Iceberg Framework was created to make LLM driven workflows predictable, validated, and safe to run in real systems. But every team and developer faces different challenges when working with AI.
I m curious to hear from the community:
What problems do you struggle with when building agentic workflows?
Where do LLMs behave unpredictably in your projects?
Do you need validation, reproducibility, or auditability in your AI pipelines?
Which parts of your current AI stack feel fragile or hard to control?
What would you want Iceberg to help you with next?
Your insights will help shape the roadmap and highlight real world use cases that matter most.
Iceberg Framework introduces a rules layer for AI — something existing tools don’t provide.
Instead of generating code directly from prompts, Iceberg forces models to follow a structured process: rules → documents → code.
This eliminates behavioral drift, reduces variance, and keeps systems maintainable over time.
It works behind the scenes, adding predictable, spec‑driven behavior to any model without changing your workflow.
