Library// topic
Deciding what to build, and who builds it
In short
The pre-engagement decision — whether to build, buy or configure, whether to hire in-house or bring in a partner, how studios, consultancies, agencies and freelancers actually differ, and how to justify the spend and run diligence on a vendor whose security posture rests on controls rather than certificates.
6 pages
definitions
- "Dedicated team" defined by what it does not promiseThe phrase commits a supplier to almost nothing on its own. What it usually means in practice, and the three artefacts that turn it into something you can verify.definition6 min
- Total cost of ownership is a structure, not a numberA single total cost figure tells you nothing. The structure does: four phases, a fixed list of line items, filled in identically for every option you are comparing.definition6 min
diagnostics
- Everything is now a change requestArguing about whether a change request is fair goes nowhere. Sorting the last 10 into 3 buckets says whether the bid was underscoped, the scope grew, or nobody decided.diagnostic9 min
- Finance sent it back again and did not say whyA second rejection with no stated reason is not obstruction. Ask which number would have to change for approval, and the reply identifies which of four defects you have.diagnostic9 min
- The engineers who pitched are not the engineers writing the codeAn impression that the team changed is unarguable and useless. Commit authorship against the names in the proposal is measurable, and it separates a legitimate rotation from a silent downgrade.diagnostic9 min
- The supplier you want cannot pass a policy written for someone elseProcurement policies rarely require a certificate universally. They require one when a condition is met, and four of those conditions can be changed by how the engagement is designed.diagnostic10 min
Other topics in Library
See allRetrieval and grounding: answering from your own contentEverything that happens at query time — how a passage is chosen, ranked, filtered by permission and cited — and how you tell 'the wrong documents came back' apart from 'the right documents, badly used'; the plumbing that gets content into the index lives in the data cluster, and eval methodology lives in the release-gate cluster.20 pagesData readiness, pipelines and keeping the corpus trueThe unglamorous half of every AI build — whether the data is usable at all, how it gets in, how it stays fresh, and how deletions, duplicates and schema drift are handled before anything is indexed or inferred over; one-off migrations of a legacy dataset belong to the integration cluster.16 pagesChoosing the shape of the systemThe decision made before any code exists: what problem shape this actually is, whether it needs an agent loop, a fixed pipeline, a classifier or no model at all, how much autonomy the task can carry, and whether prompting, retrieval or training is the right lever — which process to automate first is an organisational question and sits in the adoption cluster.2 pages
Working on something in this space?
Tell us where you are in a sentence or two. We'll tell you honestly whether we're the right team, and what a sensible first slice of the work looks like.
Start the conversation