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the perfect AI agent should remember everything. Sam Altman said it: "every conversation. every book. every email. your whole life appending to one context window." memory isn't a feature. it's the definition. I just built the memory layer. open source. install in one command. read the guide tonight. install... show more

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Sam Altman says no human assistant can remember every word or every small preference AI will, including the tiny patterns you didn't even think to mention Memory is still crude today, but when it remembers your whole life and personalizes everything, that's when it gets powerful

Sam Altman says no human assistant can remember every word or every small preference AI will, including the tiny patterns you didn't even think to mention Memory is still crude today, but when it remembers your whole life and personalizes everything, that's when it gets powerful

Haider.

54,303 просмотров • 8 месяцев назад

most agent memory is one file that grows forever and gets re-read every single turn. it overflows the context, overwrites old facts, loses the thread. that's why your agent feels sharp on day one and lost by week three. Sibyl Memory replaces the pile with a structure: → leaner context, lower token cost. a bloated agent file and flat memory get re-read in full every message. Sibyl Memory keeps a light hot layer and retrieves the rest on demand, so each turn carries only the tokens that matter. → relations are first-class. people link to projects, projects to deals, deals to the decisions behind them. ask about one partner and the agent surfaces the whole connected web around them. that relational context is what lets it help run a company. → one source of truth per fact, person, and project. no duplicates, no silent overwrites. works with hermes, claude code, and codex. beta open.

most agent memory is one file that grows forever and gets re-read every single turn. it overflows the context, overwrites old facts, loses the thread. that's why your agent feels sharp on day one and lost by week three. Sibyl Memory replaces the pile with a structure: → leaner context, lower token cost. a bloated agent file and flat memory get re-read in full every message. Sibyl Memory keeps a light hot layer and retrieves the rest on demand, so each turn carries only the tokens that matter. → relations are first-class. people link to projects, projects to deals, deals to the decisions behind them. ask about one partner and the agent surfaces the whole connected web around them. that relational context is what lets it help run a company. → one source of truth per fact, person, and project. no duplicates, no silent overwrites. works with hermes, claude code, and codex. beta open.

SIBYL

83,401 просмотров • 2 месяцев назад

An agent's identity shifts with every context. Every prompt. Every data source. So who's actually accountable for what it does? The answer isn't in the agent. It's in the human behind it. Like a surname that carries the weight of everything done under it.

An agent's identity shifts with every context. Every prompt. Every data source. So who's actually accountable for what it does? The answer isn't in the agent. It's in the human behind it. Like a surname that carries the weight of everything done under it.

Billions Network

38,305 просмотров • 5 месяцев назад

Martin Keen from IBM just explained the one thing separating "chatbot users" from $300K AI architects > most people use Claude Opus 4.8 as a temporary tool -> the pros build it a permanent memory it's called the CoALA framework. the 4 layers your agent actually needs: > Working Memory - the context window. fast but resets every session. this is the RAM, not the brain > Semantic Memory - your knowledge base. CLAUDE.md, rules, facts the agent never forgets regardless of session > Procedural Memory - skills. workflows and instructions that load only when a specific task begins > Episodic Memory - past lessons. the agent remembers every bug it fixed yesterday so it doesn't repeat it today if your agent doesn't have all four, it's a fancy autocomplete the 2026 job market isn't looking for prompt engineers > it's looking for people who can build AI brains - and the ones doing it now aren't waiting for job postings save this or watch someone else use it to get your next raise 👇

Martin Keen from IBM just explained the one thing separating "chatbot users" from $300K AI architects > most people use Claude Opus 4.8 as a temporary tool -> the pros build it a permanent memory it's called the CoALA framework. the 4 layers your agent actually needs: > Working Memory - the context window. fast but resets every session. this is the RAM, not the brain > Semantic Memory - your knowledge base. CLAUDE.md, rules, facts the agent never forgets regardless of session > Procedural Memory - skills. workflows and instructions that load only when a specific task begins > Episodic Memory - past lessons. the agent remembers every bug it fixed yesterday so it doesn't repeat it today if your agent doesn't have all four, it's a fancy autocomplete the 2026 job market isn't looking for prompt engineers > it's looking for people who can build AI brains - and the ones doing it now aren't waiting for job postings save this or watch someone else use it to get your next raise 👇

