Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

What makes an agent your agent? Not just intelligence Identity. Memory. Context. Preferences That's what Persona is building into the OptimAI agentic stack. Because the future isn't thousands of identical agents It's agents that become uniquely yours. 💡

OptimaiNetwork's profile picture

OptimAI Network

97,316 subscribers

10,218 görüntüleme • 1 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

28 Yorum

Jesse Proctor profil fotoğrafı
Jesse Proctor1 ay önce

Can't wait to train an AI agent with my exact memory and preferences so it can run my parody accounts while I do absolutely nothing. The ultimate arbitrage is outsourcing your own personality.

Nnamezie Sunday profil fotoğrafı
Nnamezie Sunday1 ay önce

The real breakthrough is when agents stop feeling generic and start feeling personal. 🧠⚡ Identity, memory, context and preferences are what turn an AI agent into your agent. OptimAI is building toward a future where every agent can evolve uniquely around its user. 🚀

Daniel Costa profil fotoğrafı
Daniel Costa1 ay önce

come with me!

maryani profil fotoğrafı
maryani1 ay önce

keep building fam🙌🏼

BlockClaimed profil fotoğrafı
BlockClaimed1 ay önce

Context and memory make the difference....this is how agents become truly yours

Darman profil fotoğrafı
Darman1 ay önce

LFG

haossut profil fotoğrafı
haossut1 ay önce

finally an AI project that gets it. having an agent with actual memory and identity instead of just some generic copy is a game-changer. @OptimaiNetwork is building something real here. super bullish on this

Kristin Barry profil fotoğrafı
Kristin Barry1 ay önce

Can’t wait to get a personalized AI agent with my exact memory and context Just so it can ignore Slack messages and postpone meetings for me

Bích Ngọc profil fotoğrafı
Bích Ngọc1 ay önce

Nice

popi akhter profil fotoğrafı
popi akhter1 ay önce

🥰

Vanessa Miller profil fotoğrafı
Vanessa Miller1 ay önce

need an agent that actually remembers my context so i don't have to explain my life story every time i prompt it

Muhammad Afaan profil fotoğrafı
Muhammad Afaan1 ay önce

Lesting date

Lee✨ profil fotoğrafı
Lee✨1 ay önce

👀👀

Ms Masum Sarkar profil fotoğrafı
Ms Masum Sarkar1 ay önce

Nice

Hunny profil fotoğrafı
Hunny1 ay önce

Interesting

Văn Toán profil fotoğrafı
Văn Toán1 ay önce

Great

Bondan profil fotoğrafı
Bondan1 ay önce

Awesome🥳🥳

Joss 🤖ボッ profil fotoğrafı
Joss 🤖ボッ1 ay önce

⬛️⬛️⬛️⬛️⬛️⬛️⬛️⬛️ GM Crypto Fam' and #Airdrop Hunters 📱 Join @OptimaiNetwork and start earning passive Rewards ! My Referral Link : My Referral Code for @OptimaiNetwork : DA373F01 ⬛️⬛️⬛️⬛️⬛️⬛️⬛️⬛️

alice profil fotoğrafı
alice1 ay önce

Haven’t joined OptimAI yet? Don’t miss your chance to get in early!

Jeffery Davenport MD profil fotoğrafı
Jeffery Davenport MD1 ay önce

need my AI agent to actually have my vibe and not just sound like a generic chATGpt clone 😭 memory and context is everything

Jagad Satria profil fotoğrafı
Jagad Satria1 ay önce

Awesome🥳🥳🥳

Jennifer Davies profil fotoğrafı
Jennifer Davies1 ay önce

Most AI tools sound like a generic LinkedIn post. An agent with actual identity, memory, and your specific vibe? That’s how you build something people actually want to interact with. The future isn't copy-paste bots.

Heri Bendot profil fotoğrafı
Heri Bendot1 ay önce

Konsisten

April Brennan profil fotoğrafı
April Brennan1 ay önce

Can someone explain this in football terms?

