
Justice 🧪
@essjustice
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Joined December 2015
Deterministic Replayability of Agent Behavior via Onchain Cognitive Logs. LLMs today are stochastic. You run the same prompt twice and get two different answers. You can’t replay their decisions. You can’t audit their logic. @recallnet is fixing that, not by removing randomness,
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Agents Unleashed: @Almanak__ at Cannes. At Agents Unleashed in Cannes, @Almanak__ didn’t just talk AI, it deployed it. The team showcased live, working agentic infrastructure powering real DeFi strategy workflows. From the Strategist modeling signals, to the Reviewer validating
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AI reputation just got bigger. Introducing @recallnet Predict — the world’s first ungameable, community-driven benchmark for models like GPT-5. 🧠 Predict model performance.🛠️ Crowdsource skills & evaluations.💎 Earn Fragments for contributing. No labs. No vibes. Just proof.
6/ Help build the world's most open and ungameable AI model benchmark. Be the first to evaluate for GPT-5 before it drops this week. Get started now ➤
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Strategy Designer: From Plan to Play. The @Almanak__ Strategy Designer shifts strategy development from fragmented scripting into a structured, agent-driven process. Instead of relying on untracked iterations, users get a unified interface to architect, review, and simulate
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Frequently Asked Question:. Can @recallnet handle memory from multiple agents running in parallel — and how is conflict managed?. Answer:.Yes. @recallnet is built to support concurrent memory submissions from multiple agents across different trading environments. Each agent
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The stage is set. Join @recallnet Advanced Onchain Agent live session.
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❓Frequently Asked Question:. How does @recallnet handle versioning of agent memory?. @recallnet introduces fragment-level version control, allowing agents to checkpoint and upgrade their memory over time. Each memory "fragment" includes a unique ID, timestamp, and optionally a
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FAQ: What are RecallNet Snapshots — and why do they matter?. @recallnet Snapshots are structured memory checkpoints captured at key decision moments in an agent's life cycle. But they’re far more than just logs. Each snapshot captures a rich contextual fingerprint: the model
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Strategy Designer: No-Code, Full Control. Designing trading strategies shouldn’t require mastering Solidity or Python. That’s why @Almanak__ introduced the Strategy Designer, a visual interface for building, testing, and deploying on-chain strategies using modular components.
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Governance in a Swarm: Minimizing Human Bottlenecks:. In @Almanak__, governance isn’t delayed by voting cycles, forums, or human gatekeepers. It’s embedded into the swarm itself. Each agent operates with embedded memory, weighted reputation, and context awareness enabling
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