The new Claude 4.6 "Agent Teams" feature finally solves "Context Rot" in massive data migrations. Unlike previous models that lose the plot halfway through a dbt project, these agents use "compaction" to summarize their own context and spin up fresh "teammates" for specific tasks without losing the high-level architecture. Read the full story on www.datapro.news 4.6 gives you sustained execution on long-running pipelines without hallucinating column names

Dave Ebbelaar is one of the most followed Data & AI Engineering teacher on YouTube with more than 8 million views on his channel. His free python course is well worth a look with over 250,000 views and 11k of likes there is something here for most every beginner. Find the course hand book here.

Scammers just pulled off a $16 million crypto rug pull using hijacked AI agent accounts. Meanwhile, autonomous agents are trading "weaponised skills" on dark markets, including reverse shells disguised as innocent plugins. And some are storing your API keys in plaintext Markdown files. If you're running autonomous agents in your data pipeline, watch this first:

In your own words describe what ACID means in the context of Data Engineering?

Make a case for this common-sense axiom discussed in this chapter: "Always prioritise requirements over building something cool."? Which of the Greenfield or Brownfield scenarios is it more applicable to?