollama for running LLMs locally (Llama, Mistral ... ... Voice Synthesis : Browser TTS (no setup) and Qwen3-TTS (AI voice cloning) Persistent Memory

... stitch systems together. The browser extension was a patch. This is infrastructure. Here's what makes it different at the architecture level: The AI pulls what it needs, when it needs it (via semantic search across your memory) It writes back. Conversations, decisions, and new context get saved from within any chat It works outside the browser entirely (IDE, CLI, local models, anywhere) Every tool connects to the same memory

... captures more of an AI workload. There will always be new features & improvements we can make. This is one of those, we've always had and seen a need in the platform to direct and instruct our memory generation layer. This is what memory

... Today we re open-sourcing the core memory engine behind @Mnexium AI : CORE-MNX. GItHub NPM For us, this is a product decision and a philosophy decision. Memory

... Mnexium SDKs give you a complete memory infrastructure as a service. Install the package, pass your LLM provider key, and your AI remembers. Node ( https://www.npmjs.com/package/@m... ) Python ( https://pypi.org/project/mnexium/ ) Docs ( https://mnexium.com/docs ) Get Started Both SDKs are MIT licensed and available now. No sign-up required omit the API key and a trial key is auto-provisioned on your first request. JavaScript / TypeScript npm install @mnexium/sdk import { Mnexium } from '@mnexium/sdk'; const mnx = new Mnexium({ apiKey: 'mnx_...', openai ... ... apiKey: process.env.OPENAI_API_KEY }, }); const alice = mnx.subject('user_123'); // Chat with memory

... Built It Most automation workflows can call a model, but still need substantial glue code for memory, personalization, and structured data. The Mnexium connector makes those capabilities native in n8n. npm install n8n-nodes-mnexium Install once, then add the Mnexium node in n8n. What You Get Chat operations with memory