Everyone loves to say AI makes creative work feel impersonal but I found the uses that actually save time without replacing my creative expertise.

Here's what's been working for me:

✍️ Copy and emails: I write the base, AI helps me polish and tighten it 🎨 Concept and moodboard copy: same approach, I write the core idea, AI helps shape the language for presentations 📦 Mockups: AI speeds up creation so I don't spend hours looking for the right .psd online

The key has been using it to speed up the boring parts so I can focus on the creative bits.

What's an AI use in your workflow that actually made things better, not just faster?

Starting with your own draft is close to how I use it on builds. I give AI the page and a short checklist, then use what it catches to tighten the work before I ship.

MyCarrier: DevOps & Cloud Transformation for Scalable Logistics SaaS

Preview description: We helped MyCarrier move toward cloud-ready DevOps: adapted the system for microservices, implemented CI/CD and test automation, moved workloads to Azure, achieved 99.9% availability, decreased update delivery time to minutes.

Full description:

Problem MyCarrier was growing fast, and the monolithic codebase became harder and more expensive to maintain. It was heavy, resource-consuming, and less suitable for the client’s long-term scaling plans. The team also needed faster delivery processes, but changes in the codebase and cloud migration had to stay unnoticed by users. Their logistics workflows could not be interrupted.

Solution IT Craft aligned the project infrastructure with a microservices architecture and prepared the system for cloud operation. The team started with a technical audit and developed the migration strategy consisting of 20-28 items. The process was divided into pre-migration, migration, and post-migration phases, thus the product could keep running while infrastructure changed step by step.

The team moved non-critical standalone jobs to the cloud, connected virtual machines to Azure Storage Account, moved logging to MongoDB Atlas, and transferred user data and related processes to the cloud. New app functionality was released as microservices. IT Craft also designed and fine-tuned a CI/CD pipeline, automated infrastructure deployments, and reduced update delivery time through regression test automation.

Results · Achieved 99.9% system availability. · Maintained high fault tolerance using three shared clusters. · Reduced update delivery time from hours to minutes. · Enabled Sprint focus changes every two weeks based on client priorities.

Tech Stack: · Azure Cloud · MongoDB Atlas · Azure SQL · Azure App Service · Azure Functions · Azure Storage Account