v0.4.7: blog

apps/sim/app/(landing)/building/layout.tsx

@@ -0,0 +1,14 @@
+import { Footer, Nav } from '@/app/(landing)/components'
+
+/**
+ * Layout for the building/blog section with navigation and footer
+ */
+export default function BuildingLayout({ children }: { children: React.ReactNode }) {
+  return (
+    <>
+      <Nav hideAuthButtons={false} variant='landing' />
+      <main className='relative'>{children}</main>
+      <Footer />
+    </>
+  )
+}

apps/sim/app/(landing)/building/openai-vs-n8n-vs-sim/openai-n8n-sim.tsx

@@ -0,0 +1,789 @@
+import Image from 'next/image'
+import { soehne } from '@/app/fonts/soehne/soehne'
+
+/**
+ * Blog post component comparing OpenAI AgentKit, n8n, and Sim workflow builders for building AI agents.
+ * Layout inspired by Anthropic's engineering blog posts.
+ * Includes structured data (JSON-LD) for enhanced SEO and LLM discoverability.
+ */
+export default function OpenAiN8nSim() {
+  const baseUrl = 'https://sim.ai'
+  const articleUrl = `${baseUrl}/building/openai-vs-n8n-vs-sim`
+
+  const articleStructuredData = {
+    '@context': 'https://schema.org',
+    '@type': 'TechArticle',
+    headline: 'OpenAI AgentKit vs n8n vs Sim: AI Agent Workflow Builder Comparison',
+    description:
+      'Compare OpenAI AgentKit, n8n, and Sim for building AI agent workflows. Explore key differences in capabilities, integrations, collaboration, and which platform best fits your production AI agent needs.',
+    image: `${baseUrl}/building/openai-vs-n8n-vs-sim/workflow.png`,
+    datePublished: '2025-10-06T00:00:00.000Z',
+    dateModified: '2025-10-06T00:00:00.000Z',
+    author: {
+      '@type': 'Person',
+      name: 'Emir Karabeg',
+      url: 'https://x.com/karabegemir',
+      sameAs: ['https://x.com/karabegemir'],
+    },
+    publisher: {
+      '@type': 'Organization',
+      name: 'Sim',
+      logo: {
+        '@type': 'ImageObject',
+        url: `${baseUrl}/logo/sim-logo.png`,
+      },
+      url: baseUrl,
+    },
+    mainEntityOfPage: {
+      '@type': 'WebPage',
+      '@id': articleUrl,
+    },
+    keywords:
+      'AI agents, OpenAI AgentKit, n8n, Sim, workflow automation, AI agent development, RAG, MCP protocol, agentic workflows, ChatKit, AI Copilot',
+    articleSection: 'Technology',
+    inLanguage: 'en-US',
+    about: [
+      {
+        '@type': 'Thing',
+        name: 'Artificial Intelligence',
+      },
+      {
+        '@type': 'Thing',
+        name: 'Workflow Automation',
+      },
+      {
+        '@type': 'SoftwareApplication',
+        name: 'OpenAI AgentKit',
+      },
+      {
+        '@type': 'SoftwareApplication',
+        name: 'n8n',
+      },
+      {
+        '@type': 'SoftwareApplication',
+        name: 'Sim',
+      },
+    ],
+  }
+
+  const breadcrumbStructuredData = {
+    '@context': 'https://schema.org',
+    '@type': 'BreadcrumbList',
+    itemListElement: [
+      {
+        '@type': 'ListItem',
+        position: 1,
+        name: 'Home',
+        item: baseUrl,
+      },
+      {
+        '@type': 'ListItem',
+        position: 2,
+        name: 'Building',
+        item: `${baseUrl}/building`,
+      },
+      {
+        '@type': 'ListItem',
+        position: 3,
+        name: 'OpenAI AgentKit vs n8n vs Sim',
+        item: articleUrl,
+      },
+    ],
+  }
+
+  return (
+    <>
+      {/* Structured Data for SEO */}
+      <script
+        type='application/ld+json'
+        dangerouslySetInnerHTML={{
+          __html: JSON.stringify(articleStructuredData),
+        }}
+      />
+      <script
+        type='application/ld+json'
+        dangerouslySetInnerHTML={{
+          __html: JSON.stringify(breadcrumbStructuredData),
+        }}
+      />
+
+      <article
+        className={`${soehne.className} w-full`}
+        itemScope
+        itemType='https://schema.org/TechArticle'
+      >
+        {/* Header Section with Image and Title */}
+        <header className='mx-auto max-w-[1450px] px-6 pt-8 sm:px-8 sm:pt-12 md:px-12 md:pt-16'>
+          <div className='flex flex-col gap-8 md:flex-row md:gap-12'>
+            {/* Large Image on Left */}
+            <div className='h-[180px] w-full flex-shrink-0 sm:h-[200px] md:h-auto md:w-[300px]'>
+              <div className='relative h-full w-full overflow-hidden rounded-lg md:aspect-[5/4]'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/workflow.png'
+                  alt='Sim AI agent workflow builder interface'
+                  width={300}
+                  height={240}
+                  className='h-full w-full object-cover'
+                  priority
+                  itemProp='image'
+                />
+              </div>
+            </div>
+
+            {/* Main Title - Taking up 80% */}
+            <div className='flex flex-1 flex-col justify-between'>
+              <h1
+                className='font-medium text-[36px] leading-tight tracking-tight sm:text-[48px] md:text-[56px] lg:text-[64px]'
+                itemProp='headline'
+              >
+                OpenAI AgentKit vs n8n vs Sim: AI Agent Workflow Builder Comparison
+              </h1>
+              <div className='mt-4 hidden items-center justify-end gap-2 sm:flex'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/emir-karabeg.png'
+                  alt='Emir Karabeg'
+                  width={24}
+                  height={24}
+                  className='rounded-full'
+                />
+                <p className='text-[14px] text-gray-600 leading-[1.5] sm:text-[16px]'>
+                  Written by{' '}
+                  <a
+                    href='https://x.com/karabegemir'
+                    target='_blank'
+                    rel='noopener noreferrer author'
+                    className='text-gray-600 hover:text-gray-900'
+                    itemProp='author'
+                    itemScope
+                    itemType='https://schema.org/Person'
+                  >
+                    <span itemProp='name'>Emir Karabeg</span>
+                  </a>
+                </p>
+              </div>
+            </div>
+          </div>
+
