Files
fidelity-ai-workspace/agent-memory/workflows/ai-to-ai-prompting.md
david.delagneau dbc1894e27 Add project-knowledge structure and templates
- Introduced new maps for navigating project knowledge, including "Current Work," "Fidelity Domain," "Fidelity Apps," "Work Items," and "People."
- Created base files for daily notes, decisions, people, systems, work items, and workstreams with defined properties and views.
- Developed templates for daily notes, decisions, meeting notes, persons, systems, work items, and workstreams to standardize documentation.
- Updated scripts and prompts to reflect the new project-knowledge directory structure.
- Removed outdated onboarding and start-here documents, consolidating relevant information into the new maps.
- Ensured all references in workflows and scripts point to the new project-knowledge paths.
2026-04-17 15:52:08 -06:00

2.4 KiB

type, status, updated, tags
type status updated tags
agent-workflow active 2026-04-17
process
ai-prompting

AI-To-AI Prompting

Goal

Generate prompts that can be sent to another AI assistant on the Fidelity development machine, especially GitHub Copilot.


Operating Assumption

This workspace does not contain the product codebase. The target AI has access to the Fidelity codebase on another machine.

Therefore prompts must:

  • include only the relevant project context from this workspace
  • tell the target AI what files/modules to inspect
  • ask for a concrete output
  • specify constraints and non-goals
  • avoid pretending the target AI already has this workspace memory

Prompt Structure

Use this structure by default:

  1. Role
  2. Project context
  3. Current task
  4. Relevant ticket/context
  5. Files/modules to inspect
  6. Constraints
  7. Expected output
  8. Validation requirements

Prompt Quality Rules

  • Prefer precise task framing over long background dumps.
  • Include Jira ID and title when the work maps to a ticket.
  • Include current constraints such as REST feature flag, GraphQL fallback, auth state, backend-driven behavior, and consumer validation when relevant.
  • Ask the target AI to inspect code before proposing changes.
  • Ask for a plan first when the implementation scope is uncertain.
  • Ask for code changes only when the desired write scope is clear.
  • Include "Do not assume REST is active by default" for REST migration tasks.
  • Include "Separate external issue from regression" for AO/Discourse issues.
  • Include "Validate against Fid4/consumer path when needed" for XFlow integration tasks.

Bad Prompt Pattern

"Fix this issue in XFlow."

Why bad:

  • no entry point
  • no auth state
  • no expected behavior
  • no ticket context
  • no validation path
  • no scope boundary

Good Prompt Pattern

"You are working in the Fidelity iOS codebase. Inspect the XFlowSDK and XFlowViewMaker integration path for PDIAP-14859 - Spike - Research strategy to remove final UIKit wrapping from XFlowSDK and XFlowViewMaker without disrupting consumer implementation. First identify where XFlow currently exposes SwiftUI through UIHostingController, where XFlowViewMaker consumes it, and what feature flag protects the migration path. Do not change code yet. Return a concise plan with affected files, risks, consumer validation needs in Fid4/FTTransfer, and any questions that block implementation."