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Meet Bezalel Bezalel is a capability plane for your agents (claude, codex, OC, hermes, etc) one MCP gives your agent: 💻 computer ⌛️ sandbox 🍎chat via iMessage 📧agent's own email +1k connectors 🧠memory 💳 a card (soon) (it's in alpha and it's free)

Micky

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184,865 次观看 • 8 天前 •via X (Twitter)

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API-first email built for AI agents One prompt to plug in via MCP or Agent Skill Your agent gets its own inbox – and can run any workflow over email Free in open alpha - link in comments

API-first email built for AI agents One prompt to plug in via MCP or Agent Skill Your agent gets its own inbox – and can run any workflow over email Free in open alpha - link in comments

Atomic Mail

218,583 次观看 • 2 个月前

YOUR AI AGENT JUST GOT ITS OWN EMAIL Atomic Mail shipped an email API built for agents, not people. One prompt and your agent registers its own inbox, then reads, sends and replies on its own. - Self-signup in ~30 seconds, no human, no CAPTCHA, no card - Plugs into Claude Code, Codex, Cursor and OpenClaw via MCP or one line - Runs on JMAP, a standard models already know - Already running support inboxes and newsletter digests unattended The agents have inboxes now.

YOUR AI AGENT JUST GOT ITS OWN EMAIL Atomic Mail shipped an email API built for agents, not people. One prompt and your agent registers its own inbox, then reads, sends and replies on its own. - Self-signup in ~30 seconds, no human, no CAPTCHA, no card - Plugs into Claude Code, Codex, Cursor and OpenClaw via MCP or one line - Runs on JMAP, a standard models already know - Already running support inboxes and newsletter digests unattended The agents have inboxes now.

BuBBliK

15,573 次观看 • 2 个月前

Anthropic just launched Computer-Use-Agents on Claude Desktop, meaning it can now take control of your entire computer environment. This is huge for businesses and enterprise, except it's limited by the fact that it requires a personal computer. If you deploy it into a virtual machine on Orgo, you can now manage hundreds or thousands of your clients' Claude accounts, setting up their skills, capabilities, connectors, etc, all on their own machines in the cloud on Orgo.

Anthropic just launched Computer-Use-Agents on Claude Desktop, meaning it can now take control of your entire computer environment. This is huge for businesses and enterprise, except it's limited by the fact that it requires a personal computer. If you deploy it into a virtual machine on Orgo, you can now manage hundreds or thousands of your clients' Claude accounts, setting up their skills, capabilities, connectors, etc, all on their own machines in the cloud on Orgo.

Nick Vasilescu

38,333 次观看 • 5 个月前

$HERMES AGENT CAN SHARE MEMORY WITH CODEX AND CLAUDE CODE THROUGH HINDSIGHT. ONE MEMORY BANK. ONE AGENT REMEMBERS, EVERY OTHER AGENT KNOWS. the problem: you use Hermes for orchestration. Codex for coding. Claude Code for debugging. each has its own memory. switch between them and you explain the same project three times. Hindsight fixes this. one shared memory bank that every agent reads and writes to. tell Codex: "the test color for this project is purple." switch to Hermes. ask: "what test color did I pick?" Hermes answers: "purple." no copy-paste. no re-explaining. instant recall. HOW IT WORKS: Hindsight runs as a Docker container on your machine. self-hosted. your data stays local. an LLM powers the memory processing (retain, recall, reflect). RETAIN: extracts facts from your conversations. entities, decisions, preferences, project context. saved to the memory bank automatically. RECALL: when you ask a question, Hindsight pulls from semantic search, keywords, graph connections, and temporal data. fused into one answer. REFLECT: deeper reasoning layer. connects memories across sessions. identifies patterns in your work. produces observations that get smarter over time. CONNECT TO HERMES: Desktop app: Settings → Memory and Context → switch provider from Namosin to Hindsight. set API URL to your local Docker container. set bank ID. done. CLI: hermes memory setup → select Hindsight. verify: hermes memory status should show: provider: hindsight, installed, available. CONNECT TO CODEX: npx hindsight-coding-agents install codex \ --self-hosted --server this installs lifecycle hooks: initialize memory on session start. recall context during work. retain the session when done. enable hooks in Codex: Settings → Hooks → trust all three. CONNECT TO CLAUDE CODE (same command): npx hindsight-coding-agents install all "all" connects every detected agent on your machine. Claude Code, Codex, Cursor, and others. one command. every agent shares the same bank. TAGS FOR FILTERING: every memory gets tagged by harness (Hermes, Codex, Claude Code) and optionally by project name. in the Hindsight control plane: filter by harness. see only Hermes memories. or only Codex memories. or search across everything. soft partitions inside one bank. not hard walls. cross-reference when you need to. ONE BANK OR MANY: one global bank: solo dev, related projects. all agents share everything. patterns emerge across projects. per-project banks: unrelated codebases. each project gets its own memory. no cross-contamination. your call. start with one. split when projects diverge. KNOWLEDGE PAGES (v0.9.0): Hindsight auto-generates living summaries from your accumulated memories. components, concepts, conventions, decisions. not static docs. projected from real agent conversations. auto-refresh as new memories land. WHAT TO KNOW: self-hosted via Docker. your data never leaves your machine. backup system built in (admin CLI + scheduled exports). works with any LLM (local Ollama, OpenAI, Codex subscription). memory defense: redact or block sensitive content automatically. 33,000+ memories accumulated in ~10 days of normal use.$

