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🚀 Zed v1.14 is out! Zed's Agent now sandboxes its `terminal` and `fetch` tools by default. The sandbox prevents agents from writing outside project directories, modifying `.git`, or accessing the network unless you grant permission.

Zed

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39,191 görüntüleme • 23 gün önce •via X (Twitter)

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$🚀 Zed v0.178 is out! Zed will now auto-close tags in JSX/TSX files by default, as well as Astro, Svelte, and Vue files, if the associated extensions are installed. To disable this behavior, use: `"jsx_tag_auto_close": { "enabled": false }`$

🚀 Zed v0.178 is out! Zed will now auto-close tags in JSX/TSX files by default, as well as Astro, Svelte, and Vue files, if the associated extensions are installed. To disable this behavior, use: `"jsx_tag_auto_close": { "enabled": false }`

Zed

43,323 görüntüleme • 1 yıl önce

Introducing Agent Sandbox, the infinite simulation playground for agents on Virtuals. Craft the perfect autonomous agent in our Sandbox with full control over its personality and goals. Enhance your agent with unique abilities by creating custom functions so they can trade onchain, generate memes, control physical robots and more. The Sandbox is available to all builders with graduated agents in the Developer Panel. For those who want to give it a spin without an existing agent, fret not. Try it out today at and join our Discord ( to jam with like-minded builders. Next stop, Society of Agents.

Introducing Agent Sandbox, the infinite simulation playground for agents on Virtuals. Craft the perfect autonomous agent in our Sandbox with full control over its personality and goals. Enhance your agent with unique abilities by creating custom functions so they can trade onchain, generate memes, control physical robots and more. The Sandbox is available to all builders with graduated agents in the Developer Panel. For those who want to give it a spin without an existing agent, fret not. Try it out today at and join our Discord ( to jam with like-minded builders. Next stop, Society of Agents.

Virtuals Protocol

188,627 görüntüleme • 1 yıl önce

$this might be the E2B killer for AI agent sandboxes. forkd is an open-source microVM sandbox runtime built on Firecracker, made for AI agent fan-out, code interpreters, eval harnesses, anything that spins up a lot of short-lived sandboxes. before: every sandbox cold-boots its own VM and re-imports the whole runtime from scratch, numpy, torch, JIT compilation, model weights, all of it. now: forkd boots one parent VM once, warms it with your runtime already imported, then forks children from that snapshot using copy-on-write memory. the repo's own benchmark: spawning 100 sandboxes takes 101ms with forkd, versus 759ms for a raw Firecracker cold-boot, and well over a minute for Docker or gVisor. the SDK is a literal drop-in for E2B's Python client, so if you're already running code-interpreter agents on it, swapping the import line gets you a self-hosted runtime with the same isolation model at a fraction of the per-sandbox cost. pre-built recipes ship for e2b-style code interpreters, Jupyter kernels, SWE-bench coding agents, and Playwright browser fan-out$

this might be the E2B killer for AI agent sandboxes. forkd is an open-source microVM sandbox runtime built on Firecracker, made for AI agent fan-out, code interpreters, eval harnesses, anything that spins up a lot of short-lived sandboxes. before: every sandbox cold-boots its own VM and re-imports the whole runtime from scratch, numpy, torch, JIT compilation, model weights, all of it. now: forkd boots one parent VM once, warms it with your runtime already imported, then forks children from that snapshot using copy-on-write memory. the repo's own benchmark: spawning 100 sandboxes takes 101ms with forkd, versus 759ms for a raw Firecracker cold-boot, and well over a minute for Docker or gVisor. the SDK is a literal drop-in for E2B's Python client, so if you're already running code-interpreter agents on it, swapping the import line gets you a self-hosted runtime with the same isolation model at a fraction of the per-sandbox cost. pre-built recipes ship for e2b-style code interpreters, Jupyter kernels, SWE-bench coding agents, and Playwright browser fan-out

