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AI development field packet

Model Facts Register: a worksheet for production AI model decisions

Use this register when a model decision depends on facts that can go stale: region, quota, context, price, lifecycle, retention, SDK behavior, and fallback. Start with one production workload and assign an owner before the next release treats the model choice as permanent.

Copy the model facts registerReview one model-dependent workflow
A model facts register field packet showing workload rows with region, quota, lifecycle, retention, SDK compatibility, owner, review cadence, and fallback fields.
Use the register to decide who owns each model fact and when it must be rechecked before the next release.

A production workload is close to a quota ceiling or throughput change.

A Bedrock, SDK, model-version, or provider-routing update could break a release.

Security or legal needs the actual data-retention posture for one model-dependent workflow.

A team needs a fallback model, manual path, or stop rule before expanding traffic.

The model catalog is useful, but no one owns local SDK behavior, project policy, or review cadence.

A pilot is moving from experimentation into a support, operations, analytics, or customer-facing workflow.

How to use it

Start with one row, one owner, and one review trigger

One workload first

Do not start by making a giant model catalog. Pick the workload that would hurt most if a region, quota, retention, or SDK fact changed quietly.

Vendor fact plus local fact

Bedrock or another vendor can expose model metadata. Your team still owns the account quota, project policy, SDK path, fallback, and review trigger.

Refresh is part of done

A row is not complete until it has a last-refreshed date, an accountable owner, and the event that makes the team recheck it.

Fallback before incident

The time to name the fallback model or stop condition is before the primary path fails in production.

Copyable worksheet

The register fields

Copy the table into a planning document or spreadsheet. Keep the first pass narrow: one production workload or five recurring questions before creating a broad catalog.

Copyable register worksheet fields and why each field matters
FieldWhat to writeWhy it matters
Workload ownerThe person accountable for this workload's model choice staying current.A catalog can surface facts, but it cannot assign anyone to act on them.
Candidate model / providerThe exact model, version, provider, and invocation path this workload calls.Provider families move fast enough that a family name is not a production decision.
Region availabilityThe regions where this model is actually served for this account and workload.A model can be generally available and still absent from the region your workflow uses.
TPM / RPM quotaThe current throughput ceiling for this account, region, and model path.Quotas are operational facts, not marketing facts, and they change outside the original selection meeting.
Context and max output limitsThe input, output, and tool-call ceilings this workload depends on.A prompt or response shape that worked last quarter can fail after a model or SDK change.
Pricing / consumption modeOn-demand, provisioned throughput, batch, committed spend, or other billing mode.The same model can have different economics depending on how the workload invokes it.
Lifecycle statusGenerally available, legacy, preview, deprecated, replacement pending, or on a sunset clock.Lifecycle notices often arrive outside the architecture doc that named the model.
Data-retention / project policyRetention, residency, logging, training-use, or project-setting commitments that apply to this traffic.Security and legal need the workload's actual policy, not a generic model-card assumption.
Known SDK / API incompatibilitiesClient-library, message-format, schema, auth, tool-calling, or provider-routing issues for this workload.Integration drift often appears when a specific SDK meets a specific model version.
Last refreshedThe date someone last checked every field in this row against current sources.A fact with no timestamp is a guess wearing a table's clothing.
Review cadenceMonthly, quarterly, on quota alert, on lifecycle notice, on SDK upgrade, or before the next release.The register only works if the row says when it gets rechecked.
Fallback model / stop ruleThe fallback model, route, manual path, or pause condition when the primary choice breaks.Without this row, a quota miss or deprecation notice becomes an incident instead of a routing decision.

Copy block

Paste this plain-text version into your next working doc

The register is intentionally portable. It should survive a meeting, a pull request, a wiki page, or a spreadsheet before it becomes a polished internal tool.

