Building an Automated Video Transfer Workflow with No-Code Tools and AI
Building an Automated Video Transfer Workflow with No-Code Tools and AI
I’d been experimenting with Make for workflow automation whilst building VisaScope AI, and it got me thinking about a client problem that was being quoted for custom development. Could I solve it using no-code solutions? I set out to build a prototype automated workflow using existing architecture and third-party products.
The client had chosen a VOD platform for their perpetual membership viewing library that wasn’t connected to their awards management platform. Their challenge was importing video content and metadata, but because of the lack of integration this was being completed manually. With 100+ videos daily during peak periods, each one required manual intervention—download from the source platform, upload to the VOD service, manually copy across all the metadata (titles, descriptions, credits), then verify everything matched.
For this workflow, I identified five critical components: email monitoring to capture approval notifications, authentication handling for API access, data processing to map metadata between platforms, secure file transfer to the VOD service, and robust error management.
The authentication piece was the most complex. The source platform requires precise HMAC-SHA256 signatures that Make couldn’t generate natively. This is where working with AI tools became an invaluable support network. I used ChatGPT and Claude to understand the HMAC requirements, design the authentication flow, and build a lightweight PHP endpoint to handle signature generation. ChatGPT had the breakthrough on the authentication approach, helping me structure the solution that would enable the broader no-code automation.
Working entirely on my own using Make and AI assistance, I built the workflow in stages to validate each component before adding complexity. The approach was deliberately modular—if any piece failed, I could isolate and fix it without starting over.
AI tools helped me:
– Understand complex API authentication requirements
– Write the PHP authentication endpoint
– Debug regex patterns for email processing
– Structure the Make workflow logic
The breakthrough came from treating this as a product problem rather than a technical challenge. Instead of asking “how do we code this,” I asked “what’s the minimum viable integration that eliminates manual work?”
The working prototype now processes each video in seconds and successfully handles the complete transfer workflow without manual intervention. It eliminates manual video transfers, achieves error-free metadata consistency, and demonstrates that complex enterprise integrations can be built by product managers using no-code tools and AI—without requiring traditional development resources.
Custom development would have delivered a robust solution, but it would have required developer resources, created maintenance dependencies, and taken considerably longer to implement. By combining no-code automation tools with AI assistance, I built a working prototype that proves the concept whilst creating a flexible foundation for future enhancements.
The key insight is that product managers can now solve technical problems that previously required development teams. AI tools bridge the knowledge gap—helping you understand authentication protocols, write necessary code snippets, and debug complex workflows—whilst Make handles the orchestration.
This project proved that the role of product manager is evolving. With the right combination of no-code tools and AI assistance, we can:
– Build working prototypes without development teams
– Validate technical approaches rapidly
– Solve complex integration challenges independently
– Demonstrate business value before committing to full development
The prototype demonstrates what’s possible when product managers combine automation tools with AI assistance. It’s a proof of concept that shows this approach can handle enterprise-scale complexity.
This experience shaped my approach at Product Scope. I now help clients identify where intelligent automation and AI assistance can solve business problems that they’re considering expensive development for. The combination of no-code tools, AI support, and product thinking creates opportunities that weren’t possible even a year ago.
For organisations facing similar integration challenges, the lesson is clear: explore what’s possible with no-code automation and AI assistance before committing to traditional development. You might be surprised at what a skilled product manager can build independently.