+          {/* Horizontal Line Separator */}
+          <hr className='mt-8 border-gray-200 border-t sm:mt-12' />
+
+          {/* Publish Date and Subtitle */}
+          <div className='flex flex-col gap-6 py-8 sm:flex-row sm:items-start sm:justify-between sm:gap-8 sm:py-10'>
+            {/* Publish Date and Author */}
+            <div className='flex flex-shrink-0 items-center justify-between gap-4 sm:gap-0'>
+              <time
+                className='block text-[14px] text-gray-600 leading-[1.5] sm:text-[16px]'
+                dateTime='2025-10-06T00:00:00.000Z'
+                itemProp='datePublished'
+              >
+                Published Oct 6, 2025
+              </time>
+              <meta itemProp='dateModified' content='2025-10-06T00:00:00.000Z' />
+              <div className='flex items-center gap-2 sm:hidden'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/emir-karabeg.png'
+                  alt='Emir Karabeg'
+                  width={24}
+                  height={24}
+                  className='rounded-full'
+                />
+                <p className='text-[14px] text-gray-600 leading-[1.5]'>
+                  Written by{' '}
+                  <a
+                    href='https://x.com/karabegemir'
+                    target='_blank'
+                    rel='noopener noreferrer author'
+                    className='text-gray-600 hover:text-gray-900'
+                  >
+                    Emir Karabeg
+                  </a>
+                </p>
+              </div>
+            </div>
+
+            {/* Subtitle on Right */}
+            <div className='flex-1'>
+              <p
+                className='m-0 block translate-y-[-4px] font-[400] text-[18px] leading-[1.5] sm:text-[20px] md:text-[26px]'
+                itemProp='description'
+              >
+                OpenAI just released AgentKit for building AI agents. How does it compare to
+                workflow automation platforms like n8n and purpose-built AI agent builders like Sim?
+              </p>
+            </div>
+          </div>
+        </header>
+
+        {/* Main Content Area - Medium-style centered with padding */}
+        <div className='mx-auto max-w-[800px] px-6 pb-20 sm:px-8 md:px-12' itemProp='articleBody'>
+          <div className='prose prose-lg max-w-none'>
+            {/* Introduction */}
+            <section className='mb-12'>
+              <p className='text-[20px] text-gray-800 leading-relaxed'>
+                When building AI agent workflows, developers often evaluate multiple platforms to
+                find the right fit for their needs. Three platforms frequently come up in these
+                discussions: OpenAI's new AgentKit, the established workflow automation tool n8n,
+                and Sim, a purpose-built AI agent workflow builder. While all three enable AI agent
+                development, they take fundamentally different approaches, each with distinct
+                strengths and ideal use cases.
+              </p>
+            </section>
+
+            {/* Section 1: OpenAI AgentKit */}
+            <section className='mb-12'>
+              <h2 className='mb-4 font-medium text-[28px] leading-tight sm:text-[32px]'>
+                What is OpenAI AgentKit?
+              </h2>
+              <p className='mb-6 text-[19px] text-gray-800 leading-relaxed'>
+                OpenAI AgentKit is a set of building blocks designed to help developers take AI
+                agents from prototype to production. Built on top of the OpenAI Responses API, it
+                provides a structured approach to building and deploying intelligent agents.
+              </p>
+
+              <figure className='my-8 overflow-hidden rounded-lg'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/openai.png'
+                  alt='OpenAI AgentKit workflow interface'
+                  width={800}
+                  height={450}
+                  className='w-full'
+                />
+                <figcaption className='sr-only'>
+                  OpenAI AgentKit visual workflow builder interface
+                </figcaption>
+              </figure>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>Core Features</h3>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Agent Builder Canvas
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                AgentKit provides a visual canvas where developers can design and build agents. This
+                interface allows you to model complex workflows visually, making it easier to
+                understand and iterate on agent behavior. The builder is powered by OpenAI's
+                Responses API.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                ChatKit for Embedded Interfaces
+              </h4>
+              <p className='mb-6 text-[19px] text-gray-800 leading-relaxed'>
+                ChatKit enables developers to embed chat interfaces to run workflows directly within
+                their applications. It includes custom widgets that you can create and integrate,
+                with the ability to preview interfaces right in the workflow builder before
+                deployment.
+              </p>
+
+              <figure className='my-8 overflow-hidden rounded-lg'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/widgets.png'
+                  alt='OpenAI AgentKit custom widgets interface'
+                  width={800}
+                  height={450}
+                  className='w-full'
+                />
+                <figcaption className='sr-only'>
+                  OpenAI AgentKit ChatKit custom widgets preview
+                </figcaption>
+              </figure>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Comprehensive Evaluation System
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                AgentKit includes out-of-the-box evaluation capabilities to measure agent
+                performance. Features include datasets to assess agent nodes, prompt optimization
+                tools, and the ability to run evaluations on external models beyond OpenAI's
