Architecture8 min read
Why AI projects stall at the infrastructure layer
Most stalled AI initiatives are not model problems. They are missing data contracts, absent ownership and no path to roll a change back.
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Engineering notes from production.
Written by the MS Global Growth engineers doing the work. Opinionated, specific, and free of vendor marketing.
Accelerated computing6 min read
Budgeting GPU-accelerated inference honestly
Batching, quotas and cold-start behaviour move accelerator cost more than model choice. A practical framework for forecasting spend.
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Data contracts: the smallest useful version
You do not need a governance programme to start. You need a schema, an owner, a test and a deprecation policy.
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Putting a human in the automation loop without killing throughput
Approval steps are cheap when they are targeted. Here is how we choose which decisions get reviewed.
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Evaluation suites as deployment gates
If a model ships without an evaluation gate, the first regression report will come from a customer.
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Observability for data pipelines, not just services
Freshness, volume, distribution and lineage belong on the same dashboards as latency and error rate.
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