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AI agents are starting to earn a real place in continuous integration pipelines: reviewing diffs, proposing fixes, generating missing tests. Six months of real-world use to separate the patterns that work from the ones that end up costing more time than they save.
Semgrep has grown into one of the most pragmatic static analyzers in the ecosystem. A look at why it works where other SAST tools fail, and how to fit it into a pipeline without turning it into noise.
Spark DataFrames are distributed, schema-based tables that the Catalyst engine optimises automatically, while pipelines chain those transformations into a reproducible end-to-end flow. Together they let you process large data volumes efficiently across a cluster, scaling from a laptop to hundreds of nodes without rewriting code.