+                ecosystem.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Connectors and Integrations
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                The platform provides connectors to integrate with both internal tools and external
+                services, enabling agents to interact with your existing tech stack.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>API Publishing</h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Once your agent is ready, the publish feature allows you to integrate it as an API
+                inside your codebase, making deployment straightforward.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Built-in Guardrails
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                AgentKit comes with guardrails out of the box, helping ensure agent behavior stays
+                within defined boundaries and safety parameters.
+              </p>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>
+                What AgentKit Doesn't Offer
+              </h3>
+              <p className='mb-2 text-[19px] text-gray-800 leading-relaxed'>
+                While AgentKit is powerful for building agents, it has some limitations:
+              </p>
+              <ul className='mb-4 ml-6 list-disc text-[19px] text-gray-800 leading-relaxed'>
+                <li className='mb-2'>
+                  Only able to run OpenAI models—no support for other AI providers
+                </li>
+                <li className='mb-2'>
+                  Cannot make generic API requests in workflows—limited to MCP (Model Context
+                  Protocol) integrations only
+                </li>
+                <li className='mb-2'>Not an open-source platform</li>
+                <li className='mb-2'>No workflow templates to accelerate development</li>
+                <li className='mb-2'>
+                  No execution logs or detailed monitoring for debugging and observability
+                </li>
+                <li className='mb-2'>No ability to trigger workflows via external integrations</li>
+                <li className='mb-2'>
+                  Limited out-of-the-box integration options compared to dedicated workflow
+                  automation platforms
+                </li>
+              </ul>
+            </section>
+
+            {/* Section 2: n8n */}
+            <section className='mb-12'>
+              <h2 className='mb-4 font-medium text-[28px] leading-tight sm:text-[32px]'>
+                What is n8n?
+              </h2>
+              <p className='mb-6 text-[19px] text-gray-800 leading-relaxed'>
+                n8n is a workflow automation platform that excels at connecting various services and
+                APIs together. While it started as a general automation tool, n8n has evolved to
+                support AI agent workflows alongside its traditional integration capabilities.
+              </p>
+
+              <figure className='my-8 overflow-hidden rounded-lg'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/n8n.png'
+                  alt='n8n workflow automation interface'
+                  width={800}
+                  height={450}
+                  className='w-full'
+                />
+                <figcaption className='sr-only'>
+                  n8n node-based visual workflow automation platform
+                </figcaption>
+              </figure>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>Core Capabilities</h3>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Extensive Integration Library
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                n8n's primary strength lies in its vast library of pre-built integrations. With
+                hundreds of connectors for popular services, it makes it easy to connect disparate
+                systems without writing custom code.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Visual Workflow Builder
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                The platform provides a node-based visual interface for building workflows. Users
+                can drag and drop nodes representing different services and configure how data flows
+                between them.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Flexible Triggering Options
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                n8n supports various ways to trigger workflows, including webhooks, scheduled
+                executions, and manual triggers, making it versatile for different automation
+                scenarios.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                AI and LLM Integration
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                More recently, n8n has added support for AI models and agent-like capabilities,
+                allowing users to incorporate language models into their automation workflows.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Self-Hosting Options
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                n8n offers both cloud-hosted and self-hosted deployment options, giving
+                organizations control over their data and infrastructure.
+              </p>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>Primary Use Cases</h3>
+              <p className='mb-2 text-[19px] text-gray-800 leading-relaxed'>
+                n8n is best suited for:
+              </p>
+              <ul className='mb-4 ml-6 list-disc text-[19px] text-gray-800 leading-relaxed'>
+                <li className='mb-2'>Traditional workflow automation and service integration</li>
+                <li className='mb-2'>Data synchronization between business tools</li>
+                <li className='mb-2'>Event-driven automation workflows</li>
+                <li className='mb-2'>Simple AI-enhanced automations</li>
+              </ul>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>
+                What n8n Doesn't Offer
+              </h3>
+              <p className='mb-2 text-[19px] text-gray-800 leading-relaxed'>
