AI-Augmented Data Engineering, with Maksym Karashchuk

No Hallucinations: AI That Ships

AI-Augmented Data Engineering, with Maksym Karashchuk

2 de jun. de 2026 · 29m 51s

Capítulos

01 · Show intro and the five stages of AI in a data team

1m 24s

02 · Why organisations slow down on adoption

3m 5s

03 · Maksym's day now versus a year ago

3m 51s

04 · Real agent examples: recordings vault, auto-documentation, the Azure DevOps loop

5m 7s

05 · Human in the loop: the engineer verifies the pull request

7m 4s

06 · The first time a machine opened the pull request for you

7m 58s

07 · Adoption among peers and the blockers

8m 40s

08 · Information overload and European governance on model inference

10m 50s

09 · The guess machine: what you cannot trust an LLM with

12m 56s

10 · Moving from wave one to wave two

13m 40s

11 · Organisational readiness, BPMN, humans-with-agents versus agents-with-humans

14m 15s

12 · The data warehouse homework an agent needs

15m 56s

13 · Infrastructure, backend, and frontend as code

16m 32s

14 · Generating project rules, garbage in garbage out

17m 24s

15 · Where to store rules: Markdown and token economics

18m 41s

16 · RAG versus Markdown, and why the vector database hallucinates more

19m 47s

17 · Version control for the knowledge base

21m 36s

18 · Treat rules like an architecture decision record

22m 13s

19 · The role shift: from code repository to knowledge base and agents

23m 23s

20 · Eighteen months out

24m 22s

21 · Better models or better processes, and running Sonnet 4.6

25m 51s

22 · Advice to data engineers: touch the technology, mind security

27m 4s

23 · Will the data engineer job exist in ten years

28m 29s

24 · Outro

29m 27s

Descripción

A data architect who builds agents every week gives an honest read on what AI is doing to the data engineering job. The job is not disappearing but it is...

mostra más

A data architect who builds agents every week gives an honest read on what AI is doing to the data engineering job. The job is not disappearing but it is shifting: from writing code by hand to curating the rules, skills, and knowledge base that agents run on. As the LLMs are becoming commodity, the bottleneck in 2026 transitions form being a top model quality to the correctly built processes.

mostra menos

Comentarios

Inicia sesión para dejar un comentario

Información

Autor	Astral Forest
Organización	Astral Forest
Página web	-
Etiquetas	#ai #analytics #architecture #astral forest #cdo #data #data leadership #datalake #datawarehouse #engineering #model #no hallucinations #podcast #reporting #technology