HERMES AGENT CAN SHARE MEMORY WITH CODEX AND CLAUDE CODE THROUGH HINDSIGHT. ONE MEMORY BANK. ONE AGENT REMEMBERS, EVERY OTHER AGENT KNOWS. the problem: you use Hermes for orchestration. Codex for coding. Claude Code for debugging. each has its own memory. switch between them and you explain the same project three times. Hindsight fixes this. one shared memory bank that every agent reads and writes to. tell Codex: "the test color for this project is purple." switch to Hermes. ask: "what test color did I pick?" Hermes answers: "purple." no copy-paste. no re-explaining. instant recall. HOW IT WORKS: Hindsight runs as a Docker container on your machine. self-hosted. your data stays local. an LLM powers the memory processing (retain, recall, reflect). RETAIN: extracts facts from your conversations. entities, decisions, preferences, project context. saved to the memory bank automatically. RECALL: when you ask a question, Hindsight pulls from semantic search, keywords, graph connections, and temporal data. fused into one answer. REFLECT: deeper reasoning layer. connects memories across sessions. identifies patterns in your work. produces observations that get smarter over time. CONNECT TO HERMES: Desktop app: Settings → Memory and Context → switch provider from Namosin to Hindsight. set API URL to your local Docker container. set bank ID. done. CLI: hermes memory setup → select Hindsight. verify: hermes memory status should show: provider: hindsight, installed, available. CONNECT TO CODEX: npx hindsight-coding-agents install codex \ --self-hosted --server this installs lifecycle hooks: initialize memory on session start. recall context during work. retain the session when done. enable hooks in Codex: Settings → Hooks → trust all three. CONNECT TO CLAUDE CODE (same command): npx hindsight-coding-agents install all "all" connects every detected agent on your machine. Claude Code, Codex, Cursor, and others. one command. every agent shares the same bank. TAGS FOR FILTERING: every memory gets tagged by harness (Hermes, Codex, Claude Code) and optionally by project name. in the Hindsight control plane: filter by harness. see only Hermes memories. or only Codex memories. or search across everything. soft partitions inside one bank. not hard walls. cross-reference when you need to. ONE BANK OR MANY: one global bank: solo dev, related projects. all agents share everything. patterns emerge across projects. per-project banks: unrelated codebases. each project gets its own memory. no cross-contamination. your call. start with one. split when projects diverge. KNOWLEDGE PAGES (v0.9.0): Hindsight auto-generates living summaries from your accumulated memories. components, concepts, conventions, decisions. not static docs. projected from real agent conversations. auto-refresh as new memories land. WHAT TO KNOW: self-hosted via Docker. your data never leaves your machine. backup system built in (admin CLI + scheduled exports). works with any LLM (local Ollama, OpenAI, Codex subscription). memory defense: redact or block sensitive content automatically. 33,000+ memories accumulated in ~10 days of normal use.