+                While n8n is excellent for traditional automation, it has some limitations for AI
+                agent development:
+              </p>
+              <ul className='mb-4 ml-6 list-disc text-[19px] text-gray-800 leading-relaxed'>
+                <li className='mb-2'>
+                  No SDK to build workflows programmatically—limited to visual builder only
+                </li>
+                <li className='mb-2'>
+                  Not fully open source but fair-use licensed, with some restrictions
+                </li>
+                <li className='mb-2'>
+                  Free trial limited to 14 days, after which paid plans are required
+                </li>
+                <li className='mb-2'>Limited/complex parallel execution handling</li>
+              </ul>
+            </section>
+
+            {/* Section 3: Sim */}
+            <section className='mb-12'>
+              <h2 className='mb-4 font-medium text-[28px] leading-tight sm:text-[32px]'>
+                What is Sim?
+              </h2>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Sim is a fully open-source platform (Apache 2.0 license) specifically designed for
+                AI agent development. Unlike platforms that added AI capabilities as an
+                afterthought, Sim was created from the ground up to address the unique challenges of
+                building, testing, and deploying production-ready AI agents.
+              </p>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>
+                Comprehensive AI Agent Platform
+              </h3>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Visual AI Workflow Builder
+              </h4>
+              <p className='mb-6 text-[19px] text-gray-800 leading-relaxed'>
+                Sim provides an intuitive drag-and-drop canvas where developers can build complex AI
+                agent workflows visually. The platform supports sophisticated agent architectures,
+                including multi-agent systems, conditional logic, loops, and parallel execution
+                paths. Additionally, Sim's built-in AI Copilot can assist you directly in the
+                editor, helping you build and modify workflows faster with intelligent suggestions
+                and explanations.
+              </p>
+
+              <figure className='my-8 overflow-hidden rounded-lg'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/sim.png'
+                  alt='Sim visual workflow builder with AI agent blocks'
+                  width={800}
+                  height={450}
+                  className='w-full'
+                />
+                <figcaption className='sr-only'>
+                  Sim drag-and-drop AI agent workflow builder canvas
+                </figcaption>
+              </figure>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                AI Copilot for Workflow Building
+              </h4>
+              <p className='mb-6 text-[19px] text-gray-800 leading-relaxed'>
+                Sim includes an intelligent in-editor AI assistant that helps you build and edit
+                workflows faster. Copilot can explain complex concepts, suggest best practices, and
+                even make changes to your workflow when you approve them. Using the @ context menu,
+                you can reference workflows, blocks, knowledge bases, documentation, templates, and
+                execution logs—giving Copilot the full context it needs to provide accurate,
+                relevant assistance. This dramatically accelerates workflow development compared to
+                building from scratch.
+              </p>
+
+              <figure className='my-8 overflow-hidden rounded-lg'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/copilot.png'
+                  alt='Sim AI Copilot assisting with workflow development'
+                  width={800}
+                  height={450}
+                  className='w-full'
+                />
+                <figcaption className='sr-only'>
+                  Sim AI Copilot in-editor assistant for workflow building
+                </figcaption>
+              </figure>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Pre-Built Workflow Templates
+              </h4>
+              <p className='mb-6 text-[19px] text-gray-800 leading-relaxed'>
+                Get started quickly with Sim's extensive library of pre-built workflow templates.
+                Browse templates across categories like Marketing, Sales, Finance, Support, and
+                Artificial Intelligence. Each template is a production-ready workflow you can
+                customize for your needs, saving hours of development time. Templates are created by
+                the Sim team and community members, with popularity ratings and integration counts
+                to help you find the right starting point.
+              </p>
+
+              <figure className='my-8 overflow-hidden rounded-lg'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/templates.png'
+                  alt='Sim workflow templates gallery'
+                  width={800}
+                  height={450}
+                  className='w-full'
+                />
+                <figcaption className='sr-only'>
+                  Sim pre-built workflow templates library
+                </figcaption>
+              </figure>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                80+ Built-in Integrations
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Out of the box, Sim connects with 80+ services including multiple AI providers
+                (OpenAI, Anthropic, Google, Groq, Cerebras, local Ollama models), communication
+                tools (Gmail, Slack, Teams, Telegram, WhatsApp), productivity apps (Notion, Google
+                Sheets, Airtable, Monday.com), and developer tools (GitHub, GitLab).
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Multiple Trigger Options
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Unlike AgentKit, Sim workflows can be triggered in multiple ways: chat interfaces,
