Glossary

The BROCS vocabulary, defined tersely and linkably.

Definitions, not arguments. Each term is a stable anchor you can link to, and the whole set is published as structured data so answer engines can quote it without paraphrasing it into something else.

BROCS #: A vendor-neutral framework naming the five parts of the surface an organization must cover to adopt AI seriously: Build, Run, Observe, Control, and Secure. Pronounced like "brocks".
The surface #: Everything an organization has to own for AI work to be useful and safe, from the tools people build with through to the evidence an auditor asks for. BROCS is the claim that the surface has five parts and that partial coverage is the default failure.
Scoreline #: A five-number summary of how well an organization covers the surface, one score of 0 to 4 per letter, written in letter order. B3 R2 O1 C2 S0 is a scoreline.
Tool churn B · Build #: The observed rate at which AI tools are adopted and abandoned. The planning assumption that follows: any layer coupled to a specific tool will be rewritten within a year, so the enablement layer has to sit underneath the tools rather than inside one.
Enablement layer B · Build #: The shared substrate that gives every AI interface the same identity, keys, data access, and runtime. It is what makes swapping a tool a configuration change instead of a migration.
Shadow AI S · Secure #: Use of AI tools that the organization has not sanctioned, usually through personal accounts and personal payment methods. It is a symptom rather than a cause: people reach for unsanctioned tools when the sanctioned path is missing or slower.
BYOK B · Build #: Bring your own key. The customer supplies their own model provider credentials so inference is billed to and governed by their account, and the vendor never holds the key.
BAA endpoint B · Build #: A model endpoint covered by a Business Associate Agreement, permitting protected health information under HIPAA. One of the three sovereign paths, alongside local models and models run through your own cloud account.
Sovereignty R · Run #: The property that inference and data processing happen somewhere the organization controls legally and physically. Treated in BROCS as a hard requirement for some organizations rather than a preference for all of them.
Golden path B · Build #: A paved, opinionated route from idea to production that is easier to follow than to avoid. The platform engineering answer to governance: make the compliant path the fast path.
Integration tax #: The cumulative cost of contracts, integrations, identity wiring, and audit processes incurred when each part of the surface is bought from a different vendor. Where the productivity gain from AI adoption usually goes.
Control plane C · Control #: The part of a system that decides what should be running, with what configuration. Distinct from the data plane, which carries the actual work.
Data plane R · Run #: The part of a system that carries the actual work: requests, inference, data. It should keep serving when the control plane is down.
Provisioning R · Run #: Creating the infrastructure a piece of work needs: compute, database, secrets, ingress, identity. Self-service provisioning is the difference between a golden path and a ticket queue.
Portability R · Run #: The ability to run the same workload in a different place without rewriting it. In BROCS the specific claim is that the runtime must go where the data already is, which in a regulated enterprise means one system covering local, private, and public infrastructure.
Golden signals O · Observe #: Latency, traffic, errors, and saturation. The four SRE signals. For AI workloads the set extends with tokens, cost, tool calls, and refusal or failure rate.
Agent trace O · Observe #: An ordered record of what an agent did in one run: prompts, tool calls, arguments, results, and the data touched. The artifact you need to answer what happened, and the artifact an auditor will ask for.
Drift O · Observe #: Change in model behaviour over time without a corresponding change in your code. Causes include provider updates, retrieval corpus changes, and prompt edits upstream of you.
Eval O · Observe #: A repeatable test of model or agent output quality against fixed inputs. Evals are to AI systems what unit tests are to code: not proof of correctness, but the thing that tells you when it got worse.
Model routing C · Control #: Deciding at request time which model or provider serves a call, and being able to change that decision centrally. The mechanism that keeps switching cost near zero.
Pinning C · Control #: Fixing a workload to a specific model version so a provider update cannot change behaviour underneath it. The counterpart to routing.
Ingress C · Control #: The front door: how requests reach an internal application, and where authentication, authorization, and logging are applied. One front door beats a tunnel per team.
Prompt injection S · Secure #: Getting a model to follow instructions from content rather than from its operator. Direct injection comes from the user; indirect injection arrives inside data the model reads, such as a document, a web page, or an email.
Blast radius S · Secure #: Everything a component can reach if it is compromised or simply wrong. For an agent it is the union of its tool permissions and its standing data access, which is usually larger than anyone assumed.
Human in the loop S · Secure #: A required human approval on a specific class of action before it executes. Useful in proportion to how narrowly the class is defined; an approval prompt on everything is trained away within a week.
Showback S · Secure #: Reporting AI spend back to the team that incurred it without moving money. Chargeback moves the money as well. Both require per-team, per-app attribution at the point of inference.
Audit evidence S · Secure #: The artifacts a control owner or auditor needs to show a control operated: access records, approvals, traces, retention proof. Treated in BROCS as a continuous platform output rather than a quarterly collection exercise.
DORA metrics B · Build #: Deployment frequency, lead time for changes, change failure rate, and time to restore service. From the DevOps Research and Assessment program. BROCS borrows lead time directly: how long from an idea to something running.
Platform engineering B · Build #: Building an internal platform as a product for the engineers who use it. The discipline BROCS leans on most heavily for Build and Run.
GRC S · Secure #: Governance, risk, and compliance. The discipline BROCS leans on for Secure, with one amendment: policy has to be encoded where it is enforced, not written where it is filed.
FinOps S · Secure #: The practice of making cloud spend visible and accountable to the teams that cause it. Applies directly to inference spend, which is more elastic and less predictable than compute.
Retrieval boundary C · Control #: The versioned, reviewed set of sources a model is permitted to answer from. Making that set explicit is what turns a chatbot's answer into a company statement you can stand behind.