# Mage Brand Voice

> Mage is a technical, authoritative, and utility-driven voice that speaks directly to the complexities of data engineering.

## Positioning
Mage is the execution layer for complex data work, designed for teams that have outgrown brittle scripts and fragmented tools. It provides a unified system to ingest, transform, orchestrate, and deliver production-grade data workflows.

## Voice principles
- **Functional:** Focuses on verbs and outcomes (ingest, transform, monitor) rather than abstract promises.
- **Direct:** Uses short, declarative sentences that address technical pain points without hedging or fluff.
- **Architectural:** Speaks in terms of systems, layers, and infrastructure to appeal to engineering mindsets.
- **Problem-Oriented:** Explicitly identifies technical debt (brittle scripts, fragmented tooling) as the enemy.

## Tone by context
| Context | Tone |
|---|---|
| Marketing Hero | High-level and authoritative, focusing on the "execution layer" concept. |
| Feature Lists | Technical and granular, emphasizing specific integrations and capabilities. |
| Value Propositions | Empathetic to the engineer's struggle with "messy" or "brittle" systems. |
| Call to Action | Low-friction and urgent (Try free, Start Building). |

## Lexicon
- **Use:** Execution layer, production workflows, orchestrate, actionable outputs, governed, brittle, fragmented, downstream, upstream, domain-owned, syncs, refreshes.
- **Avoid:** "Magic" (ironically), seamless, revolutionary, easy, simple (prefers "standardize" or "unify").

## Messaging do's and don'ts
- **Do:** Use active verbs to describe data movement (Move, Run, Send, Turn).
- **Do:** Reference specific technical formats like dbt, Python, SQL, XML, and SOAP.
- **Do:** Emphasize reliability and "production" readiness.
- **Don't:** Use flowery marketing adjectives; keep the focus on the "work" and the "logic."
- **Don't:** Over-promise simplicity; acknowledge that data work is "complex" and "messy."
- **Don't:** Personify the software; treat it as a robust infrastructure layer.

## Evidence
- "The execution layer for complex data work"
- "Replace brittle scripts, fragmented tools, messy handoffs"
- "Ingest, transform, orchestrate, monitor, and activate"
- "Standardize messy operational data"
- "Built for real production data use cases"