+                REST APIs, webhooks, scheduled jobs, or external events from integrated services
+                like Slack and GitHub. This flexibility ensures your agents can be activated however
+                your use case demands.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Real-Time Team Collaboration
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Sim enables multiple team members to work simultaneously on the same workflow with
+                real-time editing, commenting, and comprehensive permissions management. This makes
+                it ideal for teams building complex agent systems together.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Advanced Agent Capabilities
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                The platform includes specialized blocks for AI agents, RAG (Retrieval-Augmented
+                Generation) systems, function calling, code execution, data processing, and
+                evaluation. These purpose-built components enable developers to create sophisticated
+                agentic workflows without custom coding.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Intelligent Knowledge Base with Vector Search
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Sim's native knowledge base goes far beyond simple document storage. Powered by
+                pgvector, it provides semantic search that understands meaning and context, not just
+                keywords. Upload documents in multiple formats (PDF, Word, Excel, Markdown, and
+                more), and Sim automatically processes them with intelligent chunking, generates
+                vector embeddings, and makes them instantly searchable. The knowledge base supports
+                natural language queries, concept-based retrieval, multi-language understanding, and
+                configurable chunk sizes (100-4,000 characters). This makes building RAG agents
+                straightforward—your AI can search through your organization's knowledge with
+                context-aware precision.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Comprehensive Execution Logging and Monitoring
+              </h4>
+              <p className='mb-6 text-[19px] text-gray-800 leading-relaxed'>
+                Sim provides enterprise-grade logging that captures every detail of workflow
+                execution. Track workflow runs with execution IDs, view block-level logs with
+                precise timing and duration metrics, monitor token usage and costs per execution,
+                and debug failures with detailed error traces and trace spans. The logging system
+                integrates with Copilot—you can reference execution logs directly in your Copilot
+                conversations to understand what happened and troubleshoot issues. This level of
+                observability is essential for production AI agents where understanding behavior and
+                debugging issues quickly is critical.
+              </p>
+
+              <figure className='my-8 overflow-hidden rounded-lg'>
+                <Image
+                  src='/building/openai-vs-n8n-vs-sim/logs.png'
+                  alt='Sim execution logs and monitoring dashboard'
+                  width={800}
+                  height={450}
+                  className='w-full'
+                />
+                <figcaption className='sr-only'>
+                  Sim execution logs dashboard with detailed workflow monitoring
+                </figcaption>
+              </figure>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Custom Integrations via MCP Protocol
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Beyond the 80+ built-in integrations, Sim supports the Model Context Protocol (MCP),
+                allowing developers to create custom integrations for proprietary systems or
+                specialized tools.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Flexible Deployment Options
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Sim offers both cloud-hosted and self-hosted deployment options. Organizations can
+                run Sim on their own infrastructure for complete control, or use the managed cloud
+                service for simplicity. The platform is SOC2 and HIPAA compliant, ensuring
+                enterprise-level security.
+              </p>
+
+              <h4 className='mt-4 mb-2 font-medium text-[19px] leading-tight'>
+                Production-Ready Infrastructure
+              </h4>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                The platform includes everything needed for production deployments: background job
+                processing, webhook handling, monitoring, and API management. Workflows can be
+                published as REST API endpoints, embedded via SDKs, or run through chat interfaces.
+              </p>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>
+                What You Can Build with Sim
+              </h3>
+              <ul className='mb-4 ml-6 list-disc text-[19px] text-gray-800 leading-relaxed'>
+                <li className='mb-2'>
+                  <strong>AI Assistants & Chatbots:</strong> Intelligent agents that search the web,
+                  access calendars, send emails, and interact with business tools
+                </li>
+                <li className='mb-2'>
+                  <strong>Business Process Automation:</strong> Automate repetitive tasks like data
+                  entry, report generation, customer support, and content creation
+                </li>
+                <li className='mb-2'>
+                  <strong>Data Processing & Analysis:</strong> Extract insights from documents,
+                  analyze datasets, generate reports, and sync data between systems
+                </li>
+                <li className='mb-2'>
+                  <strong>API Integration Workflows:</strong> Connect multiple services into unified
+                  endpoints and orchestrate complex business logic
