Pillar 02 · See
HATEOAS is the most-cited, least-implemented part of REST. Here is where a HAL-style _links block genuinely helps in a NestJS 10 response, and where it is just noise.
A GraphQL schema is a contract you live with for years. Get nullability, Relay connections and mutation payloads right up front, or every client pays for it.
A working method for turning a domain into REST resources: collection vs singleton, when to nest sub-resources or link them, plural nouns, and a FastAPI route table.
A hands-on git subtree vs submodule comparison for sharing a library across repos, with the exact add, pull, push and split commands and where submodules still win.
How to split a flat Terraform config into versioned, composable modules with clear inputs, outputs and boundaries — and how to know when a module is premature abstraction.
“Consolidate onto one platform” and “pick best-of-breed for each function” both get argued as if one is universally right. Neither is. The question that actually matters is which specific cost each approach is asking you to accept — and most organisations pick a side before anyone has named the cost honestly. Consolidation’s advocates point to …
Ask a compliance team what the AI Act requires and you get articles and annexes. Ask the engineering team building the actual system and you get a shrug, because nobody has translated “conduct a fundamental rights impact assessment” into a sprint they can actually plan. That translation gap is where AI Act compliance programmes quietly …
Every automation decision now defaults to “can we make this agentic” when the actual first question should be “does this need to be.” Deterministic automation and agentic autonomy solve genuinely different problems, and picking the more exciting one for a task that needed the boring one is a specific, recurring, expensive mistake. Deterministic automation — …
Walking into an organisation on day one and being asked “so, how are we doing” is the single most common moment in fractional CTO work, and it’s also the moment where a wrong first move costs months. There’s no existing context, no institutional memory of past decisions, and a genuine risk of either taking too …
AI doesn’t make an engineering organisation good or bad. It makes a good one better and a bad one worse, faster than either outcome would have happened without it — and the organisations most excited about AI’s productivity gains are frequently the ones with the least visibility into which of the two they actually currently …