An agent can only explain what your data platform can explain. How business rules, their history, and corrections are engineered from the lakehouse up decides what analysts can trust and what agents can safely do.
43 minutes
How an employee's Microsoft Entra sign-in reaches an ADK agent on Agent Runtime: the token checks, the session binding, who else can call …
58 minutes
Choosing storage for a BigQuery lakehouse layer by layer: what native tables, managed Iceberg, and Iceberg in an open catalog each give up, …
21 minutes
Many QSR and retail estates run identity in Microsoft Entra ID, back-office systems on SQL Server in Azure, the data platform on Google …
22 minutes
Why operations and analytics report different sales for the same store-day, and how a medallion pipeline brings a multi-site network to one …
10 minutes
Loyalty points are a balance-sheet liability as well as a marketing tool. Following one point through enrolment, earning, accrual, …
6 minutes
A 71-page operating manual for engineering leaders whose software has started to reason, decide, and write the software that carries out …
18 minutes
A 150-billion-parameter mixture-of-experts model streamed from NVMe on an ordinary developer laptop with no usable GPU. Across a 200-token …
10 minutes
A studio can find its back catalogue inside a public model's training data and discover it cannot prove, from its own systems, when the work …
9 minutes
Subscription and on-demand media platforms still spend their engineering effort preparing for the scheduled launch, while the traffic that …
7 minutes
Two weeks ago I argued that your ontology is the asset and you should own it in a neutral, versioned form. Arguing is cheap. Arkhe v0.2 is …
9 minutes
Regulators have moved from asking banks for periodic reports to asking for specific evidence, on demand, about decisions made months ago. …
9 minutes
Being correct is not the same as being able to prove it. This final post in The Engineering Underneath argues that trust is an engineering …
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