Rusl profil fotoğrafı
Rusl1 ay önce

The real shift with AI is moving away from generic assistants to agents that actually understand your specific context and nuance. This is going to make building niche brands and characters so much more interesting.

coin68 profil fotoğrafı
coin681 ay önce

tuyệt vời

Eric Harris profil fotoğrafı
Eric Harris1 ay önce

If my agent doesn't have the risk appetite of a high-leverage degen buying the dip, is it even mine? Let's see if these personalized agents can handle the volatility without running scurred.

Januario profil fotoğrafı
Januario1 ay önce

Recompensador este projeto maravilhoso de vocês sucesso no lançamento @OptimaiNetwork

Benzer Videolar

OptimAI is building a full agentic stack. • OptimAI Search brings real-time decentralized discovery. • OptimAI Claw turns intent into execution on your device. • OptimAI Persona Agent enables domain-specific intelligence with custom knowledge. • Agentic Marketplace makes those agents usable, shareable, and composable. These layers work together: data → agents → execution → distribution. A system where intelligence doesn’t just respond, but operates. Building the agent-native internet. 💡
0:36

OptimAI is building a full agentic stack. • OptimAI Search brings real-time decentralized discovery. • OptimAI Claw turns intent into execution on your device. • OptimAI Persona Agent enables domain-specific intelligence with custom knowledge. • Agentic Marketplace makes those agents usable, shareable, and composable. These layers work together: data → agents → execution → distribution. A system where intelligence doesn’t just respond, but operates. Building the agent-native internet. 💡

OptimAI Network

16,497 görüntüleme • 5 ay önce

The real moat is not more prompts. It is more expertise. OptimAI is turning community knowledge into live persona agents - systems that can think with domain context, not guess with generic intelligence. That is how a network becomes infrastructure. 💡 --- 🔥 Explore what others are building. And start build your own agent. 💡 Quick tip: Start with one niche you know deeply. The best agents are built from real experience, not broad assumptions.
0:53

The real moat is not more prompts. It is more expertise. OptimAI is turning community knowledge into live persona agents - systems that can think with domain context, not guess with generic intelligence. That is how a network becomes infrastructure. 💡 --- 🔥 Explore what others are building. And start build your own agent. 💡 Quick tip: Start with one niche you know deeply. The best agents are built from real experience, not broad assumptions.

OptimAI Network

16,782 görüntüleme • 4 ay önce

The next wave of AI will not be one model doing everything. It will be specialized agents built around real domains, real knowledge, and real usage. That is what OptimAI is building with Search, Claw, Persona Agents, and Marketplace. Create an agent. Give it expertise. Publish it. Let it be used. That is how intelligence becomes infrastructure. 💡Build yours at:
1:46

The next wave of AI will not be one model doing everything. It will be specialized agents built around real domains, real knowledge, and real usage. That is what OptimAI is building with Search, Claw, Persona Agents, and Marketplace. Create an agent. Give it expertise. Publish it. Let it be used. That is how intelligence becomes infrastructure. 💡Build yours at:

OptimAI Network

24,312 görüntüleme • 5 ay önce

An agent without access to the world is operating in a bubble. OptimAI Search breaks that boundary. Live information becomes agent-readable context: enabling agents to research, discover and reason beyond their training data. And the building blocks are ready: MCP. SDK. Marketplace. 💡 The infrastructure is there. Now let's see what agents you build on top of it.
1:07

An agent without access to the world is operating in a bubble. OptimAI Search breaks that boundary. Live information becomes agent-readable context: enabling agents to research, discover and reason beyond their training data. And the building blocks are ready: MCP. SDK. Marketplace. 💡 The infrastructure is there. Now let's see what agents you build on top of it.

