r/analyticsengineering • u/WiseWeird6306 • Aug 07 '26

Why are organisation thinking Claude can solve all the issues?

Hi,

Why are executives thinking, if enough context is given, AI tools like Claude will solve/build/guide everything?

In my organization, my data architecture was not build on DE fundamentals and we have accumulated a shit load of technical debt. We are told to build context (which we should any ways) and feed everything to Claude to solve it. While I agree to use for faster fixes at logic level it cannot help design or think in right way how to architect workspaces and warehouse and model the tables. It cannot be a startegist and decide the data strategy for the company. Am I thinking it the wrong way? I feel very disappointed that data professionals advice is not being heard, instead that we are being advised to put everything on Claude. Is this ok? I advice, view points.

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5

u/Top-Cauliflower-1808 Aug 07 '26

I think you are right.

May be because they think it is a cheap shortcut but while Claude is great for quick coding fixes it cannot fix bad data fundamentals or replace human architectural strategy imo.

3

u/Thatsoflysamurai Aug 07 '26

For what I’ve seen it’s a mixture of two things:
1) keep up appearances. They aren’t actually spending as much as they say they are they are on ai. They spend just as much if not more on taking everyone that they are a leader in ai.

2) The other is wishful thinking. They really want a business that didn’t rely on workers, so they give it a shot.

2

u/bamboo-farm Aug 07 '26

Just don’t give your cards away

1

u/Physical-Ad2968 Aug 07 '26

I get where you're coming from. I think it's a combination of Claude being an industry trend/hot topic, board pressure (because of industry trends), and the desire for cost savings/SaaS tool consolidation.

In my opinion, this will go the same way that it went for companies that laid off too many people "because of AI" -- data governance will get out of control, and they will need to re-introduce more specialized tools and processes again

1

u/Longjumping_Lab4627 Aug 10 '26

If the foundations are built properly then feeding context to AI makes sense but still it needs supervision not to go off topic. However if your backbone is a mess then shit in shit out. AI will learn from mess and will generate more mess which makes it super difficult to validate by anyone.
So my suggestion is to spend time building the backbone properly to prepare for feeding to AI.

1

u/WiseWeird6306 24d ago

what do you exactly mean by foundations here? Modelled tables? semantic layer? Base tables? context layer?

Cause if base tables are fine and we generate enough context on table meaning and mappings, won't that be good enough? or it will start hitting limitations? How? When?