AI & Prompts: standardize, evaluate, and share—without drift
Centralize prompts, system messages, eval sets, dashboards, model cards, and RAG sources. Tag by model, task, tone, version, owner, and status—publish a read-only catalog for teams.
TL;DR: AI Platform + use-case workspaces → tags for model, task, tone, version, owner, status → import canonical links → publish approved prompts → enforce SSO/SAML & audit.
Common pain points
- Prompts scattered across repos, wikis, and personal docs.
- Multiple versions with unclear ownership (who changed what?).
- Support/Sales using outdated prompts; inconsistent tone.
- Hard to connect prompts with eval runs, dashboards, and model cards.
How Linkinize helps
- Governed library with model/task/tone/version/owner/status tags.
- Approved catalogs via read-only Public Pages for field teams.
- Cross-tool links to eval sets, dashboards, model cards, and RAG sources.
- SSO/SAML + audit to enforce access and review changes.
What is prompt drift (and how to prevent it)?
Prompt drift happens when teams use slightly different versions of a prompt over time—reducing quality and consistency. Prevent it by: publishing an approved catalog, tagging version/owner/status, linking to eval results, and archiving deprecated prompts.
How it works (5 steps)
- Create an AI Platform workspace, plus per-use-case workspaces (Support, Sales, RAG, Agents).
- Define tags (see template):
model:*,task:*,tone:*,version:v1|v2,owner:*,status:approved|draft|deprecated. - Import canonical links: prompts/system messages (repo/wiki), eval datasets, evaluation dashboards, model cards, and RAG sources.
- Publish a Public Page of approved prompts, with usage notes and examples for non-technical teams.
- Enforce SSO/SAML, assign owners, and review audit logs monthly. Deprecate old prompts.
Integrations you’ll likely use
Link to the single source of truth—permissions remain enforced where content lives.
- Model APIs: OpenAI, Azure OpenAI, Anthropic, Google Vertex AI, AWS Bedrock
- Orchestration: LangChain, LlamaIndex
- Evals/Monitoring: Promptfoo, LangSmith, Humanloop, Langfuse, Helicone
- Vector DB/RAG: Pinecone, Weaviate, pgvector, Elastic
- Docs/Wikis: Notion, Confluence, Google Drive/SharePoint
- Support/Sales: Intercom, Zendesk, Salesforce/HubSpot (link prompt playbooks)
Starter taxonomy (copy & adapt)
Model & Task
- model:gpt-4o · model:llama3 · model:claude
- task:summarize · task:extract · task:classify · task:generate · task:translate
Tone & Version
- tone:formal · tone:friendly · tone:creative
- version:v1 · version:v2
Owner & Status
- owner:research · owner:marketing · owner:support
- status:approved · status:draft · status:deprecated
Common questions & objections
“We already store prompts in code.”
Perfect—keep it that way. Linkinize indexes the canonical locations and explains usage to non-dev teams, with ownership and status labels.
Perfect—keep it that way. Linkinize indexes the canonical locations and explains usage to non-dev teams, with ownership and status labels.
“Every team tweaks prompts.”
Publish an approved set and tag drafts separately. Archive deprecated variants and link to eval deltas to justify changes.
Publish an approved set and tag drafts separately. Archive deprecated variants and link to eval deltas to justify changes.
“Will this expose sensitive details?”
Keep sensitive materials in private workspaces behind SSO; publish a minimal, read-only catalog for broad consumption.
Keep sensitive materials in private workspaces behind SSO; publish a minimal, read-only catalog for broad consumption.
“Another tool to maintain?”
You save canonical URLs; content stays where it lives. Public Pages auto-update as links change in source systems.
You save canonical URLs; content stays where it lives. Public Pages auto-update as links change in source systems.
Consistent prompts, consistent outcomes
Teams use Linkinize to standardize prompts across support, sales, and RAG apps—reducing drift and aligning tone while keeping developers in control.
- • Approved, searchable prompt catalog
- • Links to evals, dashboards, and model cards
- • SSO/SAML, roles, and audit logging
- • Works with OpenAI/Anthropic/Vertex/Bedrock, LangChain/LlamaIndex
Frequently Asked Questions
- Do we store prompts in Linkinize?
- No—Linkinize stores links and metadata. Keep prompts in code, repos, or your prompt manager; Linkinize is the retrieval and governance layer.
- How do we handle per-model tuning?
- Create model-specific variants (e.g.,
model:gpt-4o,model:llama3) and link each to eval results + model cards. - Can non-technical teams use the catalog?
- Yes—share a read-only Public Page with approved prompts and plain-language usage notes.