Mr. Buzzoni

10,435 просмотров • 2 месяцев назад

Introducing mem0 CLI 🚀 Give your agents memory from the terminal - add, search, and retrieve memory - remember agents + developers's preference - agent-first, JSON schema-driven We built mem0 CLI to help agents remember Get started npm install -g @mem0/cli Open source 👇

Introducing mem0 CLI 🚀 Give your agents memory from the terminal - add, search, and retrieve memory - remember agents + developers's preference - agent-first, JSON schema-driven We built mem0 CLI to help agents remember Get started npm install -g @mem0/cli Open source 👇

Taranjeet

20,567 просмотров • 4 месяцев назад

📁 Sam Altman says the real AI breakthrough will not be better reasoning, but total memory. An AI will be able to remember every conversation, email, and document across a person’s lifetime, identifying patterns and preferences humans never consciously express. Once memory becomes persistent, the idea of a personal assistant will fundamentally change.

📁 Sam Altman says the real AI breakthrough will not be better reasoning, but total memory. An AI will be able to remember every conversation, email, and document across a person’s lifetime, identifying patterns and preferences humans never consciously express. Once memory becomes persistent, the idea of a personal assistant will fundamentally change.

Jon Hernandez

4,271,270 просмотров • 8 месяцев назад

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

Dami-Defi

11,668 просмотров • 2 месяцев назад

V10 Decentralized Knowledge Graph is live! A shared memory for AI — open to every human and every agent. Open source. Yours to own. Every fact provable and traceable. The grid is awake. 1/3

V10 Decentralized Knowledge Graph is live! A shared memory for AI — open to every human and every agent. Open source. Yours to own. Every fact provable and traceable. The grid is awake. 1/3

OriginTrail

1,350,130 просмотров • 2 месяцев назад

Introducing Memory 101 🧠 Every ai tool you use is a goldfish. brilliant for one chat, close the tab and it forgets you completely. memory is the most underbuilt layer in ai right now. so we're explaining how it actually works, one episode at a time. coming up: → rag vs memory, why most "ai memory" is just search → the 5 things real memory needs: facts, profiles, graphs, time, forgetting → why good memory has to forget things follow along!

Introducing Memory 101 🧠 Every ai tool you use is a goldfish. brilliant for one chat, close the tab and it forgets you completely. memory is the most underbuilt layer in ai right now. so we're explaining how it actually works, one episode at a time. coming up: → rag vs memory, why most "ai memory" is just search → the 5 things real memory needs: facts, profiles, graphs, time, forgetting → why good memory has to forget things follow along!

supermemory

17,235 просмотров • 2 месяцев назад

We learned how to fly a plane to tell SF one thing. Introducing the Vendo (YC S26) Full-Stack Agentic Interface. A production-ready agent for your users with everything they need. It takes real actions for your users. And it can even build whole new features, micro-apps, and automations, right on top of your product. Built-in permissioning, tool guards, user context, and more. Everything you need for a user-facing agent. One command to install. Open source. Vendo (YC S26) Nour Zahzah

We learned how to fly a plane to tell SF one thing. Introducing the Vendo (YC S26) Full-Stack Agentic Interface. A production-ready agent for your users with everything they need. It takes real actions for your users. And it can even build whole new features, micro-apps, and automations, right on top of your product. Built-in permissioning, tool guards, user context, and more. Everything you need for a user-facing agent. One command to install. Open source. Vendo (YC S26) Nour Zahzah

Yousef

32,734 просмотров • 11 дней назад

just shipped thred!! context that carries your work forward. Claude → Codex → Cursor → whatever comes next. thred gives every agent one shared memory for decisions, revisions, evidence, and unfinished work — so the next agent starts where the last one stopped. built on MCP. powered by temporal memory with HydraDB. no more re-explaining the codebase. no more lost decisions between sessions. just save → switch → resume. built for Hack Hydra | Memory + Context Retrieval.