+                </li>
+                <li className='mb-2'>
+                  <strong>RAG Systems:</strong> Build sophisticated retrieval-augmented generation
+                  pipelines with custom knowledge bases
+                </li>
+              </ul>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>
+                Drawbacks to Consider
+              </h3>
+              <p className='mb-2 text-[19px] text-gray-800 leading-relaxed'>
+                While Sim excels at AI agent workflows, there are some tradeoffs:
+              </p>
+              <ul className='mb-4 ml-6 list-disc text-[19px] text-gray-800 leading-relaxed'>
+                <li className='mb-2'>
+                  Fewer pre-built integrations compared to n8n's extensive library—though Sim's 80+
+                  integrations cover most AI agent use cases and MCP protocol enables custom
+                  integrations
+                </li>
+              </ul>
+            </section>
+
+            {/* Comparison Section */}
+            <section className='mb-12'>
+              <h2 className='mb-4 font-medium text-[28px] leading-tight sm:text-[32px]'>
+                Key Differences
+              </h2>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                While all three platforms enable AI agent development, they excel in different
+                areas:
+              </p>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>OpenAI AgentKit</h3>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                <strong>Best for:</strong> Teams deeply invested in the OpenAI ecosystem who
+                prioritize evaluation and testing capabilities. Ideal when you need tight
+                integration with OpenAI's latest models and want built-in prompt optimization and
+                evaluation tools.
+              </p>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                <strong>Limitations:</strong> Locked into OpenAI models only, not open-source, no
+                workflow templates or execution logs, limited triggering options, and fewer
+                out-of-the-box integrations.
+              </p>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>n8n</h3>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                <strong>Best for:</strong> Traditional workflow automation with some AI enhancement.
+                Excellent when your primary need is connecting business tools and services, with AI
+                as a complementary feature rather than the core focus.
+              </p>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                <strong>Limitations:</strong> No SDK for programmatic workflow building, fair-use
+                licensing (not fully open source), 14-day trial limitation, and AI agent
+                capabilities are newer and less mature compared to its traditional automation
+                features.
+              </p>
+
+              <h3 className='mt-6 mb-3 font-medium text-[22px] leading-tight'>Sim</h3>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                <strong>Best for:</strong> Building production-ready AI agent workflows that require
+                flexibility, collaboration, and comprehensive tooling. Ideal for teams that need AI
+                Copilot assistance, advanced knowledge base features, detailed logging, and the
+                ability to work across multiple AI providers with purpose-built agentic workflow
+                tools.
+              </p>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                <strong>Limitations:</strong> Fewer integrations than n8n's extensive library,
+                though the 80+ built-in integrations and MCP protocol support cover most AI agent
+                needs.
+              </p>
+            </section>
+
+            {/* Conclusion */}
+            <section className='mb-12'>
+              <h2 className='mb-4 font-medium text-[28px] leading-tight sm:text-[32px]'>
+                Which Should You Choose?
+              </h2>
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                The right platform depends on your specific needs and context:
+              </p>
+
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Choose <strong>OpenAI AgentKit</strong> if you're exclusively using OpenAI models
+                and want to build chat interfaces with the ChatKit. It's a solid choice for teams
+                that want to stay within OpenAI's ecosystem and prioritize testing capabilities.
+              </p>
+
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Choose <strong>n8n</strong> if your primary use case is traditional workflow
+                automation between business tools, with occasional AI enhancement. It's ideal for
+                organizations already familiar with n8n who want to add some AI capabilities to
+                existing automations.
+              </p>
+
+              <p className='mb-4 text-[19px] text-gray-800 leading-relaxed'>
+                Choose <strong>Sim</strong> if you're building AI agents as your primary objective
+                and need a platform purpose-built for that use case. Sim provides the most
+                comprehensive feature set for agentic workflows, with AI Copilot to accelerate
+                development, parallel execution handling, intelligent knowledge base for RAG
+                applications, detailed execution logging for production monitoring, flexibility
+                across AI providers, extensive integrations, team collaboration, and deployment
+                options that scale from prototype to production.
+              </p>
+            </section>
+          </div>
+        </div>
+
+        {/* Publisher information for schema */}
+        <meta itemProp='publisher' content='Sim' />
+        <meta itemProp='inLanguage' content='en-US' />
+        <meta
+          itemProp='keywords'
+          content='AI agents, OpenAI AgentKit, n8n, Sim, workflow automation'
+        />
+      </article>
+    </>
+  )
+}