Model Facts Register

Workload name:
Business owner:
Technical owner:
Current model path:

| Field | What to write | Owner / source | Last refreshed | Review trigger |
| --- | --- | --- | --- | --- |
| Workload owner |  |  |  |  |
| Candidate model / provider |  |  |  |  |
| Region availability |  |  |  |  |
| TPM / RPM quota |  |  |  |  |
| Context and max output limits |  |  |  |  |
| Pricing / consumption mode |  |  |  |  |
| Lifecycle status |  |  |  |  |
| Data-retention / project policy |  |  |  |  |
| Known SDK / API incompatibilities |  |  |  |  |
| Last refreshed |  |  |  |  |
| Review cadence |  |  |  |  |
| Fallback model / stop rule |  |  |  |  |

Decision note:
What changed since the last review:
What blocks the next release:
What the workflow does if the model path fails:

Example row

A sample row, clearly marked as sample data

Workload owner
Support platform lead
Candidate model / provider
Claude Sonnet via Amazon Bedrock Messages API
Region availability
us-east-1 and us-west-2 confirmed for production traffic
TPM / RPM quota
Current account quota checked before each release train
Context and max output limits
Long support-history summaries need a 200K context path and short final replies
Pricing / consumption mode
On-demand for normal ticket volume; revisit if nightly batch summary expands
Lifecycle status
GA; owner watches provider and Bedrock lifecycle notices
Data-retention / project policy
Use the approved project setting for customer-support data; confirm retention before model swap
Known SDK / API incompatibilities
Track strict tool-schema and message-format issues in the integration backlog
Last refreshed
2026-07-03
Review cadence
Monthly, and before SDK or model-version upgrades
Fallback model / stop rule
Pause customer-facing draft generation if the primary model or SDK path rejects the request shape
Diagram showing vendor catalog facts and local workload facts merging into one owned model facts register row with owner, review cadence, fallback, and stop rule.
A catalog can say what a model supports; the register says who rechecks that fact for this workload.

Next step

Bring one model-dependent workflow to a focused review

BaristaLabs can help map the model facts that matter for one production workload, especially the retention, SDK compatibility, quota, lifecycle, and fallback rows that vendor catalogs do not own for your implementation.

Review one model-dependent workflow

Source notes

Claims checked before publication

  • AWS's July 2026 Model Profiler article still describes Amazon Bedrock as offering access to more than 100 foundation models and names scattered console, documentation, regional, pricing, context, and throughput facts as the problem the open-source profiler addresses.
  • The AWS article still says the profiler provides model cards, side-by-side comparisons, regional availability maps, and pricing breakdowns updated daily from multiple APIs and public sources.
  • The AWS article still describes a serverless pipeline with 17 Lambda functions, Step Functions orchestration, inter-Lambda S3 caching that reduces roughly 480 API calls to 29 per run, a 97% cache hit rate, and an 8–12 minute daily run cadence.
  • The aws-samples Bedrock Model Profiler README is still live and frames the project around model selection, migration planning, cost optimization, regional planning, capability matching, and quota analysis.
  • The Vercel AI SDK, LiteLLM, and Terraform AWS provider GitHub pages remain useful as integration-drift signals, not universal failure claims: they show specific Bedrock Messages API, data-retention/project-mode, AgentCore registry, and private-endpoint support work moving outside a model catalog.

Related resources

Keep the register connected to controls, receipts, and services

Production AI model evaluation guide

Build the comparison evidence before the approved model path, owner, fallback, and recheck trigger enter the register.

Open resource

AI workflow controls

Connect the model row to permissions, approval policy, receipts, rollback, and launch evidence.

Open resource

AI workflow security review worksheet

Name the data, vendor/model exposure, credential, retention, and security questions before model traffic expands.

Open resource

Agent receipt template

Record which model path ran, what evidence it used, what action it proposed, and how the team can reconstruct or correct it.

Open resource

AI workflow rollback plan

Turn fallback and stop-rule fields into a recovery path before model or quota drift becomes an incident.

Open resource

Strategic AI consulting

Use the register as advisory evidence before a model or vendor choice becomes the default.

Open resource

Custom solutions

Bring the register into custom AI systems that need production-readiness artifacts, not just model-pick notes.

Open resource