YanXbt

29,045 次观看 • 12 天前

Finally, a proper chat UI for Hermes Agent (open-source)! Hermes ships an official dashboard, but it's primarily built for management, and its chat is just a terminal piped into a browser tab. Hermes Web UI is an open-source chat-first alternative. It's self-hosted and points at your existing ~/.hermes state, so there's nothing new to configure. - It's a native web chat, not a terminal in a tab - Sessions group by date with a context ring - Kanban renders the agent's task board - Spaces manages your workspaces - Skills panel lists the full catalog - Tasks panel shows cron jobs - Insights show usage and activity - Memory shows MEMORY and SOUL files - Logs tails the agent, gateway, and error logs The whole setup runs 100% locally, binds to localhost by default, and you reach it over an SSH tunnel or Tailscale from your phone. I have shared the Hermes Web UI GitHub repo in the replies. Do note that it's a community project, not official, so expect occasional rough edges (concurrent profile runs are blocked for now). To dive deeper into Hermes Agent, my co-founder wrote a full masterclass about it, covering the learning loop, the memory tiers, self-evolving skills, GEPA, and running multiple isolated agents. Read it below.

Avi Chawla

77,966 次观看 • 3 个月前

The barrier to deploying AI agents just hit zero. Akash Agents is a streamlined way to launch your OpenClaw or Hermes agent with a few simple clicks. Deploy instantly. No terminal, YAML, or cloud console required. Just your agent's logic, memory, and capabilities. Hermes by Nous Research ships with 40+ built-in tools, persistent memory, and subagent parallelization, making the experience best-in-class out of the box. → Try it for free at Built by our community member Sandeep Narahari

The barrier to deploying AI agents just hit zero. Akash Agents is a streamlined way to launch your OpenClaw or Hermes agent with a few simple clicks. Deploy instantly. No terminal, YAML, or cloud console required. Just your agent's logic, memory, and capabilities. Hermes by Nous Research ships with 40+ built-in tools, persistent memory, and subagent parallelization, making the experience best-in-class out of the box. → Try it for free at Built by our community member Sandeep Narahari

Akash Network

22,891 次观看 • 5 个月前

You probably don’t use just one AI agent anymore. Maybe Codex for coding. Claude Code for research. Cursor for quick edits. Hermes for the rest. Each one is great at something different. But every time you switch, you have to start over — re-explaining your project, preferences, and the way you like to work. Your agents know how to help you. They just don’t share a memory of you. memU just shipped an update that fixes this. One personal memory, shared across every agent and device you use. What Codex learned last night, Claude Code can remember this morning. 🧵

You probably don’t use just one AI agent anymore. Maybe Codex for coding. Claude Code for research. Cursor for quick edits. Hermes for the rest. Each one is great at something different. But every time you switch, you have to start over — re-explaining your project, preferences, and the way you like to work. Your agents know how to help you. They just don’t share a memory of you. memU just shipped an update that fixes this. One personal memory, shared across every agent and device you use. What Codex learned last night, Claude Code can remember this morning. 🧵

Hasan

22,362 次观看 • 1 个月前

🚀 LangSmith Agent Builder is now available in Public Beta Now anyone can create production ready agents without writing code, just chat. Agent Builder guides you from initial idea to deployed agent, creating detailed prompts, selecting required tools, and even creating subagents. Our Beta release also includes: 🧰 Bring your own tools via MCP server 🧩 Browse, copy, and customize agents across a shared workspace 🧠 Use your preferred model Try Agent Builder free: Read more on the launch:

🚀 LangSmith Agent Builder is now available in Public Beta Now anyone can create production ready agents without writing code, just chat. Agent Builder guides you from initial idea to deployed agent, creating detailed prompts, selecting required tools, and even creating subagents. Our Beta release also includes: 🧰 Bring your own tools via MCP server 🧩 Browse, copy, and customize agents across a shared workspace 🧠 Use your preferred model Try Agent Builder free: Read more on the launch:

LangChain

37,833 次观看 • 9 个月前

We just launched a new primitive for AI Walrus Memory gives your agents persistent, portable memory that you own, and it drops straight into the platforms you already build on. Anthropic Claude, OpenAI ChatGPT, and Google Gemini, you name it plus native MCP and SDKs, added in a few lines of code LIVE TODAY

We just launched a new primitive for AI Walrus Memory gives your agents persistent, portable memory that you own, and it drops straight into the platforms you already build on. Anthropic Claude, OpenAI ChatGPT, and Google Gemini, you name it plus native MCP and SDKs, added in a few lines of code LIVE TODAY

Adeniyi.sui

46,208 次观看 • 2 个月前

Codex is now a full video editor! Our new plugin opens a full built-in NLE right inside the Codex app, where you and your agent can edit together, effortlessly. If you're already paying for Codex, you get this one for FREE. It's available now. Start using it in 1 minute, by just telling your Codex: "Turn Codex into a Video Editor, read