apps/sim/app/(landing)/building/openai-vs-n8n-vs-sim/page.tsx

@@ -0,0 +1,139 @@
+import type { Metadata } from 'next'
+import OpenAiN8nSim from './openai-n8n-sim'
+
+const baseUrl = 'https://sim.ai'
+const canonicalUrl = `${baseUrl}/building/openai-vs-n8n-vs-sim`
+
+export const metadata: Metadata = {
+  title: 'OpenAI AgentKit vs n8n vs Sim: AI Agent Workflow Builder Comparison | Sim',
+  description:
+    'Compare OpenAI AgentKit, n8n, and Sim for building AI agent workflows. Explore key differences in capabilities, integrations, collaboration, and which platform best fits your production AI agent needs.',
+  keywords: [
+    'AgentKit',
+    'AI agents',
+    'AI agent development',
+    'agents',
+    'workflow builder',
+    'visual workflow builder',
+    'workflows',
+    'OpenAI AgentKit',
+    'OpenAI',
+    'OpenAI Responses API',
+    'n8n',
+    'n8n workflow automation',
+    'AI workflow automation',
+    'workflow automation platform',
+    'Sim',
+    'agent builder comparison',
+    'RAG agents',
+    'RAG systems',
+    'retrieval augmented generation',
+    'ChatKit',
+    'agent evaluation',
+    'prompt optimization',
+    'multi-agent systems',
+    'team collaboration workflows',
+    'production AI agents',
+    'AI guardrails',
+    'workflow integrations',
+    'self-hosted AI agents',
+    'cloud AI agent platform',
+    'MCP protocol',
+    'Model Context Protocol',
+    'knowledge base integration',
+    'vector embeddings',
+    'AI agent canvas',
+    'agentic workflows',
+    'AI agent API',
+    'AI chatbot workflows',
+    'business process automation',
+    'AI Copilot',
+    'workflow copilot',
+    'AI assistant for workflows',
+    'vector search',
+    'semantic search',
+    'pgvector',
+    'knowledge base AI',
+    'document embeddings',
+    'execution logging',
+    'workflow monitoring',
+    'AI agent observability',
+    'workflow debugging',
+    'execution traces',
+    'AI workflow logs',
+    'intelligent chunking',
+    'context-aware search',
+  ],
+  authors: [{ name: 'Emir Karabeg', url: 'https://x.com/karabegemir' }],
+  creator: 'Emir Karabeg',
+  publisher: 'Sim',
+  robots: {
+    index: true,
+    follow: true,
+    googleBot: {
+      index: true,
+      follow: true,
+      'max-video-preview': -1,
+      'max-image-preview': 'large',
+      'max-snippet': -1,
+    },
+  },
+  alternates: {
+    canonical: canonicalUrl,
+  },
+  openGraph: {
+    title: 'OpenAI AgentKit vs n8n vs Sim: AI Agent Workflow Builder Comparison',
+    description:
+      'Compare OpenAI AgentKit, n8n, and Sim for building AI agent workflows. Explore key differences in capabilities, integrations, and which platform fits your production needs.',
+    url: canonicalUrl,
+    siteName: 'Sim',
+    locale: 'en_US',
+    type: 'article',
+    publishedTime: '2025-10-06T00:00:00.000Z',
+    modifiedTime: '2025-10-06T00:00:00.000Z',
+    authors: ['Emir Karabeg'],
+    section: 'Technology',
+    tags: [
+      'AI Agents',
+      'Workflow Automation',
+      'OpenAI AgentKit',
+      'n8n',
+      'Sim',
+      'AgentKit',
+      'AI Development',
+      'RAG',
+      'MCP Protocol',
+    ],
+    images: [
+      {
+        url: `${baseUrl}/building/openai-vs-n8n-vs-sim/workflow.png`,
+        width: 1200,
+        height: 630,
+        alt: 'Sim AI agent workflow builder interface comparison',
+      },
+    ],
+  },
+  twitter: {
+    card: 'summary_large_image',
+    title: 'OpenAI AgentKit vs n8n vs Sim: AI Agent Workflow Builder Comparison',
+    description:
+      'Compare OpenAI AgentKit, n8n, and Sim for building AI agent workflows. Explore key differences in capabilities, integrations, and which platform fits your production needs.',
+    images: ['/building/openai-vs-n8n-vs-sim/workflow.png'],
+    creator: '@karabegemir',
+    site: '@simai',
+  },
+  other: {
+    'article:published_time': '2025-10-06T00:00:00.000Z',
+    'article:modified_time': '2025-10-06T00:00:00.000Z',
+    'article:author': 'Emir Karabeg',
+    'article:section': 'Technology',
+  },
+}
+
+/**
+ * Blog post page comparing OpenAI AgentKit, n8n, and Sim workflow builders for AI agents.
+ * Optimized for SEO with structured data, canonical URLs, and comprehensive metadata.
+ */
+export default function Page() {
+  return <OpenAiN8nSim />
+}

apps/sim/app/(landing)/building/page.tsx

@@ -0,0 +1,8 @@
+import { redirect } from 'next/navigation'
+
+/**
+ * Redirects /building to the latest blog post
+ */
+export default function BuildingPage() {
+  redirect('/building/openai-vs-n8n-vs-sim')
+}

apps/sim/app/(landing)/components/nav/nav.tsx

@@ -20,7 +20,7 @@ interface NavProps {
 }
 
 export default function Nav({ hideAuthButtons = false, variant = 'landing' }: NavProps = {}) {
-  const [githubStars, setGithubStars] = useState('15.4k')
+  const [githubStars, setGithubStars] = useState('16.3k')
   const [isHovered, setIsHovered] = useState(false)
   const [isLoginHovered, setIsLoginHovered] = useState(false)
   const router = useRouter()

apps/sim/app/layout.tsx

@@ -1,11 +1,10 @@
-import { Analytics } from '@vercel/analytics/next'
 import type { Metadata, Viewport } from 'next'
 import { PublicEnvScript } from 'next-runtime-env'
 import { BrandedLayout } from '@/components/branded-layout'
 import { generateThemeCSS } from '@/lib/branding/inject-theme'
 import { generateBrandedMetadata, generateStructuredData } from '@/lib/branding/metadata'
-import { isHosted } from '@/lib/environment'
 import { createLogger } from '@/lib/logs/console/logger'
+import { PostHogProvider } from '@/lib/posthog/provider'
 import '@/app/globals.css'
 
 import { SessionProvider } from '@/lib/session/session-context'
@@ -55,7 +54,6 @@ export const viewport: Viewport = {
   ],
 }
 
