The text discusses the challenges and solutions associated with building engine-agnostic data stacks, which allow data teams to utilize multiple processing tools like Spark, DuckDB, and Snowflake without being constrained by vendor-specific ecosystems. Iceberg addresses the issue of storage by enabling reliable shared data access across different engines with features such as ACID transactions and multi-engine coordination. However, it does not solve the problem of code portability, which is where tools like Ibis come into play, allowing analytical code to be written once and executed across various platforms. This decoupling of data and code from specific compute engines provides flexibility, letting teams choose the best tool for each task and reducing the time spent on integration and maintenance. The trend towards engine-agnostic solutions is driven by the need for flexibility and efficiency, as more vendors adopt Iceberg support and tools like Ibis expand their backend coverage.