andy nguyen
@kevinnguyendn • 3,448 subscribers
Creator of https://t.co/EMx6p0sbuD | Building an agentic memory layer for coding agents to help millions of devs vibe code better! 🚀 #VibeCoding
Videos
Memory Skill for OpenClaw with 26k+ users in 1 week🚀 OpenClaw's memory system is broken by default. It requires curating massive MEMORY.md files or relying on duplicate-heavy generation. Hours are wasted tuning, and massive amounts of tokens are burned. It's time to stop. So we built the memory skill to solve that prob Here is our superpower ⚔️ 🎯 Top #1 market accuracy (92.19%) after 8+ months of intense architecture iteration 🧠 The ultimate solution to keep the timeline, facts, and meaning perfectly in place ☁️ Local & Cloud + Version control ⚡ Super easy setup
andy nguyen587,723 次观看 • 3 个月前
Memory for OpenClaw is now Native! Our first OpenClaw Memory Skill was a massive success: 30k+ downloads in a week and 500k+ organic impressions overnight for launch post. But we knew memory needed to be native. On March 21, OpenClaw merged PR #50848, allowing us to go beyond the skill layer and integrate directly into the agent’s context assembly flow. We try to make OpenClaw a truly 24/7 employee capable of complex workflows. The technical setup isn’t the hardest part but the real challenge is giving it a "brain" that remembers exact project details, past decisions, and team changes over time. The Native Memory Plugin is now live on NPM & ClawHub. Here is what it brings to your OpenClaw agents: 👉 Native Integration: Automatically manages a Three-Layer Memory architecture (Context Tree, Workspace Memory, Daily Memory). 👉 Git-like Stateful Memory: Organizes memory into a semantic hierarchy of human-readable, diffable Markdown files. You always get updated knowledge and can actually see and fix what your agent learns. 👉 Top Market Accuracy: Achieves an industry-leading 92.2% retrieval accuracy (LoCoMo & LongMemEval benchmarks), maintaining 90% accuracy even with cheap, lightweight models. 👉 Local-first & Portable: Local-by-default, fully portable for multi-agent teams. 👉 Super Easy Setup
andy nguyen168,996 次观看 • 2 个月前
HTML vs Markdown for agent memory: Which is cheaper? Before we ran the benchmark, we expected HTML to cost more because it carries images and charts. Surprisingly it was 42% cheaper. Also 5.9% more accurate and 39% faster The test was conducted across 271 sessions, 603 questions on LoCoMo Check how we tested ↓
andy nguyen20,351 次观看 • 29 天前
We analyzed Anthropic’s memory architecture and built something better: a persistent, human-inspectable, and token-efficient memory layer that scales with your projects. Today, it’s OPEN-SOURCE. ByteRover CLI gives agents (like OpenClaw, Claude Code, and Hermes) persistent, structured memory. Built on the exact architecture that became the #1 memory system for OpenClaw (30,000+ downloads in a week), it lets developers curate project knowledge into a file-based hierarchy. This guarantees highly accurate, lightning-fast retrieval, even with lightweight models. 👉Highly Accurate: >92% retrieval accuracy across long-running sessions - the highest proven production accuracy on the market. ⚡Fast: ~1.6s average retrieval time. 💰Economic: Maintains >90% accuracy even with lightweight models, saving 50-70% on token costs. ☁ Portable: Runs locally by default, with cloud-sync to share memory across agents and teammates.
andy nguyen28,892 次观看 • 2 个月前
If you're a product builder deciding what to ship next, your day is probably filled with: - market research across X, Reddit, HN, etc - going through notes that scattered everywhere: Obsidian, GBrain, wikis, team docs, support tickets, sales calls. With Hermes × ByteRover, this stack saves you hours. ByteRover is the memory that holds every source you care about, and ranks what matters the moment you ask. Hermes is the mind that does the research. The answer is ready before you've finished typing the question.
andy nguyen15,246 次观看 • 1 个月前
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