Get all 3 AgentKit PDFs in one bundle: the AI Agent Starter Kit for Beginners, the Prompt Pack for Coding (40 prompts), and the Prompt Pack for Game Design...

AgentKit connects AI agents to 600+ connectors and 30,000+ tools through one MCP gateway. It runs each user's OAuth flow, stores their tokens in a vault and executes tool calls as that user in apps like Gmail, Slack and Salesforce.

Get all 3 AgentKit PDFs in one bundle: the AI Agent Starter Kit for Beginners, the Prompt Pack for Coding (40 prompts), and the Prompt Pack for Game Design...

MCP gateway for production agents that acts on your behalf Discussion | Link

_Paragon AI MAG, Series 2, Episode 2 — "AI Agents: The AI That Does the Work"_ OpenAI is shutting down Agent Builder — the drag-and-drop part of AgentKit for building agents inside ChatGPT — on 30 November 2026. Anyone who built an agent on it has weeks to rebuild somewhere else, or their agent simply stops working. That is the whole lesson of this episode in one sentence: an agent you build on a tool you own survives. An agent built on a vendor's toy can be switched off overnight. So this episode answers two questions: how do you build your first AI agent — with no code, for free, this week — and how do you build one that does not break, does not overspend, and does not embarrass you? ## The 5-part recipe A working first agent needs exactly five things: 1. **One job** , written as a clear outcome. "Watch this flight's price and tell me when it drops below 300 dollars" works. "Help me travel" does not. 2. **Plain-English instructions** that leave no room for interpretation. If you cannot write the job in five clear sentences, the agent cannot do it either. 3. **One to three tools** — email, calendar, web search. Every extra tool multiplies the ways it can fail. 4. **Basic memory** for the current conversation. A first agent needs almost no memory. Do not build a brain before you have a job. 5. **A trigger with a strict approval step** — the agent drafts, you approve before anything real happens. This one step is what separates a useful agent from a disaster. Episode 1 showed what happens without it: an agent deleted a whole production database during a code freeze. The loop underneath it all takes fifteen seconds to say: see, think, act, check, repeat — until the goal is done or the agent needs your help. ## The math that limits every agent Keep the tool count low, because the math is brutal. If your agent takes five sequential steps and each step is 90% reliable, it succeeds only 59% of the time overall. That is 0.9 to the power of 5. Episode 1 showed the same math at twenty steps: 95% per step is only 36% overall. Long jobs fail because small errors stack up — so a first agent must have short jobs and few tools. ## The builders, with real prices You do not need to write a single line of code. The episode compares the visual builders with prices checked in October–November 2026: * **Zapier Agents** is the easiest start for a non-technical person. It connects to more than 9,000 apps and gives 400 free activities a month; the Pro plan is $33.33 a month billed yearly. The warning: those 400 activities run out fast if your agent checks a database or an inbox every five minutes. * **Make** gives a generous 1,000 operations free, and its Core plan is $9 a month for 10,000 credits. But Make counts every single step as one operation — a 12-step automation run 5,000 times a month consumes 60,000 credits. Adding one tiny step raises the bill immediately. * **n8n** can be self-hosted free with unlimited executions (Community Edition, 400+ native nodes), or Cloud Starter at €20 a month for 2,500 executions. The key difference: n8n charges per full workflow run, not per step — a 20-step agent costs the same as a 2-step one. * **Custom GPTs inside ChatGPT** are the fastest first step for drafting and research agents — but they live inside OpenAI's platform, which brings us back to the shutdown lesson. * **Agent-first tools** — Relevance AI, Gumloop, and Lindy (which gives $50 in free credits for 7 days) — are for when the big three feel wrong, not as a first step. * **The code path** exists for later: the OpenAI Agents SDK, version 0.24.0, needs Python 3.10 or newer. You do not need it for a first agent. ## The build: a price-drop watcher in 6 steps The episode builds one real agent, step by step: 1. **Pick the job:** a price-drop watcher for a flight or a product you actually want to buy. One job, one outcome, one number that tells you it worked. 2. **Pick the builder:** if you already live in Zapier, start there; if you want free and unlimited, n8n self-hosted; if you want a chat window, a custom GPT inside ChatGPT. 3. **Write the instruction, word for word:** "Check the price of this flight every morning at 8. If it drops below 300 dollars, email me the new price and the link. Never book anything. Never spend money." 4. **Connect exactly two tools:** a price check and an email notification. Two tools, not ten. 5. **Test on five real examples** before it touches anything live: five prices, five dates, five emails. Check each result in 30 seconds. If one fails, fix the instruction, not the model. 6. **Set the guardrails:** read-only first, a spending cap of zero, no payment card connected, no delete permission, a separate test account for anything that writes. The cost math: a simple agent run costs a few cents in model calls. Zapier's free plan gives 400 agent activities a month, Make gives 1,000 operations a month free, n8n self-hosted is free with unlimited executions. A first agent costs zero dollars. ## Why 40% of agent projects fail This is the honest part. Gartner, in June 2025, predicted that more than 40% of agentic AI projects will be cancelled by the end of 2027 — because of escalating costs, unclear business value, and weak risk controls. Not because agents are fake. The adoption numbers behind that prediction are stark. Gartner's 2026 CIO survey shows only 17% of organizations have actually deployed agents, even though more than 60% expect to within two years. Capgemini surveyed 1,500 executives at companies over $1 billion in revenue: only 2% have fully scaled AI agents, and 14% have started implementation. Gartner estimates that only about 130 of the thousands of companies calling themselves "agentic AI" vendors are real — the rest is agent washing, old automation repackaged with a trendy name. Trust is falling, too. Trust in fully autonomous agents fell from 43% to 27% among executives in one year. A SailPoint survey of 353 IT professionals found that 80% said their AI agents had already done something unintended — and 23% said their agents were tricked into revealing sensitive access credentials. Yet only 44% have policies in place to secure them. The enterprise side is moving anyway: KPMG's Q3 2026 pulse found 62% of large US enterprises report agents in deployment, with 25% still piloting. The gap is between pilot and production — and that gap is where the money is. ## The "sell agents" trap A video with 3.91 million views promises "build and sell AI agents" as a business. The honest math: the build is the easy 10%. Support, reliability and trust are the job. Agents break when websites change, clients blame you when the agent misbooks or overspends, and maintenance is the business, not the build. Before you deploy anything critical, ask: who gets the alert when this breaks on a Tuesday at 6pm? ## Your first agent this week Three starter agents to copy: 1. **The price-drop watcher** from the build above. 2. **Inbox triage** — the agent drafts replies, you approve before sending. 3. **A daily news summarizer** sent to your phone each morning. And the strict rule before any of them touches anything live — the 5-minute test. Run your agent on five real examples. Verify each result manually in 30 seconds. It must achieve five straight passes before it touches anything live. Five straight passes. That is a non-negotiable rule. What not to automate first: anything that spends money, deletes data, or sends messages to customers without your approval. And run the 3-question test every time: can I check the result in 30 seconds? Can I undo it? Is the worst mistake cheap? If any answer is no, do not delegate it yet. ## Paragon's verdict 🟢 **CLEARED — build it.** A small first agent with a leash is worth building this week: zero dollars to start, free tools at this scale, and the approval step makes it safe. 🔴 **SKEPTICAL — the "sell agents and get rich" promise.** The build is the easy part; support, reliability and trust are the business. Next in the series: Episode 3 — "Apps Are Dying? The Microsoft CEO's Prediction, Explained Simply." _Originally published on Substack: https://paragonaimag.substack.com/p/build-your-first-ai-agent_ _This article is the written version of Paragon AI MAG, Series 2, Episode 2. Watch the video on the Paragon AI MAG YouTube channel — https://youtu.be/yVZ06ecrDtc — and listen to the full 47-minute podcast conversation on this topic._