Codex is now a full video editor! Our new plugin opens a full built-in NLE right inside the Codex app, where you and your agent can edit together, effortlessly. If you're already paying for Codex, you get this one for FREE. It's available now. Start using it in 1 minute, by just telling your Codex: "Turn Codex into a Video Editor, read

ChatCut

1,877,835 次观看 • 1 个月前

stop stressing with Claude Code and OpenClaw for DIY trading bot setups introducing Sides Agent — a pre-configured autonomous AI agent for Polymarket. lives in your Telegram. no terminal, no MCP wiring describe your strategy in plain english → it runs 24/7 in your budget cap ◢ Polymarket CLOB, batch trades, one-tap confirm ◢ EV, Kelly sizing, basket arb, X sentiment via Grok ◢ tick memory, auto-pause on 3 failures, budget reservation built it for myself. now it's yours first 500 activations are FREE comment "agent" + RT + follow Sides.Trade – Polymarket AI Bot

stop stressing with Claude Code and OpenClaw for DIY trading bot setups introducing Sides Agent — a pre-configured autonomous AI agent for Polymarket. lives in your Telegram. no terminal, no MCP wiring describe your strategy in plain english → it runs 24/7 in your budget cap ◢ Polymarket CLOB, batch trades, one-tap confirm ◢ EV, Kelly sizing, basket arb, X sentiment via Grok ◢ tick memory, auto-pause on 3 failures, budget reservation built it for myself. now it's yours first 500 activations are FREE comment "agent" + RT + follow Sides.Trade – Polymarket AI Bot

arty.hl

16,968 次观看 • 3 个月前

THIS AGENT LEARNS FROM EVERY TASK. BUILDS ITS OWN SKILLS. REMEMBERS EVERYTHING 100K GitHub stars in 53 days. 160K+ now. 26K forks. 1,000+ contributors. what makes it different: > completes a task > writes a reusable skill from experience > gets faster next use > three-tier memory: remembers your projects, preferences, environment across every session > 200+ models via OpenRouter. Claude, GPT, Grok, Gemini, Ollama local one command > Telegram, Discord, WhatsApp, iMessage one gateway > built-in cron scheduler. sub-agents. MCP servers. web search. code execution > runs on a $5 VPS. 24/7. from your phone most AI agents: blank slate every session. Hermes: remembers everything. always

THIS AGENT LEARNS FROM EVERY TASK. BUILDS ITS OWN SKILLS. REMEMBERS EVERYTHING 100K GitHub stars in 53 days. 160K+ now. 26K forks. 1,000+ contributors. what makes it different: > completes a task > writes a reusable skill from experience > gets faster next use > three-tier memory: remembers your projects, preferences, environment across every session > 200+ models via OpenRouter. Claude, GPT, Grok, Gemini, Ollama local one command > Telegram, Discord, WhatsApp, iMessage one gateway > built-in cron scheduler. sub-agents. MCP servers. web search. code execution > runs on a $5 VPS. 24/7. from your phone most AI agents: blank slate every session. Hermes: remembers everything. always

NO1ennn

24,902 次观看 • 3 个月前

i merged all my AI agents into one brain Claude Code, Codex, Gemini: one team, one memory, zero re-briefing result: 8+ hours a week back, and every agent already knows my projects, my clients and how i think here's the setup with Jarvix: 1. dump your context once: projects, clients, writing style, how you make decisions.. it builds your personal model from your actual AI interactions 2. switch agents mid-task with zero re-briefing: Claude Code builds, Codex reviews, Gemini researches, all reading the same context 3. it carries what YOU choose across sessions.. never start a chat from zero again 4. when it's time to act, it pulls the right agents together as one team instead of five separate assistants the unlock isn't another agent. it's that your context finally travels agents without shared memory are five interns on their first day, forever. agents with it are a team that's worked with you for years not more agents. one shared context that's the right bet P.S. thanks to the Jarvix team for the early access

i merged all my AI agents into one brain Claude Code, Codex, Gemini: one team, one memory, zero re-briefing result: 8+ hours a week back, and every agent already knows my projects, my clients and how i think here's the setup with Jarvix: 1. dump your context once: projects, clients, writing style, how you make decisions.. it builds your personal model from your actual AI interactions 2. switch agents mid-task with zero re-briefing: Claude Code builds, Codex reviews, Gemini researches, all reading the same context 3. it carries what YOU choose across sessions.. never start a chat from zero again 4. when it's time to act, it pulls the right agents together as one team instead of five separate assistants the unlock isn't another agent. it's that your context finally travels agents without shared memory are five interns on their first day, forever. agents with it are a team that's worked with you for years not more agents. one shared context that's the right bet P.S. thanks to the Jarvix team for the early access