just shipped thred!! context that carries your work forward. Claude → Codex → Cursor → whatever comes next. thred gives every agent one shared memory for decisions, revisions, evidence, and unfinished work — so the next agent starts where the last one stopped. built on MCP. powered by temporal memory with HydraDB. no more re-explaining the codebase. no more lost decisions between sessions. just save → switch → resume. built for Hack Hydra | Memory + Context Retrieval.

nikhil · sys/quests

15,716 просмотров • 7 дней назад

Every AI agent I've used has the same bug: It forgets everything. Not after a month. Sometimes after a single session. This week I tested Memanto, an open-source memory companion for AI agents, and it completely changed how I think about agent workflows. 👇 Moorcheh.ai #ad

Every AI agent I've used has the same bug: It forgets everything. Not after a month. Sometimes after a single session. This week I tested Memanto, an open-source memory companion for AI agents, and it completely changed how I think about agent workflows. 👇 Moorcheh.ai #ad

Kaitee

37,566 просмотров • 2 месяцев назад

The reason your AI keeps forgetting isn't the context window. It's that the context lives somewhere the model never sees: your team's actual conversation. So you become the integration layer. Read the channel, compress it, paste it in, every session. That's not a prompting problem. It's an architecture problem. Helio 's answer is unsexy put the teammate inside the channel. Same threads, same files, same history as everyone else. The compression step disappears because there's nothing left to compress. Still gated: -> It stops and asks before anything consequential. -> In a shared channel that's the correct default, not a missing feature.

The reason your AI keeps forgetting isn't the context window. It's that the context lives somewhere the model never sees: your team's actual conversation. So you become the integration layer. Read the channel, compress it, paste it in, every session. That's not a prompting problem. It's an architecture problem. Helio 's answer is unsexy put the teammate inside the channel. Same threads, same files, same history as everyone else. The compression step disappears because there's nothing left to compress. Still gated: -> It stops and asks before anything consequential. -> In a shared channel that's the correct default, not a missing feature.

ronix ⎋

28,904 просмотров • 22 дней назад

HERMES AGENT IS THE MOST POWERFUL OPEN SOURCE AI AGENT FRAMEWORK AVAILABLE RIGHT NOW — AND MOST PEOPLE HAVE NO IDEA HOW TO USE IT PROPERLY. This masterclass fixes that completely. From zero to a fully operational autonomous agent system in one sitting. Installation. Skills. Memory. MCP servers. Scheduler. Multi-agent operations. Every section builds on the previous one. The people who read this this weekend will have a production-ready autonomous agent operation running by Monday. Read this and bookmark it now.

HERMES AGENT IS THE MOST POWERFUL OPEN SOURCE AI AGENT FRAMEWORK AVAILABLE RIGHT NOW — AND MOST PEOPLE HAVE NO IDEA HOW TO USE IT PROPERLY. This masterclass fixes that completely. From zero to a fully operational autonomous agent system in one sitting. Installation. Skills. Memory. MCP servers. Scheduler. Multi-agent operations. Every section builds on the previous one. The people who read this this weekend will have a production-ready autonomous agent operation running by Monday. Read this and bookmark it now.

CyrilXBT

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SmartX is an AI trading terminal. Ask it about a market, it comes back with the evidence. Ask it about yourself, it reads your whole book back to you. Which categories you actually do well in. How early you enter. How you size. Every venue on one screen. Every decision becomes memory.

SmartX is an AI trading terminal. Ask it about a market, it comes back with the evidence. Ask it about yourself, it reads your whole book back to you. Which categories you actually do well in. How early you enter. How you size. Every venue on one screen. Every decision becomes memory.

