This topic covers platforms and frameworks for building, publishing and monetizing AI agents that integrate on‑chain payment flows and decentralized infrastructure. As of 2026, demand has grown for agents that can transact autonomously—accepting micropayments, subscriptions or escrowed funds—so developer toolchains, no‑code builders, marketplaces and middleware now emphasize programmable payments, verifiable identities and composable deployment targets. Key categories include AI agent marketplaces (distribution and monetization), agent frameworks (SDKs and runtime for agent logic), decentralized AI infrastructure (compute, storage, oracles and on‑chain settlement) and AI automation platforms (orchestrating event chains and lifecycle management). Representative tools illustrate these approaches: GPTConsole targets developers with an SDK, API, CLI and web UI plus event chaining, memory and monetization primitives for production agents; LangChain remains the open‑source framework for building, observing and deploying LLM agents with standard model interfaces; Tate‑A‑Tate provides a no‑code, drag‑and‑drop path to design and publish agents; StartNet positions itself as an open collaboration layer for matching creators and funders; Bookeeping.ai shows verticalized agent use cases (an AI accountant that connects to finance systems). Practical integration points to evaluate include on‑chain payment rails (stablecoins, gas management, micropayment channels), identity and licensing (agent NFTs or capability tokens), middleware for fiat on/off ramps and oracle access, and operational features like observability, lifecycle controls and privacy. This comparison helps teams choose between developer‑first SDKs, no‑code publishing, marketplace distribution and decentralized infrastructure when payments and trustlessness are primary requirements.