OptimAI Network

12,502 görüntüleme • 1 ay önce

One agent is a product. Millions of agents are infrastructure. As agents begin to research, create, trade, automate and operate continuously, they need somewhere to run. That's what we're building: Not infra for one agent. Infrastructure for an agentic economy. ⚡️
1:25

One agent is a product. Millions of agents are infrastructure. As agents begin to research, create, trade, automate and operate continuously, they need somewhere to run. That's what we're building: Not infra for one agent. Infrastructure for an agentic economy. ⚡️

OptimAI Network

10,288 görüntüleme • 1 ay önce

We’re not building features. We’re building an agent that understands context, learns intent, and acts autonomously. This is what agentic AI should feel like. Try OptimAI and help shape what’s next. 👉
0:24

We’re not building features. We’re building an agent that understands context, learns intent, and acts autonomously. This is what agentic AI should feel like. Try OptimAI and help shape what’s next. 👉

OptimAI

30,916 görüntüleme • 9 ay önce

Andrej Karpathy just broke the entire premise of modern AI: "The new computer isn't a chip - It's a language model running agent loops." Agents talking to agents -loops spawning sub-loops The stack being built RIGHT NOW: agent loop + memory + sub-agents + harness In a 20-minute talk, Karpathy explain the full reasoning stack
17:31

Andrej Karpathy just broke the entire premise of modern AI: "The new computer isn't a chip - It's a language model running agent loops." Agents talking to agents -loops spawning sub-loops The stack being built RIGHT NOW: agent loop + memory + sub-agents + harness In a 20-minute talk, Karpathy explain the full reasoning stack

Ricker

32,015 görüntüleme • 2 ay önce

Everyone wants agent swarms. Very few people are talking seriously enough about the context layer that makes swarms useful. Even with one agent, context is fragile. Too little context and the agent guesses. Too much context and it wastes tokens, loses focus, or reasons over irrelevant noise. The sweet spot is precise context: the right knowledge, in the right structure, at the right moment. With many agents, that challenge explodes. Each agent produces decisions, assumptions, findings, summaries, risks, and partial conclusions. Unless that knowledge becomes shared, structured, and reusable, every new agent is forced to rediscover what another agent already learned. That is not a swarm. That is a crowd. Shared context graphs are what turn agent activity into agent collaboration, and OriginTrail DKG V10 brings them to life. Was just playing with some final polishing for the V10 release, and it is really powerful to see shared context graphs where multiple agents contribute knowledge into the same connected memory, with attribution visible directly in the graph ui. That matters for three reasons. First, agents can access and build on one shared memory instead of staying trapped in isolated sessions. Second, the graph structure helps them retrieve the exact context they need, instead of stuffing everything into a prompt and hoping the model sorts it out. Third, verifiability of provenance. You can see which agent contributed each piece of knowledge, trace the source, and decide what to trust. Tokenmaxxing starts with fewer tokens, but the deeper story is coordination - agents stop reloading the world and start building on shared, verifiable context. That is the foundation for serious multi-agent work across software engineering, research, finance, operations, project management, and far beyond. The future is not more agents, it is agents working from shared, verifiable context. But the more the merrier, of course.
0:22

Everyone wants agent swarms. Very few people are talking seriously enough about the context layer that makes swarms useful. Even with one agent, context is fragile. Too little context and the agent guesses. Too much context and it wastes tokens, loses focus, or reasons over irrelevant noise. The sweet spot is precise context: the right knowledge, in the right structure, at the right moment. With many agents, that challenge explodes. Each agent produces decisions, assumptions, findings, summaries, risks, and partial conclusions. Unless that knowledge becomes shared, structured, and reusable, every new agent is forced to rediscover what another agent already learned. That is not a swarm. That is a crowd. Shared context graphs are what turn agent activity into agent collaboration, and OriginTrail DKG V10 brings them to life. Was just playing with some final polishing for the V10 release, and it is really powerful to see shared context graphs where multiple agents contribute knowledge into the same connected memory, with attribution visible directly in the graph ui. That matters for three reasons. First, agents can access and build on one shared memory instead of staying trapped in isolated sessions. Second, the graph structure helps them retrieve the exact context they need, instead of stuffing everything into a prompt and hoping the model sorts it out. Third, verifiability of provenance. You can see which agent contributed each piece of knowledge, trace the source, and decide what to trust. Tokenmaxxing starts with fewer tokens, but the deeper story is coordination - agents stop reloading the world and start building on shared, verifiable context. That is the foundation for serious multi-agent work across software engineering, research, finance, operations, project management, and far beyond. The future is not more agents, it is agents working from shared, verifiable context. But the more the merrier, of course.

