Digiaeon Services Pvt Ltd logo

Insights

Notes from the part of the work nobody demos.

What we have learned building systems that have to keep answering at 3am — how to evaluate output that changes every call, how to budget inference, and why the model is rarely the thing that breaks.

The shelf

Pieces published
04
Topics covered
04
Written by
Engineers
Latest
Data & Platform Engineering19 May 20269 min read

Data contracts before models

Most AI programmes do not fail on the model. They fail because nobody owns the meaning of a column. What a data contract actually contains, why it must be enforced at the producer, and how to retrofit one onto a warehouse that is already in production.

Read the piece

In this piece

  1. What a data contract actually contains
  2. Enforce at the producer, not the consumer
  3. Compatibility modes, and the one most teams choose wrongly
  4. What breaks without lineage
  5. The semantic layer: one definition per business entity

Archive

Everything else we have written down

Long-form, technical, and written by the people who would be on call for the system in question.

Topics

What we write about

Narrow on purpose. We publish on the parts of the work where the received wisdom is thin and the failure modes are expensive.

Data & Platform Engineering
1 piece
Cost engineering
1 piece
Evaluation
1 piece
Applied AI
1 piece

Next step

Disagree with something here?

Good. The fastest way to find out whether we are useful to you is a working session about a system you are actually trying to ship.

Start a conversationSee a blueprint