AI Architecture Scalability Blueprint

Status: draft / active reference
Module: Standards And Decisions
Source: ../intake/2026-06-07-new-4-ai-architecture-scalability-blueprint.txt
Related: software-project-best-practices.md, software-project-master-brief.md, ai-native-architecture.md

Purpose

This blueprint defines how roles in an AI-assisted system should communicate safely and scalably.

It standardizes:

planning,
generation,
evaluation,
handoff format,
shared context,
RAG integration,
JSON schema exchange,
agent traceability.

Core Idea

Each role has a narrow responsibility and communicates through explicit data contracts rather than long copied conversations.

The system should support automatic handoffs between roles without manual copy-paste.

Roles

Planning

The planning role:

clarifies the task,
breaks work into deliverables,
records constraints,
prepares the execution brief,
points to the relevant context.

Generation

The generation role:

produces the implementation or artifact,
respects the brief,
does not silently change the goal,
writes output in the requested format,
adds a self-check summary.

Evaluation

The evaluation role:

checks the result against acceptance criteria,
validates quality and architecture,
decides whether the result is approved or needs revision,
keeps review independent from generation when required.

Orchestration Pattern

Use an orchestrator plus specialists model.

The orchestrator owns task state and handoff lifecycle. The specialist roles only do their bounded job.

Handoff Flow

Recommended flow:

planning.request
planning.output
generation.request
generation.output
evaluation.request
evaluation.output

Each handoff should carry task identity, version, priority, target role and context references.

File Exchange Standard

The system should use JSON files for role handoffs and artifact exchange.

Recommended file types:

task-envelope.json
planning-brief.json
generation-artifact.json
evaluation-report.json
context-bundle.json
knowledge-ref.json

Envelope Rule

The task-envelope.json should be the single transport contract between roles.

It should contain:

schema version,
message type,
message and task ids,
workflow id,
producer and consumer role,
status,
priority,
timestamps,
instruction,
payload reference,
context reference,
trace data.

JSON Contract Principles

The schema should be:

explicit,
versioned,
small enough to maintain,
strict enough to validate,
flexible enough to evolve.

Use enum values for known states and keep raw large content out of the envelope itself by referencing external files or storage objects.

RAG and Shared Context

The shared context should be stored outside the model window and retrieved selectively.

Each role should receive a context-bundle built from:

relevant knowledge refs,
project decisions,
ADRs,
domain requirements,
prior outputs.

RAG should support context reuse without making every role duplicate expensive AI queries.

Output Contracts

Each role should emit a predictable artifact:

Planning -> planning brief,
Generation -> execution artifact,
Evaluation -> review report.

This makes the pipeline easier to automate, inspect and resume.

Traceability Rules

Every handoff should include:

workflow id,
task id,
message id,
attempt number,
source role,
target role.

That allows replay, audit and recovery after interruptions.

Scaling Intent

The blueprint is meant to support:

manual orchestration,
agent handoff automation,
repo-based traceability,
workflow runtime automation,
later scaling into larger agent systems.

Next Actions

Link this blueprint from the standards index.
Use it when designing V2S, RS Forge or any future multi-agent pipeline.
Translate it into actual file names and schemas when implementation starts.