Dave Ebbelaar's recommended five-layer AI automation stack for 2026
Dave Ebbelaar, AI engineer and founder of Datalumina, breaks down the five-layer stack he recommends for AI automation in 2026: backend, database, frontend, AI models, and deployment infrastructure.
Score breakdown
The stack is framed as a direct map to real job requirements in AI engineering, contrasting with no-code automation tools that Ebbelaar argues employers do not list as prerequisites.
- 01The stack is organized into five layers: backend, database, frontend, AI models, and deployment infrastructure.
- 02Backend layer uses Python, FastAPI, and Celery.
- 03Database layer uses Postgres and Supabase.
Dave Ebbelaar, who describes himself as an AI engineer and founder of Datalumina with a bachelor's and master's degree in AI, presents what he calls a "lasting stack" built across five layers: backend, database, frontend, AI models, and deployment infrastructure. His central argument is that no-code and low-code automation tools are unlikely to appear as job requirements, whereas the underlying engineering skills — building a backend, working with a database, deploying infrastructure — are what employers actually seek.
The backend layer is anchored by Python as the core language, with FastAPI and Celery as the two additional packages he specifically highlights.
The backend layer is anchored by Python as the core language, with FastAPI and Celery as the two additional packages he specifically highlights. The database layer uses Postgres and Supabase, the frontend stack uses React, Vite, and ShadCN UI for building dashboards, internal tools, and APIs. The AI model layer is accessed through API calls to providers such as OpenAI, Anthropic, AWS, Azure, and Google Cloud, covering language models, embeddings, vision, speech, and image generation. For infrastructure, the video covers Docker, Railway, VPS deployment, and cloud hosting. Ebbelaar also mentions sharing a complete project codebase containing all five layers for viewers to clone and reverse-engineer.
Key facts
- 01The stack is organized into five layers: backend, database, frontend, AI models, and deployment infrastructure.
- 02Backend layer uses Python, FastAPI, and Celery.
- 03Database layer uses Postgres and Supabase.
- 04Frontend stack uses React, Vite, and ShadCN UI.
- 05AI model layer covers language models, embeddings, vision, speech, and image generation via APIs from OpenAI, Anthropic, AWS, Azure, and Google Cloud.
- 06Infrastructure options include Docker, Railway, VPS deployment, and cloud hosting.
- 07Ebbelaar offers a complete project codebase with all five layers for viewers to clone and reverse-engineer.
Topics
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