add real images

Author: jharrell

content/800-guides/100-build-a-video-processing-pipeline.mdx

@@ -3,7 +3,7 @@ title: 'Build a Video Processing Pipeline'
 metaTitle: 'Build a Video Processing Pipeline with Prisma Pulse and Trigger.dev'
 description: 'Learn how to build a scalable video processing pipeline using a decoupled, event-driven architecture with Prisma Pulse and Trigger.dev.'
 sidebar_label: 'Video Processing Pipeline'
-
+image: '/img/guides/video-processing-pipeline-cover.svg'
 ---
 
 Serverless computing enables applications to scale efficiently, supporting millions of users. However, it faces challenges with longer runtimes and intensive data processing, both of which are crucial for machine learning (ML) applications. To address this, tools like Pulse and Trigger.dev assist developers in creating decoupled, event-driven workflows, facilitating efficient handling of complex tasks.
@@ -25,7 +25,7 @@ These benefits make decoupled, event-driven architectures an ideal choice for mo
 
 To demonstrate how you can apply this architecture, let's build a video transcribing workflow using [Pulse](https://www.prisma.io/pulse) and [Trigger.dev](https://trigger.dev). We'll create a system that transcribes a video from a URL and stores the transcription in a database.
 
-![Pulse and Trigger.dev Flow](https://www.prisma.io/blog/assets/pulse-trigger-workflow.png)
+![Pulse and Trigger.dev Flow](/img/guides/pulse-trigger-workflow.png)
 
 ### Defining the Data Model
 

content/800-guides/200-build-real-time-durable-workflows.mdx

@@ -3,6 +3,7 @@ title: 'Build Real-Time Durable Workflows'
 metaTitle: 'Build Real-Time, Durable Workflows with Pulse and Inngest'
 metaDescription: 'Learn how to create real-time, durable, and extensible workflows using Prisma Pulse and Inngest.'
 sidebar_label: 'Real-Time Durable Workflows'
+image: '/img/guides/real-time-durable-workflows-cover.svg'
 ---
 
 Building web applications today isn't just about functionality—it's about creating seamless and engaging user experiences. Users expect applications to be responsive, real-time, and feature-rich, handling ever-increasing data sets efficiently.