SmartX

53,758 просмотров • 11 дней назад

🚨 SOMEONE JUST KILLED THE COACHING INDUSTRY a developer spent 22,000 hours building a Personal AI Operating System on top of Claude Code now anyone with a terminal can install it for FREE it knows your goals, remembers every decision you've made, and prepares your morning briefing while you sleep [ the numbers are insane ]: - hours of dev work in it: 22,000 - sessions logged: 6,000 - time saved per day: 2-3 hours - GitHub stars: 12,100 - skills built in: 45 - workflows wired up: 171 - safety hooks: 37 - cost to install: $0 [ the science is wild too ]: no embeddings, no vector databases, no AI magic you can't read every memory, decision, and context lives in plain markdown files you read it with cat, search it with ripgrep, version it with git 4 memory types compound over time: - work memory (active projects, open decisions) - knowledge memory (domain expertise, research) - people memory (contacts, companies, relationships) - learning memory (patterns, mistakes, what works for YOU) every complex task routes through a 7-step cycle: OBSERVE → THINK → PLAN → BUILD → EXECUTE → VERIFY → LEARN privacy is enforced by CODE, not prompts a hook called ContainmentGuard physically blocks sensitive data from being written outside designated zones [ the grift opportunity is even wilder ]: freelancers are already charging $500-2,000 per personal AI setup for executives, founders, and busy operators one person + one weekend = a consulting business that didn't exist 6 months ago every AI productivity app you're paying $30/month for is replaceable by 4 hours of setup work and this one repo REPO: 100% OPEN SOURCE, FREE

🚨 SOMEONE JUST KILLED THE COACHING INDUSTRY a developer spent 22,000 hours building a Personal AI Operating System on top of Claude Code now anyone with a terminal can install it for FREE it knows your goals, remembers every decision you've made, and prepares your morning briefing while you sleep [ the numbers are insane ]: - hours of dev work in it: 22,000 - sessions logged: 6,000 - time saved per day: 2-3 hours - GitHub stars: 12,100 - skills built in: 45 - workflows wired up: 171 - safety hooks: 37 - cost to install: $0 [ the science is wild too ]: no embeddings, no vector databases, no AI magic you can't read every memory, decision, and context lives in plain markdown files you read it with cat, search it with ripgrep, version it with git 4 memory types compound over time: - work memory (active projects, open decisions) - knowledge memory (domain expertise, research) - people memory (contacts, companies, relationships) - learning memory (patterns, mistakes, what works for YOU) every complex task routes through a 7-step cycle: OBSERVE → THINK → PLAN → BUILD → EXECUTE → VERIFY → LEARN privacy is enforced by CODE, not prompts a hook called ContainmentGuard physically blocks sensitive data from being written outside designated zones [ the grift opportunity is even wilder ]: freelancers are already charging $500-2,000 per personal AI setup for executives, founders, and busy operators one person + one weekend = a consulting business that didn't exist 6 months ago every AI productivity app you're paying $30/month for is replaceable by 4 hours of setup work and this one repo REPO: 100% OPEN SOURCE, FREE

Ronin

614,821 просмотров • 3 месяцев назад

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

Madni Aghadi

396,893 просмотров • 1 месяц назад

Here's 4 minutes of the most UNDERRATED play in football. It's one of the easiest plays to execute and it gets the ball to one of your best players in space. It's the first play I install every season. Bookmark these to study for fall camp.

Here's 4 minutes of the most UNDERRATED play in football. It's one of the easiest plays to execute and it gets the ball to one of your best players in space. It's the first play I install every season. Bookmark these to study for fall camp.

Thad Wells

115,123 просмотров • 3 месяцев назад

1/ Context Lens, new in Tlon v9.2.0. Everything your agent has ever done, stored durably on your personal server. Every message, every tool call. Debugging an agent usually means ssh-ing into a server and grepping logs. Now it's a tap in Tlon Messenger's UI. Tap the badge under a bot's reply to open the run: the context it read, each tool call with timing, the model that answered, and a persistence log of everything it wrote.

1/ Context Lens, new in Tlon v9.2.0. Everything your agent has ever done, stored durably on your personal server. Every message, every tool call. Debugging an agent usually means ssh-ing into a server and grepping logs. Now it's a tap in Tlon Messenger's UI. Tap the badge under a bot's reply to open the run: the context it read, each tool call with timing, the model that answered, and a persistence log of everything it wrote.

Tlon

10,650 просмотров • 1 месяц назад

AI can write a 10,000-word essay in seconds… but forgets you just told it your name yesterday. Engramme is trying to fix that. Memory that sticks. Context that follows you. Across every app. This might be the missing layer AI needed.

AI can write a 10,000-word essay in seconds… but forgets you just told it your name yesterday. Engramme is trying to fix that. Memory that sticks. Context that follows you. Across every app. This might be the missing layer AI needed.

Sripathi Teja

27,799 просмотров • 4 месяцев назад