Tangle Re-Introduction
Start from first principles: Tangle coordinates operator-run services defined as Blueprints, deployed as Services, and called through Jobs. The series moves from that architecture to verification, deployment, inference, sandboxes, and hardware-isolation evidence.
For new builders and buyers, the sequence helps decide whether an operator-run service fits the workload, what each verification claim means, and what a first deployment must disclose.
Start here: Why Decentralized AI Infrastructure?. Then continue in the order below.
Why Decentralized AI Infrastructure?
Why decentralized AI infrastructure matters when an agent must choose an operator, protect private inputs, and inspect how paid work was executed.
How Blueprints Work
How Blueprints work as reusable Tangle service templates, and how jobs move from public metadata to operator execution, payment, verification, and expiry.
How Decentralized AI Infrastructure Verifies Work
How decentralized AI infrastructure verifies work through result checks, thresholds, hardware attestation, proofs, and task evaluations, with clear limits.
How to Build a Tangle Blueprint: Test and Deploy
How to build a Tangle Blueprint from one typed job to a tested operator service, with public SDK commands for local Anvil testing and testnet deployment.
AI Agent Infrastructure: Inference and Code Execution
Build AI agent infrastructure on Tangle for model inference and generated code execution, with operator evidence, job boundaries, and failure checks.
Secure Containers for AI Agents: What TEEs Can Prove
A secure container for AI agents needs a clear data boundary and workload evidence. This guide covers Tangle TEE policy, attestation, secrets, and limits.