Ronin

15,071 次观看 • 18 天前

Introducing My.AGNT I built a one-click OpenClaw agent — and it's free. The goal of My.AGNT is to make sure everyone can participate in the agent economy. All you have to do is sign up with your email, and you get your own personalized agent on OpenClaw with prebuilt skills: → Soul → Identity → Wallet → Full Grok X Search → Full Internet Search → All AI Agent MegaETH Skills → 8004 Registration via AGNT Coming soon: → Polymarket Skills → Abstract Chain AI Agent Skills → So much more Your agent, without all the hassle.

Introducing My.AGNT I built a one-click OpenClaw agent — and it's free. The goal of My.AGNT is to make sure everyone can participate in the agent economy. All you have to do is sign up with your email, and you get your own personalized agent on OpenClaw with prebuilt skills: → Soul → Identity → Wallet → Full Grok X Search → Full Internet Search → All AI Agent MegaETH Skills → 8004 Registration via AGNT Coming soon: → Polymarket Skills → Abstract Chain AI Agent Skills → So much more Your agent, without all the hassle.

tut™

39,515 次观看 • 5 个月前

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 次观看 • 1 年前

I was tired of vibe coding having ZERO vibe : CNVS is live today. 100% voice controlled locally via parakeet, or through gpt realtime for conversational control like jarvis. you can create remote canvasses on your vps that keep shipping even after you close the macbook. you connect and chat with hermes straight from the canvas via local network or vps. its built in swift for native mac os performance. their is bidirectional agent and canvas control via mcp and cli. their is built in shared memory system without bloat. you can buy a lifetime license rn, zero sub required, fully byok. Supports every agent cli, claude code, codex, cursor, etc... made with love by a dad in his basement who is tired of vibe coding being slow, boring, and constrained.

I was tired of vibe coding having ZERO vibe : CNVS is live today. 100% voice controlled locally via parakeet, or through gpt realtime for conversational control like jarvis. you can create remote canvasses on your vps that keep shipping even after you close the macbook. you connect and chat with hermes straight from the canvas via local network or vps. its built in swift for native mac os performance. their is bidirectional agent and canvas control via mcp and cli. their is built in shared memory system without bloat. you can buy a lifetime license rn, zero sub required, fully byok. Supports every agent cli, claude code, codex, cursor, etc... made with love by a dad in his basement who is tired of vibe coding being slow, boring, and constrained.

Max Blade

14,592 次观看 • 2 个月前

I ran the same task on Claude Code and DeepSeek's new agent harness. One cost $150. The other cost $2. Today we're launching (AgentSky), the "OpenRouter for Agents" — one API → Claude Code, Codex, DeepSeek, Kimi, OpenCode, and every major agent in the cloud. And Agent Playground on top: race them on your own task, with your real tools (GitHub, Gmail, more), side by side in a browser: time, cost, tokens burnt. Guess which one was $2.

I ran the same task on Claude Code and DeepSeek's new agent harness. One cost $150. The other cost $2. Today we're launching (AgentSky), the "OpenRouter for Agents" — one API → Claude Code, Codex, DeepSeek, Kimi, OpenCode, and every major agent in the cloud. And Agent Playground on top: race them on your own task, with your real tools (GitHub, Gmail, more), side by side in a browser: time, cost, tokens burnt. Guess which one was $2.

Xiaoyin Qu

2,180,448 次观看 • 6 天前

🤯 YOUR AGENT NOW GETS ITS OWN COMPUTER - WITHOUT PAYING FOR GROK someone open-sourced the entire Grok Bot stack. Rakazo. 531 stars in 3 days on GitHub. -> install it - and your agent gets: - any LLM you pick (OpenRouter, ChatGPT, Copilot, or sign in with SuperGrok) - a live Linux desktop it can see, click, and type on - Docker, E2B, or your own Mac as the sandbox - web, desktop, and mobile - one product, your hardware - memory, routines, and history per bot - bots that spawn other bots, or subagents inside one turn - self-hosted. no Rakazo control plane required no vendor lock-in. no closed bot computer. important: still beta - you need Docker, Postgres, and your own model key. your agent has been renting someone else's sandbox this whole time. save this before the Grok team sees it ↓

