Together AI Reference Architecture

Overview

This skill turns workload requirements into explicit real-time, batch, and dedicated paths with one governed provider boundary and observable cost/quality behavior.

Prerequisites

• Workload classes, modalities, volumes, latency objectives, and data classifications
• Model-quality evaluations and fallback constraints
• Availability, cost, retention, residency, and recovery objectives
• Existing gateway, queue, telemetry, and secret-management topology

Tool Discipline

Use Read, Glob, and Grep to map callers, trust boundaries, queues, storage, and observability. Use WebFetch for current Together capabilities and limits. Use Write or Edit only for approved diagrams, ADRs, interfaces, or configuration.

Current Contract