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Agent Intent Infrastructure

Learn how software discovers a Tangle service, runs a bounded task, pays per request, and keeps evidence. A Blueprint is a reusable service definition, a Job is one callable unit, and an operator runs that Job.

For teams integrating external agent services, this series separates discovery, execution, payment, and evidence so each boundary can be designed and tested on its own.

Start here: How AI Agents Discover Products. Then continue in the order below.

An editorial still life about describing and running an agent task
Part 1

How AI Agents Discover Products

AI agents discover products through stable URLs, scoped packages, safe calls, OpenAPI files, manifests, and READMEs they can verify.

An editorial still life about describing and running an agent task
Part 2

AI Agent Sandbox: Build a Controlled Agent Workspace

An AI agent sandbox gives a software agent isolated files, processes, network rules, and reviewable output. Learn how to test the workspace with a real task.

An editorial still life about describing and running an agent task
Part 3

Browser Automation for AI Agents: Evidence and Safe Stops

Browser automation for AI agents needs page state, screenshots, recovery, and a clear stop condition so a reviewer can tell what happened.

An editorial still life about describing and running an agent task
Part 4

OpenAI Compatible Routers for Agents

OpenAI-compatible routers keep one request shape while exposing model discovery, routing policy, usage records, and provider or cost changes.

An editorial still life about describing and running an agent task
Part 5

x402 Payments for AI Agents: v2 Safety Guide

Learn how x402 payments for AI agents expose payment requirements, prevent duplicate work, reconcile settlement, and separate receipts from proof of results.

An editorial still life about describing and running an agent task
Part 6

Natural Language E2E Testing for Wallet Apps

Natural-language E2E testing for wallet apps lets agents drive browser flows while stopping before destructive signing and preserving evidence.

An editorial still life about describing and running an agent task
Part 7

AI Agent Runtime Environment: Tools, State, and Proof

An AI agent runtime environment gives a model tools, files, permissions, and records for real work. Follow a toy tax-document review workflow.

An editorial still life about describing and running an agent task
Part 8

Tangle Sandbox vs E2B: Choosing An AI Agent Sandbox

Tangle Sandbox and E2B both isolate agent code, but differ in durable sessions, workspace recovery, templates, and trace-oriented review.

An editorial still life about describing and running an agent task
Part 9

Tangle Sandbox vs Daytona and Modal

Compare Tangle Sandbox, Daytona, and Modal by work unit: durable agent computer, development sandbox, or serverless job or GPU workload.

An editorial still life about describing and running an agent task
Part 10

Tangle Browser Agent vs Browserbase and Browser Use

Compare Tangle Browser Agent, Browserbase, and Browser Use by task evidence, browser sessions, workspace control, and API surface.

An editorial still life about describing and running an agent task
Part 11

Deploy a Paid AI Agent Service: One Traceable Job

A practical path for exposing one paid AI job with discovery, authorization, payment, execution, recovery, and evidence that a buyer can inspect.

An editorial still life about hardware-backed evidence for an AI service
Part 12

TEE Attestation for AI Services: What the Evidence Proves

TEE attestation can bind an AI service request to approved code on protected hardware, but it cannot prove the answer is correct. Check reports and secrets.