🤯 YOUR AGENT NOW GETS ITS OWN COMPUTER - WITHOUT PAYING FOR GROK someone open-sourced the entire Grok Bot stack. Rakazo. 531 stars in 3 days on GitHub. -> install it - and your agent gets: - any LLM you pick (OpenRouter, ChatGPT, Copilot, or sign in with SuperGrok) - a live Linux desktop it can see, click, and type on - Docker, E2B, or your own Mac as the sandbox - web, desktop, and mobile - one product, your hardware - memory, routines, and history per bot - bots that spawn other bots, or subagents inside one turn - self-hosted. no Rakazo control plane required no vendor lock-in. no closed bot computer. important: still beta - you need Docker, Postgres, and your own model key. your agent has been renting someone else's sandbox this whole time. save this before the Grok team sees it ↓

Granite

40,696 次观看 • 14 天前

Everyone's handing AI agents access to their machine. Almost nobody's watching what those agents actually do with it. Perplexity just open-sourced the tool that fixes that. It's called Numbat. It sits on your computer and watches what your coding agent, Claude Code, Codex, and others, actually tries to do. When an agent reaches for something risky, like reading your SSH keys, opening your .env file, or grabbing browser cookies, Numbat flags it, and can block it before it happens. - Watches agent activity live, on your own device - Optionally blocks dangerous actions before they run - Reconstructs exactly what an agent did after the fact - Ships as a single binary for macOS, Linux, & Windows The problem it solves isn't hackers. It's an agent chasing a goal and doing something destructive on the way there. 100% Free. Open Source.

Everyone's handing AI agents access to their machine. Almost nobody's watching what those agents actually do with it. Perplexity just open-sourced the tool that fixes that. It's called Numbat. It sits on your computer and watches what your coding agent, Claude Code, Codex, and others, actually tries to do. When an agent reaches for something risky, like reading your SSH keys, opening your .env file, or grabbing browser cookies, Numbat flags it, and can block it before it happens. - Watches agent activity live, on your own device - Optionally blocks dangerous actions before they run - Reconstructs exactly what an agent did after the fact - Ships as a single binary for macOS, Linux, & Windows The problem it solves isn't hackers. It's an agent chasing a goal and doing something destructive on the way there. 100% Free. Open Source.

Simplifying AI

31,411 次观看 • 24 天前

If you use Cursor for coding, Claude Code for debugging, and local agents for automation, you almost certainly have a context problem. Every tool acts like an isolated employee. One assistant forgets what the other just learned. The biggest bottleneck in multi-agent workflows right now isn’t reasoning. It’s collective amnesia, combined with zero communication between agents. Memmy just launched a smart fix for this: a local, cross-agent memory layer. Instead of re-pasting your context everywhere, Memmy gives your stack a shared memory hub: → accumulate knowledge once, then use it across Cursor, Codex, and OpenClaw → automatically scan and import your existing agent history, so you don’t have to start from zero → keep your memory local, while model usage depends on your chosen provider or BYOK setup And it isn’t just a memory plugin. It’s a complete personal AI runtime with both MCP and a CLI. Memmy officially launched on Product Hunt, and the team is giving early users experiencing context fragmentation a free trial with 2M GPT tokens. Check it out and support the team with an upvote: → Best part? It’s also open-source for devs who want to build their own agents 🔥 Repo in 🧵↓

If you use Cursor for coding, Claude Code for debugging, and local agents for automation, you almost certainly have a context problem. Every tool acts like an isolated employee. One assistant forgets what the other just learned. The biggest bottleneck in multi-agent workflows right now isn’t reasoning. It’s collective amnesia, combined with zero communication between agents. Memmy just launched a smart fix for this: a local, cross-agent memory layer. Instead of re-pasting your context everywhere, Memmy gives your stack a shared memory hub: → accumulate knowledge once, then use it across Cursor, Codex, and OpenClaw → automatically scan and import your existing agent history, so you don’t have to start from zero → keep your memory local, while model usage depends on your chosen provider or BYOK setup And it isn’t just a memory plugin. It’s a complete personal AI runtime with both MCP and a CLI. Memmy officially launched on Product Hunt, and the team is giving early users experiencing context fragmentation a free trial with 2M GPT tokens. Check it out and support the team with an upvote: → Best part? It’s also open-source for devs who want to build their own agents 🔥 Repo in 🧵↓

Charly Wargnier

203,456 次观看 • 1 个月前