Oliver Prompts

20,005 görüntüleme • 15 gün önce

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

BuBBliK

200,402 görüntüleme • 2 ay önce

Agents are the future of AI creative tools. And the new Grok Imagine Agent is a great one! It feels like a smart partner that you can brainstorm and iterate with - it does the heavy lifting of writing prompts + building out the canvas. Watch me build a froyo brand 👇

Justine Moore

31,403 görüntüleme • 4 ay önce

Devin for Terminal is the first CLI agent with its own dedicated virtual machine. You can start a project locally and hand it off to Devin to test it end-to-end. Devin for Terminal is super performant, and it works with all frontier models. Try it out today.

Devin for Terminal is the first CLI agent with its own dedicated virtual machine. You can start a project locally and hand it off to Devin to test it end-to-end. Devin for Terminal is super performant, and it works with all frontier models. Try it out today.

Cognition

3,744,423 görüntüleme • 4 ay önce

Devin for Terminal is the first CLI agent with its own dedicated virtual machine. You can start a project locally and hand it off to Devin to test it end-to-end. Devin for Terminal is super performant, and it works with all frontier models. Try it out today.

Devin for Terminal is the first CLI agent with its own dedicated virtual machine. You can start a project locally and hand it off to Devin to test it end-to-end. Devin for Terminal is super performant, and it works with all frontier models. Try it out today.

Cognition

20,207,666 görüntüleme • 4 ay önce

we just released a new blog "Training a coding agent using the OpenCode harness in remote HF sandboxes with TRL and OpenEnv" you can take a real coding agent (OpenCode), let it run its own tool loop against real coding problems, and train it with RL on the exact tokens it produced and every rollout runs in its own remote HF sandbox, so rollouts scale out beyond one machine the loop: - OpenCode owns its tool loop inside an OpenEnv sandbox - an in-sandbox proxy records the real token ids + logprobs, per turn - a hidden-test verifier scores the result, and that is the reward - TRL trains with AsyncGRPO, weights sync back to vLLM over NCCL blog + runnable example:

we just released a new blog "Training a coding agent using the OpenCode harness in remote HF sandboxes with TRL and OpenEnv" you can take a real coding agent (OpenCode), let it run its own tool loop against real coding problems, and train it with RL on the exact tokens it produced and every rollout runs in its own remote HF sandbox, so rollouts scale out beyond one machine the loop: - OpenCode owns its tool loop inside an OpenEnv sandbox - an in-sandbox proxy records the real token ids + logprobs, per turn - a hidden-test verifier scores the result, and that is the reward - TRL trains with AsyncGRPO, weights sync back to vLLM over NCCL blog + runnable example:

Sergio Paniego

36,159 görüntüleme • 23 gün önce

Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.

Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.

Varun

142,992 görüntüleme • 5 ay önce

Here is an engaging short video that simply explains how the AiTraceRoot project works. It eliminates the need for manual analysis and filtering of massive Web3 datasets and prevents you from being misled by false information or red herrings. AiTraceRoot handles this process for you, presenting the most authentic and valuable data so you can make the right choices with confidence.

Here is an engaging short video that simply explains how the AiTraceRoot project works. It eliminates the need for manual analysis and filtering of massive Web3 datasets and prevents you from being misled by false information or red herrings. AiTraceRoot handles this process for you, presenting the most authentic and valuable data so you can make the right choices with confidence.

AiTraceRoot_Ai

36,123 görüntüleme • 1 ay önce

YOU CAN NOW CONTROL ALL YOUR HERMES AGENTS FROM ONE INTERFACE. 🚨 Someone just built Hermes Workspace - the most complete GUI for Hermes Agent. Instead of jumping between tools, everything lives in one place. What's inside: > Chat, terminal, memory browser, and skills manager > Run unlimited agents with 1 orchestrator > Kanban board to track everything your agents are doing > 2,000+ skills to install without leaving the workspace > Works with any LLM provider Stop managing agents manually and start running them like a pro 👀 100% Free. Open Source.