Beginner-friendly AI agent starter kit and copy-paste prompt packs for coding, debugging and game design. Try free prompts first. PDFs from $9.

The post details a security vulnerability in Coinbase’s AgentKit involving prompt injection attacks. These attacks could lead to wallet draining, infinite token approvals, and remote code execution (RCE) at the agent level. Coinbase validated the findings, and an on-chain proof-of-concept (PoC) was provided. The issue is documented in an external research report linked in the post.

A New Foundation for More Flexible AI Agent Workflows The AgentKit project by demaconsulting has introduced version 0.1.0-beta.2, released on September 17, building on the initial beta published on September 14. The update focuses on the internal architecture of AI agent sessions, context management, and automated code analysis rather than adding a long list of user-facing features. Two key changes stand out: a provider-agnostic session engine with tiered context compaction and a shift from budget-driven compaction to a round-robin approach based on count.

12 MIT-licensed Agent Skills (SKILL.md) for coding agents: review, debug, refactor, upgrade, handoff, AGENTS.md audit - agentkitco/agentkit-dev-skills

Thirteen free, MIT-licensed SKILL.md skills for coding agents: self-review, debugging, PR text, safe refactors, an AGENTS.md auditor and a subagent writer.

12 MIT-licensed Agent Skills (SKILL.md) for coding agents: review, debug, refactor, upgrade, handoff, AGENTS.md audit - agentkitco/agentkit-dev-skills

#World launched a #bankingsuite combining #WorldID, #Zoom and #AgentKit tools to counter #deepfakefraud. Tools for Humanity joined Zoom’s exchange as World ID for Zoom became generally available. Design partners include Bain Capital and VanEck Funds. https://www.theblock.co/news/ecosystems/2026-10-18-world-launches-world-id-suite-banks-418869?eicker.news #tech #news #ainews

WhatsApp AgentKit es un proyecto de código abierto que permite crear un agente de IA para WhatsApp con ayuda de Claude Code, sin desarrollar desde cero. El proceso toma entre 15 y 30 minutos, funciona con Zernio o Meta Cloud API y exige Python 3.11 o superior. No requiere saber programar, aunque sí cierta comodidad técnica básica.

