
Whisper
Persistent memory for ai agents
What it does
AI agents forget context between chats—hallucinate, repeat, lose track. Frustrating. Usewhisper adds real, persistent memory: agents remember conversations, facts, and details forever. Support bots recall tickets. Assistants continue seamlessly. Code agents keep project context. Custom Ai agents mostly We support all One command to add it: npx whisper-wizard <60 seconds setup. Free tier. Persistent memory for reliable agents. Run now ↑ | Feedback in comments
Does a similar job
all alternatives →- AgentmemoryMay 2026 · agent-memory.dev · ▲322
Persistent memory for Claude Code, Codex & coding agents



Second Brain for AIMay 2026 · github.com · ▲286Persistent memory for Claude, ChatGPT & Cursor. Free.
- CAChatIndex – A Lossless Memory System for AI AgentsNov 2025 · ▲17
Current AI chat assistants face a fundamental challenge: context management in long conversations. While current LLM apps use multiple separate conversations to bypass context limits, a truly human-like AI assistant should maintain a single, coherent conversation thread, making efficient context management critical. Although modern LLMs have longer contexts, they still suffer from the long-context problem (e.g. context rot problem) - reasoning ability decreases as context grows longer. Memory-based systems have been invented to alleviate the context rot problem, however, memory-based…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, March 2026
the whole month →

Switch from ChatGPT to Claude with import memory feature
AI · Mar 2026 · claude.com