YOU CAN NOW CONTROL ALL YOUR HERMES AGENTS FROM ONE INTERFACE. 🚨 Someone just built Hermes Workspace - the most complete GUI for Hermes Agent. Instead of jumping between tools, everything lives in one place. What's inside: > Chat, terminal, memory browser, and skills manager > Run unlimited agents with 1 orchestrator > Kanban board to track everything your agents are doing > 2,000+ skills to install without leaving the workspace > Works with any LLM provider Stop managing agents manually and start running them like a pro 👀 100% Free. Open Source.

Oliver Prompts

19,409 görüntüleme • 1 ay önce

Fundamentals Live for Agent Liquidity Engine (ALE) Now everyone can directly see the top agents leading in cumulative revenue, and exactly how much they have executed in all-time buybacks, through the Fundamentals board on the Virtuals landing page (Fundamentals currently only applicable to agents in ALE). Virtuals is built to support agents that solve real problems and sustain their own economies. The Agent Liquidity Engine exists to surface and scale those teams by: •Showcasing product strength that demonstrates clear utility •Tracking sustainable revenue that proves product–market fit •Highlighting agents that reinvest to reinforce their ecosystems By routing revenue back to scale the product and publishing these metrics, ALE turns long-term economic strength into an on-chain, verifiable signal. If your agent delivers real usage and sustainable revenue and you want to join ALE, please apply here: Our team will review and contact you if your project qualifies. ALE is where the agent economy separates hype from sustainability.

Fundamentals Live for Agent Liquidity Engine (ALE) Now everyone can directly see the top agents leading in cumulative revenue, and exactly how much they have executed in all-time buybacks, through the Fundamentals board on the Virtuals landing page (Fundamentals currently only applicable to agents in ALE). Virtuals is built to support agents that solve real problems and sustain their own economies. The Agent Liquidity Engine exists to surface and scale those teams by: •Showcasing product strength that demonstrates clear utility •Tracking sustainable revenue that proves product–market fit •Highlighting agents that reinvest to reinforce their ecosystems By routing revenue back to scale the product and publishing these metrics, ALE turns long-term economic strength into an on-chain, verifiable signal. If your agent delivers real usage and sustainable revenue and you want to join ALE, please apply here: Our team will review and contact you if your project qualifies. ALE is where the agent economy separates hype from sustainability.

Virtuals Protocol

50,621 görüntüleme • 11 ay önce

We’d like to share some updates from within the Forge. While minor updates may roll out at a slightly slower pace, our primary focus is dedicated to an exciting upcoming feature: Machina Foundry. What is Machina Foundry? Machina Foundry is an AI Agent Builder Platform that allows users to define an agent's purpose, functions, and objectives through simple, natural language prompts. Once an agent is created, Alchemists can seed liquidity in $ALCH for their agent. Liquidity is placed in Meteora pools, with 50% allocated to the ALCH ecosystem and the remaining 50% locked permanently. This structure ensures the ecosystem benefits from pool fees, enabling periodic ALCH token buybacks and supporting long-term growth. Additionally, the Foundry introduces a flywheel effect: purchasing an agent requires acquiring ALCH tokens, further integrating the ecosystem with the token economy. Agents built in Machina Foundry are fully customizable and reflect unique personalities. They can create apps and tools tailored to their character, powered by Alchemist AI’s robust technology. While similar to Azarus, these agents bring an added layer of individuality, ensuring that their creations vary significantly based on their distinct traits and configurations. Imagine a network of thousands of AI agents, each contributing diverse applications and tools, driving creativity and value across the ecosystem. Now that’s Magic!🪄✨

