Duraid Wadie

Head of M&A Architecture

Medium Article · 2 min read · Feb 25, 2022

The Systems Got Smarter, But the Orchestration Got Real

AIArchitectureDevOpsDecision MakingAPIObservabilityOpenAIArchitects

Article summary

The Systems Got Smarter, But the Orchestration Got Real We used to think the hardest part of integrating AI was the model. By February 2022, we knew better. The hardest part was orchestration. Not just moving data to and from models, but embedding models in human systems without making a mess. The biggest shift wasn’t intelligence. It was context. Fine-tuned transformers were becoming easier to deploy. Tools like Hugging Face made model hosting approachable. But none of that mattered if the model didn’t know what you were asking. Prompt engineering had become a core skill. We watched engineers spend more time tuning input phrasing than writing code. That’s when we realized: the model isn’t the product. The interface is. And architecture had to center on flows-not endpoints. We stopped drawing AI as boxes. We started drawing it as loops.

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Practical takeaway

The main idea behind The Systems Got Smarter, But the Orchestration Got Real is to help teams move from broad theory to clear, repeatable decision making. When teams apply this thinking, they reduce ambiguity and focus on improvements that deliver measurable momentum.

Example scenario

Imagine a team facing competing priorities. By applying the ideas in The Systems Got Smarter, But the Orchestration Got Real, they can map dependencies, identify risks and choose the next move that produces progress without destabilizing their system.

Common mistakes to avoid

How to apply this in real work

Start by identifying where The Systems Got Smarter, But the Orchestration Got Real already shows up in your architecture or delivery flow. Then pick one area where clarity would reduce friction. Apply the idea, measure its effect and share the learning.

Signs you are doing it correctly

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