Has anyone else noticed that the hardest part of building agent workflows isn't the model anymore?

Reddit r/AI_Agents News

Summary

A developer observes that the biggest challenge in building agent workflows has shifted from models and prompts to maintaining context, business rules, and external data synchronization, and asks the community about their primary bottleneck.

A year ago most of my time was spent trying different models and prompts. Now it feels like the real challenge is keeping context, business rules, and external data synchronized without creating a maintenance nightmare. Curious what others see as the biggest bottleneck today: Tool reliability Context management Evaluation/testing User trust Something else entirely Interested in hearing what's causing the most friction in real world deployments.
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