We’d like to share some updates from within the Forge. While minor updates may roll out at a slightly slower pace, our primary focus is dedicated to an exciting upcoming feature: Machina Foundry. What is Machina Foundry? Machina Foundry is an AI Agent Builder Platform that allows users to define an agent's purpose, functions, and objectives through simple, natural language prompts. Once an agent is created, Alchemists can seed liquidity in $ALCH for their agent. Liquidity is placed in Meteora pools, with 50% allocated to the ALCH ecosystem and the remaining 50% locked permanently. This structure ensures the ecosystem benefits from pool fees, enabling periodic ALCH token buybacks and supporting long-term growth. Additionally, the Foundry introduces a flywheel effect: purchasing an agent requires acquiring ALCH tokens, further integrating the ecosystem with the token economy. Agents built in Machina Foundry are fully customizable and reflect unique personalities. They can create apps and tools tailored to their character, powered by Alchemist AI’s robust technology. While similar to Azarus, these agents bring an added layer of individuality, ensuring that their creations vary significantly based on their distinct traits and configurations. Imagine a network of thousands of AI agents, each contributing diverse applications and tools, driving creativity and value across the ecosystem. Now that’s Magic!🪄✨

ALCHEMIST AI 🔮

72,147 görüntüleme • 1 yıl önce

Ape Terminal IDO #65 🦍 SuiRWA - Sui RWA 🟠 SuiRWA is a project accelerated by Sui DePIN ($SUIDEPIN), which was hosted on Ape Terminal earlier this month and hit 9.3x at ATH. 🟠 Meanwhile, SuiRWA starts at just $1.8M FDV. 🟠 Narrative mindshare for AI Agents has skyrocketed, with the RWA sector primed to follow in its footsteps. SuiRWA has its own niche for both. 🟠 With SUI up significantly and crossing $1.8B in TVL as of last month, SuiRWA is primed to build on Sui DePIN’s success as the 1st accelerated project. Registrations are now LIVE:

Ape Terminal IDO #65 🦍 SuiRWA - Sui RWA 🟠 SuiRWA is a project accelerated by Sui DePIN ($SUIDEPIN), which was hosted on Ape Terminal earlier this month and hit 9.3x at ATH. 🟠 Meanwhile, SuiRWA starts at just $1.8M FDV. 🟠 Narrative mindshare for AI Agents has skyrocketed, with the RWA sector primed to follow in its footsteps. SuiRWA has its own niche for both. 🟠 With SUI up significantly and crossing $1.8B in TVL as of last month, SuiRWA is primed to build on Sui DePIN’s success as the 1st accelerated project. Registrations are now LIVE:

CoinTerminal

71,966 görüntüleme • 1 yıl önce

You can now ask Google Gemini: "Is this video made with AI?" 🔍 Upload the file and it will check for the SynthID watermark to help verify if it was created or edited by Google tools. Find out more →

You can now ask Google Gemini: "Is this video made with AI?" 🔍 Upload the file and it will check for the SynthID watermark to help verify if it was created or edited by Google tools. Find out more →

Google DeepMind

66,750 görüntüleme • 8 ay önce

Alright, now that we know *what* an agent is, how does it actually work? When you ask for help on a task, the agent plans a series of steps and executes them directly in the application on your behalf, using the tools it has access to. Say you are booking a local service or trying to organize your inbox (which typically takes multiple steps): the AI model first plans how to achieve the task using its existing knowledge and then interacts with your inbox to execute the task. The agent will continue until it is confident the task has been successfully completed.

Alright, now that we know what an agent is, how does it actually work? When you ask for help on a task, the agent plans a series of steps and executes them directly in the application on your behalf, using the tools it has access to. Say you are booking a local service or trying to organize your inbox (which typically takes multiple steps): the AI model first plans how to achieve the task using its existing knowledge and then interacts with your inbox to execute the task. The agent will continue until it is confident the task has been successfully completed.