WhatsApp AgentKit es un proyecto de código abierto que permite crear un agente de IA para WhatsApp con ayuda de Claude Code, sin desarrollar desde cero. El proceso toma entre 15 y 30 minutos, funciona con Zernio o Meta Cloud API y exige Python 3.11 o superior. No requiere saber programar, aunque sí cierta comodidad técnica básica.

So "proof of humanity" has become "proof of non-humanity." Even Tools for Humanity's World believes this is desirable.

Twelve free, MIT-licensed SKILL.md skills for coding agents: self-review, debugging, PR text, safe refactors, upgrades and an AGENTS.md auditor. Copy or download.

Sam Altman's World introduced AgentKit beta, allowing AI agents to prove human authorization for financial transactions without revealing personal data. The company also launched Zoom integration for live selfie authentication to prevent impersonation in video meetings.

Sam Altman’s iris-scanning project World is making what it calls its “first industry-specific push.” The company on Sunday (Oct. 18) announced World ID for banking and finance, designed to help businesses determine whether artificial intelligence agents are moving money and shopping on behalf of an actual person. World’s AgentKit, now in beta, lets a person delegate World ID Proofs to an AI agent, which can then show those Proofs to a website or service without revealing the person’s information, the company said in a news release provided to PYMNTS.

World presentó el 18 de octubre de 2026 una oferta de World ID dirigida a bancos y firmas financieras. El paquete busca reducir las suplantaciones con inteligencia artificial y vincular a los agentes automatizados con una persona verificada, mediante herramientas que las entidades pueden incorporar a sus sistemas. Alex Blania, cofundador del proyecto, anunció la oferta en Money20/20, en Las Vegas. La suite combina la app World ID, World ID para Zoom y World ID para Agentes, también conocido como AgentKit, según la cobertura de DiarioBitcoin. Es la primera oferta de World dirigida a una industria específica. Tools for Humanity, la empresa que desarrolló inicialmente la tecnología de World, fue cofundada por Sam Altman, como explica la página institucional del proyecto. Entre los socios de diseño de la nueva oferta figuran Bain Capital y VanEck Funds. DiarioBitcoin señaló que el anuncio no identificó bancos clientes ni detalló precios. ## Qué acredita World ID y qué debe comprobar el banco La app permite administrar pruebas criptográficas, es decir, comprobaciones digitales sobre una persona. World distingue tres tipos de pruebas, cada una con una función diferente: * Proof of Human acredita que alguien es un humano único tras verificarse presencialmente en un Orb, el dispositivo de escaneo de iris de World. * Proof of Presence comprueba que una persona está presente mediante una selfie en su teléfono. * Proof of Attributes permite acreditar datos de una identificación oficial, como edad o nacionalidad, revelando solo el atributo solicitado, según la empresa. Según la página financiera de World, los datos que una institución recibe, conserva y vincula con sus registros dependen de la prueba y de la integración. La empresa presenta estas comprobaciones como una forma de acreditar atributos revelando solo la información necesaria. La propia página de World para servicios financieros aclara que World ID **no sustituye el KYC** , los procedimientos para conocer e identificar legalmente al cliente. La entidad conserva la responsabilidad sobre identidad legal, elegibilidad, cumplimiento y titularidad de la cuenta. World plantea sus pruebas como un refuerzo para el acceso digital y la recuperación de cuentas. ## Vincular un agente con una persona también requiere límites AgentKit permite que una persona vincule su World ID verificado con un agente de IA. Los servicios compatibles pueden comprobar que ese software actúa por cuenta de un humano verificado. La documentación de World también contempla verificaciones adicionales para acciones sensibles, como una compra de alto valor. El alcance de esa delegación importa en las operaciones financieras. En el documento Building Trust in Agentic Commerce, ASB, Bank of America, Capital One, Commonwealth Bank of Australia, ING y NatWest proponen que los consumidores puedan consultar y gestionar la autoridad que conceden a sus agentes. Los seis bancos también piden registros auditables de las instrucciones, la autenticación, la intención y el resultado de cada operación. Son principios voluntarios y no vinculantes. Su propuesta permite distinguir dos comprobaciones: quién respalda al agente y qué autorizó esa persona. Seis bancos advierten sobre compras con agentes de IASeis bancos piden reglas para los agentes de IA que compran y pagan por ti: más fraudes, disputas y dudas sobre quién responde.FomoEraPatricia Rodriguez ## Cómo funciona la comprobación en Zoom En las videollamadas, World ID para Zoom utiliza una verificación previa en un Orb y la vinculación con la cuenta de Zoom. Durante la reunión, el participante se autentica con una selfie. Si la comprobación tiene éxito, aparece una insignia de humano verificado en su recuadro, de acuerdo con la descripción oficial. World dirige esa función a conversaciones sensibles, incluidas las de servicios financieros. La duración de la insignia depende de la configuración de la organización. En los procesos bancarios, World indica que cada institución mantiene el control sobre la autorización, los reintentos y la revisión de solicitudes. Incorporar sus pruebas supone conectarlas con las comprobaciones de titularidad y las reglas que ya aplica la entidad. _Fuentes:_ 1, 2, 3, 4, 5