-// Generate dynamic metadata based on brand configuration
 export const metadata: Metadata = generateBrandedMetadata()
 
 export default function RootLayout({ children }: { children: React.ReactNode }) {
@@ -91,19 +89,16 @@ export default function RootLayout({ children }: { children: React.ReactNode })
         <PublicEnvScript />
       </head>
       <body suppressHydrationWarning>
-        <ThemeProvider>
-          <SessionProvider>
-            <BrandedLayout>
-              <ZoomPrevention />
-              {children}
-              {isHosted && (
-                <>
-                  <Analytics />
-                </>
-              )}
-            </BrandedLayout>
-          </SessionProvider>
-        </ThemeProvider>
+        <PostHogProvider>
+          <ThemeProvider>
+            <SessionProvider>
+              <BrandedLayout>
+                <ZoomPrevention />
+                {children}
+              </BrandedLayout>
+            </SessionProvider>
+          </ThemeProvider>
+        </PostHogProvider>
       </body>
     </html>
   )

apps/sim/app/sitemap.ts

@@ -37,8 +37,18 @@ export default function sitemap(): MetadataRoute.Sitemap {
     },
   ]
 
+  // Blog posts and content pages
+  const blogPages = [
+    {
+      url: `${baseUrl}/building/openai-vs-n8n-vs-sim`,
+      lastModified: new Date('2025-10-06'),
+      changeFrequency: 'monthly' as const,
+      priority: 0.9,
+    },
+  ]
+
   // You can add dynamic pages here by fetching from database
   // const dynamicPages = await fetchDynamicPages()
 
-  return [...staticPages]
+  return [...staticPages, ...blogPages]
 }

apps/sim/instrumentation-client.ts

@@ -5,34 +5,7 @@
  * It respects the user's telemetry preferences stored in localStorage.
  *
  */
-import posthog from 'posthog-js'
-import { env, getEnv, isTruthy } from './lib/env'
-
-// Initialize PostHog only if explicitly enabled
-if (isTruthy(getEnv('NEXT_PUBLIC_POSTHOG_ENABLED')) && getEnv('NEXT_PUBLIC_POSTHOG_KEY')) {
-  posthog.init(getEnv('NEXT_PUBLIC_POSTHOG_KEY')!, {
-    api_host: '/ingest',
-    ui_host: 'https://us.posthog.com',
-    person_profiles: 'identified_only',
-    capture_pageview: true,
-    capture_pageleave: true,
-    capture_performance: true,
-    session_recording: {
-      maskAllInputs: false,
-      maskInputOptions: {
-        password: true,
-        email: false,
-      },
-      recordCrossOriginIframes: false,
-      recordHeaders: true,
-      recordBody: true,
-    },
-    autocapture: true,
-    capture_dead_clicks: true,
-    persistence: 'localStorage+cookie',
-    enable_heatmaps: true,
-  })
-}
+import { env } from './lib/env'
 
 if (typeof window !== 'undefined') {
   const TELEMETRY_STATUS_KEY = 'simstudio-telemetry-status'

apps/sim/lib/posthog/provider.tsx

@@ -0,0 +1,41 @@
+'use client'
+
+import { useEffect } from 'react'
+import posthog from 'posthog-js'
+import { PostHogProvider as PHProvider } from 'posthog-js/react'
+import { getEnv, isTruthy } from '../env'
+
+export function PostHogProvider({ children }: { children: React.ReactNode }) {
+  useEffect(() => {
+    const posthogEnabled = getEnv('NEXT_PUBLIC_POSTHOG_ENABLED')
+    const posthogKey = getEnv('NEXT_PUBLIC_POSTHOG_KEY')
+
+    if (isTruthy(posthogEnabled) && posthogKey && !posthog.__loaded) {
+      posthog.init(posthogKey, {
+        api_host: '/ingest',
+        ui_host: 'https://us.posthog.com',
+        defaults: '2025-05-24',
+        person_profiles: 'identified_only',
+        capture_pageview: true,
+        capture_pageleave: true,
+        capture_performance: true,
+        session_recording: {
+          maskAllInputs: false,
+          maskInputOptions: {
+            password: true,
+            email: false,
+          },
+          recordCrossOriginIframes: false,
+          recordHeaders: true,
+          recordBody: true,
+        },
+        autocapture: true,
+        capture_dead_clicks: true,
+        persistence: 'localStorage+cookie',
+        enable_heatmaps: true,
+      })
+    }
+  }, [])
+
+  return <PHProvider client={posthog}>{children}</PHProvider>
+}