Jurij Skornik

11,180 görüntüleme • 4 ay önce

AI agents don’t get better from intelligence alone. They get better from better data, better validation, better identity, and better privacy. That is why OptimAI is building a community-powered data network. OptimAI Core Node powers it: • collects real-time web and social signals • contributes compute and bandwidth • participates in validation and reinforcement The network turns this into structured, reliable context for agents. Not static training. Not blind trust. A system that improves with real usage. Building the agent-native internet. 👉
1:28

AI agents don’t get better from intelligence alone. They get better from better data, better validation, better identity, and better privacy. That is why OptimAI is building a community-powered data network. OptimAI Core Node powers it: • collects real-time web and social signals • contributes compute and bandwidth • participates in validation and reinforcement The network turns this into structured, reliable context for agents. Not static training. Not blind trust. A system that improves with real usage. Building the agent-native internet. 👉

OptimAI Network

14,716 görüntüleme • 5 ay önce

The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.
0:31

The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.

OptimAI Network

50,492 görüntüleme • 1 yıl önce

Agents are now your customers. Here are 9 startup ideas for that customer: - An agency that makes agents cite you. - A system that gives an agent an identity and permissions. - Receipts and audit trails for the work an agent does. - A generator that makes your documents ready for agents. - Security for the agent that reads your inbox. - A service that makes your pricing page readable to an agent. - MCP servers for franchises. - A support desk that agents call. - A sandbox where agents test your software. Pick one and build it.
4:07

Agents are now your customers. Here are 9 startup ideas for that customer: - An agency that makes agents cite you. - A system that gives an agent an identity and permissions. - Receipts and audit trails for the work an agent does. - A generator that makes your documents ready for agents. - Security for the agent that reads your inbox. - A service that makes your pricing page readable to an agent. - MCP servers for franchises. - A support desk that agents call. - A sandbox where agents test your software. Pick one and build it.

The Startup Ideas Podcast (SIP) 🧃

14,148 görüntüleme • 1 ay önce

Creator of Claude Code: “I’m not just prompting agents anymore. I’m building a harness with graphs and loops - and the agents inside it are building my agent. In 3–6 months, we’ll all be engineering harnesses for our agentic systems.” In this 10-minute talk, Boris Cherny reveals what the future of agentic engineering will look like. Worth more than a $500 agentic AI course. Watch it today, then read the complete guide to building an agent harness in the article below.
11:17

Creator of Claude Code: “I’m not just prompting agents anymore. I’m building a harness with graphs and loops - and the agents inside it are building my agent. In 3–6 months, we’ll all be engineering harnesses for our agentic systems.” In this 10-minute talk, Boris Cherny reveals what the future of agentic engineering will look like. Worth more than a $500 agentic AI course. Watch it today, then read the complete guide to building an agent harness in the article below.

Ichigo

72,810 görüntüleme • 21 gün önce

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣
0:24

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

rody

18,089 görüntüleme • 15 gün önce

SpaceXAI engineer Lauren (poteto) on why your codebase is a form of memory for agents. The architecture you choose and the constraints your tech stack imposes shape how well an agent reasons about the code, so good structure makes your agents smarter by default.
0:24

SpaceXAI engineer Lauren (poteto) on why your codebase is a form of memory for agents. The architecture you choose and the constraints your tech stack imposes shape how well an agent reasons about the code, so good structure makes your agents smarter by default.

tetsuo

25,747 görüntüleme • 1 ay önce

Your agent has a request. Open models are ready. OptimAI Router connects the dots.🟢 One API. Multiple open models. A network of independent computers. We're building a new way for AI agents to access intelligence, with OptimAI Core Node bringing community-powered compute into the picture. One connection for builders. A network of possibilities behind it. The agentic internet needs infrastructure. We're building it. OptimAI Router is coming.⚡️
0:57

Your agent has a request. Open models are ready. OptimAI Router connects the dots.🟢 One API. Multiple open models. A network of independent computers. We're building a new way for AI agents to access intelligence, with OptimAI Core Node bringing community-powered compute into the picture. One connection for builders. A network of possibilities behind it. The agentic internet needs infrastructure. We're building it. OptimAI Router is coming.⚡️

