---
title: "The Partner Well-Architected Framework: What's New and What's Next"
description: "The Partner Well-Architected Framework (PWAF) has moved partner guidance from static PDFs to AI-ready guidance spanning Built-On, Connected, and Data Collaboration architectures. It combines an architecture center with technical standards, patterns, and instrumentation guidance intended to align integrations with partner-engineering validation while making adoption and DBU impact measurable. Since February, Databricks has added a Dev Kit containing 15+ tested AI-developed skills, new or refreshed guidance for Clean Rooms, software-defined storage, Marketplace apps, Genie, Lakebase, and MCP server onboarding, and an open-source Firefly Analytics reference implementation. The framework is positioned as an evolving, agent-compatible way to shift routine integration work to AI tools, freeing partner and Databricks engineers to focus on complex architecture; more patterns, skills, reference implementations, and demos are planned."
---

# The Partner Well-Architected Framework: What's New and What's Next

[Databricks](https://yomu.fyi/company/databricks) · David Porter · Jun 17, 2026

**Type:** Announcement

## Summary

The Partner Well-Architected Framework (PWAF) has moved partner guidance from static PDFs to AI-ready guidance spanning Built-On, Connected, and Data Collaboration architectures. It combines an architecture center with technical standards, patterns, and instrumentation guidance intended to align integrations with partner-engineering validation while making adoption and DBU impact measurable. Since February, Databricks has added a Dev Kit containing 15+ tested AI-developed skills, new or refreshed guidance for Clean Rooms, software-defined storage, Marketplace apps, Genie, Lakebase, and MCP server onboarding, and an open-source Firefly Analytics reference implementation. The framework is positioned as an evolving, agent-compatible way to shift routine integration work to AI tools, freeing partner and Databricks engineers to focus on complex architecture; more patterns, skills, reference implementations, and demos are planned.

## Context

PWAF was created to replace static partner guidance, keep pace with Databricks releases and the AI market, and provide common patterns and standards for partners building data and AI applications, agents, and AI-powered experiences on Databricks.

## Approach / What changed

PWAF combines architecture guidance, validated technical standards, measurable telemetry, AI-developed coding skills, refreshed integration patterns, and the open-source Firefly Analytics reference implementation across Built-On, Connected, and Data Collaboration architectures.

## Takeaways

- The Databricks AI Partner Dev Kit contains 15+ fully tested skills covering integration patterns, telemetry instrumentation, and partner validation preparation.
- A JDBC integration that previously took around 20 prompts of back-and-forth with a coding tool came together in a single shot using the Dev Kit.
- Firefly Analytics is an open-source Databricks Labs reference implementation with examples for authentication, IAM, SSO/SPN flows, security, scale, embedded apps, and AI.

**Tags:** [AI Agents](https://yomu.fyi/topic/ai-agents), [Architecture](https://yomu.fyi/topic/architecture), [Open Source](https://yomu.fyi/topic/open-source)

- Source: [Databricks](https://www.databricks.com/blog/partner-well-architected-framework-whats-new-and-whats-next)
- Source URL: https://www.databricks.com/blog/partner-well-architected-framework-whats-new-and-whats-next
- Ingested by Yomu: 2026-08-30T17:01:18.929Z

[Read original post](https://www.databricks.com/blog/partner-well-architected-framework-whats-new-and-whats-next)