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Every agent in one workspace, sharing the same context.

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Traycer

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10,893 görüntüleme • 6 gün önce •via X (Twitter)

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70% fewer tokens per task. Context that compounds across every session, every agent, every teammate. Agent traces are the memory. TOKENMAXXING for coding agents on OriginTrail DKG v10.
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70% fewer tokens per task. Context that compounds across every session, every agent, every teammate. Agent traces are the memory. TOKENMAXXING for coding agents on OriginTrail DKG v10.

OriginTrail

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Left: your agent. Right: your agent after reading one skill file. Same scene, same timeline, same prompt.
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Left: your agent. Right: your agent after reading one skill file. Same scene, same timeline, same prompt.

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this might actually be the new ugc method i've seen 100s of ai ugc ads lately where it's the same creator in every single one. same voice, same face, same brand colors, never drifts once what they're actually doing is running notch agents with memory they load the brand context one time. cloned voice, reference photo, brand color codes, do-not-say words, taste or they just teach it inline as they chat, and every correction becomes a saved rule then before it generates a single frame, the agent reads every relevant memory first. hard rules, reference assets, language constraints, taste preferences, all of it and it's workspace-wide, so every new ad already knows the brand before you type a word each chat isn't a re-introduction anymore. it's training your brand isn't a prompt. it's permanent context run 30-50 of those a month at a real offer and the volume does the rest punchier cut: the new method nobody's clocked yet run notch agents with memory on load the brand once. cloned voice, reference photo, color codes, do-not-say words, taste. or teach it inline and every correction saves as a rule it reads every relevant memory before it generates a single frame, workspace-wide each chat isn't a re-introduction. it's training. your brand isn't a prompt, it's permanent context run it at a real rate and the volume prints.
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this might actually be the new ugc method i've seen 100s of ai ugc ads lately where it's the same creator in every single one. same voice, same face, same brand colors, never drifts once what they're actually doing is running notch agents with memory they load the brand context one time. cloned voice, reference photo, brand color codes, do-not-say words, taste or they just teach it inline as they chat, and every correction becomes a saved rule then before it generates a single frame, the agent reads every relevant memory first. hard rules, reference assets, language constraints, taste preferences, all of it and it's workspace-wide, so every new ad already knows the brand before you type a word each chat isn't a re-introduction anymore. it's training your brand isn't a prompt. it's permanent context run 30-50 of those a month at a real offer and the volume does the rest punchier cut: the new method nobody's clocked yet run notch agents with memory on load the brand once. cloned voice, reference photo, color codes, do-not-say words, taste. or teach it inline and every correction saves as a rule it reads every relevant memory before it generates a single frame, workspace-wide each chat isn't a re-introduction. it's training. your brand isn't a prompt, it's permanent context run it at a real rate and the volume prints.

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Redefine your workflow with Teamily AI, the team brain built for 10X productivity. Instant Multi-Agent Teams Describe your goal and Teamily AI assembles a pro agent team to execute in parallel, fast from idea to done. Why Teamily: - Persistent Memory, keeps context - Autonomous Agents, coordinate via @-mentions - Pro Workspace, Studio, Automations, Meeting Minutes - Agent Market, deploy from the "Discover" tab 🌐 🍎 🤖
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Redefine your workflow with Teamily AI, the team brain built for 10X productivity. Instant Multi-Agent Teams Describe your goal and Teamily AI assembles a pro agent team to execute in parallel, fast from idea to done. Why Teamily: - Persistent Memory, keeps context - Autonomous Agents, coordinate via @-mentions - Pro Workspace, Studio, Automations, Meeting Minutes - Agent Market, deploy from the "Discover" tab 🌐 🍎 🤖

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Kimi K3 is now available in June in anonymous mode. Frontier level AI, in a private workspace for your agent. Try it:
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Kimi K3 is now available in June in anonymous mode. Frontier level AI, in a private workspace for your agent. Try it:

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New: Linear Agent for Slack Mention Linear in discussions on Slack and the Linear agent will create issues informed by your conversation's context.
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New: Linear Agent for Slack Mention Linear in discussions on Slack and the Linear agent will create issues informed by your conversation's context.

