I'm quite interested by the current trends about no code / low code GenAI :
- Models are becoming more versatile and multimodal = They can ingest almost any type of content / data
- Auto-embedding and Auto-RAG features are becoming better and more accessible (GPT Builder, "Projects" from Anthropic...), reducing the need for AI engineering, and with less and less limitations on the type and quantity of content that can be added
- Fine-tuning can be done directly by myself, the meta-prompts is added to the "AI assistant" with standard features
At the same time, I feel a lot of companies are still organizing their "GenAI Engineering" capabilities , still upskilling, trying not to get outrun by the fast pace of innovation & the obsolescence of some products or approaches, and with the growing demand from the users, the bottleneck is getting bigger.
So, my feeling is we'll see more and more use cases fully covered by standard features and less and less work for AI Architect and AI Engineers, with the exception of complex ecosystem integration,, agentic on complex processes, specific requirements like real time, high number of people etc.
What do you think? What's the future of AI Architecture & Engineering?
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