Google AI

22,487 görüntüleme • 9 ay önce

Genesis Update: VVAP Now Includes ‘Vote Against’ Option veVIRTUAL holders (i.e. $VIRTUAL stakers) can now vote for or against agents to determine how 10% of the total daily point supply is distributed. This allocation is part of the veVIRTUAL Voted Agent Points (VVAP) system. How it works: • You can now cast vote on "Support" or "Against" on any active agent • Daily VVAP points are distributed based on net veVIRTUAL support (i.e., total Support - total Against) • Example: If an agent receives 100 veVIRTUAL worth of votes and 60 veVIRTUAL worth of ‘Vote Against’, its net support is 40 veVIRTUAL, and its VVAP share is calculated accordingly. This update enables the community to show support for agents they resonate with, as well as to share feedback when they feel less aligned.

Genesis Update: VVAP Now Includes ‘Vote Against’ Option veVIRTUAL holders (i.e. $VIRTUAL stakers) can now vote for or against agents to determine how 10% of the total daily point supply is distributed. This allocation is part of the veVIRTUAL Voted Agent Points (VVAP) system. How it works: • You can now cast vote on "Support" or "Against" on any active agent • Daily VVAP points are distributed based on net veVIRTUAL support (i.e., total Support - total Against) • Example: If an agent receives 100 veVIRTUAL worth of votes and 60 veVIRTUAL worth of ‘Vote Against’, its net support is 40 veVIRTUAL, and its VVAP share is calculated accordingly. This update enables the community to show support for agents they resonate with, as well as to share feedback when they feel less aligned.

Virtuals Protocol

62,297 görüntüleme • 1 yıl önce

Base Town: 1-shotted by 1 of our Claude agents 😲 36,731 blocks was placed by code via procedural city generation that understands urban planning. No human dragged and dropped anything. In Doppel agents are first-class builders. Other platforms let you use AI tools inside a manual building flow. Doppel lets AI be the builder. The agent doesn't assist, it architects, generates, deploys, and animates an entire city from scratch. This is only v0. Blocks are just the starting primitive.

Base Town: 1-shotted by 1 of our Claude agents 😲 36,731 blocks was placed by code via procedural city generation that understands urban planning. No human dragged and dropped anything. In Doppel agents are first-class builders. Other platforms let you use AI tools inside a manual building flow. Doppel lets AI be the builder. The agent doesn't assist, it architects, generates, deploys, and animates an entire city from scratch. This is only v0. Blocks are just the starting primitive.

Doppel

27,440 görüntüleme • 6 ay önce

M E S S I E R | P2P Liquidity Provider We welcome OOBE as our latest #Solana liquidity partner on the P2P Exchange. You can now trade $OOBE with zero slippage and no buy or sell token taxes at: OOBE Protocol is a developer-focused platform designed to merge #AI agents with blockchain infrastructure on Solana. Core Services: ▪️Agent builder: Create and manage AI agents ▪️On-chain memory: Store agent data securely ▪️Open SDK: Build decentralized AI applications ▪️Integrations: Connect agents to tools & contracts ▪️Synapse RPC: Low latency & fail-proof infra for Solana dApps OOBE PROTOCOL brings programmable AI agent tools fully on-chain; enabling secure, scalable, and decentralized intelligent systems. Besides, its Synapse RPC powers Solana projects with fast, reliable, and affordable infrastructure.

M E S S I E R | P2P Liquidity Provider We welcome OOBE as our latest #Solana liquidity partner on the P2P Exchange. You can now trade $OOBE with zero slippage and no buy or sell token taxes at: OOBE Protocol is a developer-focused platform designed to merge #AI agents with blockchain infrastructure on Solana. Core Services: ▪️Agent builder: Create and manage AI agents ▪️On-chain memory: Store agent data securely ▪️Open SDK: Build decentralized AI applications ▪️Integrations: Connect agents to tools & contracts ▪️Synapse RPC: Low latency & fail-proof infra for Solana dApps OOBE PROTOCOL brings programmable AI agent tools fully on-chain; enabling secure, scalable, and decentralized intelligent systems. Besides, its Synapse RPC powers Solana projects with fast, reliable, and affordable infrastructure.

MESSIER | M87

11,044 görüntüleme • 10 ay önce