OptimAI Network

14,970 görüntüleme • 2 gün önce

One click away, and a new world starts to unfold.💫 What looks like a small extension is actually the starting point for a personal AI agent that can search, think, and act with you. That is what we are building at OptimAI: live context, autonomous execution, and agents that feel native to the way people actually work. Not a demo. Not a gimmick. A new interface for the agent-native internet. Build your own personal AI agent:
0:23

One click away, and a new world starts to unfold.💫 What looks like a small extension is actually the starting point for a personal AI agent that can search, think, and act with you. That is what we are building at OptimAI: live context, autonomous execution, and agents that feel native to the way people actually work. Not a demo. Not a gimmick. A new interface for the agent-native internet. Build your own personal AI agent:

OptimAI Network

20,860 görüntüleme • 5 ay önce

Google just showed the part of the agent stack most people are still underestimating. Not the model. Not the chat UI. The memory substrate around the agent. In this Antigravity segment, Google describes an agent-first environment built around: - agent conversations - agent-produced artifacts - multi-agent orchestration - subagents - hooks - asynchronous task management That is not a nicer IDE. It is what happens when software stops being a sequence of chats and starts becoming a persistent workforce. Karl's article explains why the winning agents will not just be the ones with the smartest rented model. They will be the ones that remember what they did, what they learned, what changed, and what can be trusted. Full breakdown below.
1:25

Google just showed the part of the agent stack most people are still underestimating. Not the model. Not the chat UI. The memory substrate around the agent. In this Antigravity segment, Google describes an agent-first environment built around: - agent conversations - agent-produced artifacts - multi-agent orchestration - subagents - hooks - asynchronous task management That is not a nicer IDE. It is what happens when software stops being a sequence of chats and starts becoming a persistent workforce. Karl's article explains why the winning agents will not just be the ones with the smartest rented model. They will be the ones that remember what they did, what they learned, what changed, and what can be trusted. Full breakdown below.

Karl Mehta

13,930 görüntüleme • 3 ay önce

In an agentic world, identity = infrastructure. As humans, agents, and micro-agents start coordinating everything, you need a stable way to name and trust them and .agent is that shared identity layer. It’s designed to start on-chain and extend into DNS. Get your .agent identity set up before the good ones run out 👇
1:27

In an agentic world, identity = infrastructure. As humans, agents, and micro-agents start coordinating everything, you need a stable way to name and trust them and .agent is that shared identity layer. It’s designed to start on-chain and extend into DNS. Get your .agent identity set up before the good ones run out 👇

Sentient

58,759 görüntüleme • 9 ay önce

NVIDIA AI director Ali Golshan reveals how 3 agents can route around a policy that no single agent is allowed to break by splitting the forbidden task between them: "If you write a policy that says, 'My agent should not have access to GitHub and to Facebook at the same time, because I'm worried it's gonna go copy my code and paste it on some message board,' that's very acceptable." "The problem we started to see is it's not the behavior of one agent that's the complex part, it's fleets of agents working together that creates complexity." "An agent spawns two sub-agents, with one sub-agent that can only read from GitHub, but the ability to tunnel through the network, talk to an agent that can write to a post. Now you have three agents that combined exceed your global policies." "The agents don't really process the intent or goodwill of your policy. They just see it as very specific binary." NVIDIA
1:42

NVIDIA AI director Ali Golshan reveals how 3 agents can route around a policy that no single agent is allowed to break by splitting the forbidden task between them: "If you write a policy that says, 'My agent should not have access to GitHub and to Facebook at the same time, because I'm worried it's gonna go copy my code and paste it on some message board,' that's very acceptable." "The problem we started to see is it's not the behavior of one agent that's the complex part, it's fleets of agents working together that creates complexity." "An agent spawns two sub-agents, with one sub-agent that can only read from GitHub, but the ability to tunnel through the network, talk to an agent that can write to a post. Now you have three agents that combined exceed your global policies." "The agents don't really process the intent or goodwill of your policy. They just see it as very specific binary." NVIDIA

MTS

11,721 görüntüleme • 15 gün önce