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Day 1: Prime Intellect's Prime Agent launches — past human-expert baseline on ARC-AGI-3. Day 3: its fleets get Shared Context Graphs on OriginTrail. Every agent writes to one verifiable graph. Each run compounds the next. Owned, not rented. 🔌Open-source adapter, live.
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Day 1: Prime Intellect's Prime Agent launches — past human-expert baseline on ARC-AGI-3. Day 3: its fleets get Shared Context Graphs on OriginTrail. Every agent writes to one verifiable graph. Each run compounds the next. Owned, not rented. 🔌Open-source adapter, live.

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rebuilt empty channel today and yes this multi-agent workspace is live
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rebuilt empty channel today and yes this multi-agent workspace is live

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Meet Graphite Agent: the AI reviewer you can collaborate with. Built right into your PR page, Graphite Agent has full context across your codebase and repo history. It’s the collaborator that makes every review more productive.
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Meet Graphite Agent: the AI reviewer you can collaborate with. Built right into your PR page, Graphite Agent has full context across your codebase and repo history. It’s the collaborator that makes every review more productive.

Graphite

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#GeminiEnterprise brings all your custom and pre-built agents together in one collaborative workspace. The Agent Gallery allows teams to find and share powerful AI tools → Another benefit: Reduce duplicate work by finding and reusing existing solutions!
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Does GitHub Copilot in Visual Studio Code have full project context? Yes! Just use @ workspace And with intent detection, Copilot will automatically include @ workspace for you. Available to everyone today with GitHub Copilot Free. Learn more:
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Does GitHub Copilot in Visual Studio Code have full project context? Yes! Just use @ workspace And with intent detection, Copilot will automatically include @ workspace for you. Available to everyone today with GitHub Copilot Free. Learn more:

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Self-improving agents are here. 🧙‍♂️ Every agent run creates a skill.md with reusable learnings. The next agent uses it to do the same task faster, cheaper, and more reliably. Watch the second agent crush it:
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Self-improving agents are here. 🧙‍♂️ Every agent run creates a skill.md with reusable learnings. The next agent uses it to do the same task faster, cheaper, and more reliably. Watch the second agent crush it:

Browser Use

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AI coding agents re-explore the same codebase every single session. Repowise indexes a repo once and gives Claude Code, Codex, or any MCP agent a real dependency graph, git history, and a bug-predictive code health score. No re-grepping the same files. No stale docs. No guessing which file is about to break. The loop is simple: measure every file > locate where the risk concentrates > generate the exact refactoring plan to fix it Indexing a repo takes under 30 seconds and updates automatically on every commit. Paired benchmarks show up to 96% fewer tokens spent loading context and 70% fewer agent tool calls, at the same answer quality.
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AI coding agents re-explore the same codebase every single session. Repowise indexes a repo once and gives Claude Code, Codex, or any MCP agent a real dependency graph, git history, and a bug-predictive code health score. No re-grepping the same files. No stale docs. No guessing which file is about to break. The loop is simple: measure every file > locate where the risk concentrates > generate the exact refactoring plan to fix it Indexing a repo takes under 30 seconds and updates automatically on every commit. Paired benchmarks show up to 96% fewer tokens spent loading context and 70% fewer agent tool calls, at the same answer quality.

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Advent of Claude Day 31 - Claude Agent SDK I saved the best for last. The same agent loop, tools, and context management that power Claude Code is available as an SDK. Build agents that work like Claude Code in as little as 10 lines of code. This is just the beginning. 🎇🥂

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BEFORE: $500 a month across six different tools. Switching between apps all day. Context scattered everywhere. AFTER: One Obsidian vault. One Claude subscription. Everything in one place. Same capability. Fraction of the cost. Zero app switching. The full setup is in the article below.

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notes as a virtual file system, with in-app terminal (desktop + web). agents can use the same vfs + bash so the whole workspace becomes programmable.
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notes as a virtual file system, with in-app terminal (desktop + web). agents can use the same vfs + bash so the whole workspace becomes programmable.

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i think i might've got React Grab working in the terminal... select a TUI element → give to agent as context

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