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    <title>topic An AI agent that validates and PRs your Unity Catalog access requests, and knows when to say no in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/an-ai-agent-that-validates-and-prs-your-unity-catalog-access/m-p/166267#M55551</link>
    <description>&lt;P&gt;&lt;SPAN class=""&gt;&lt;SPAN&gt;Most access requests still go through a person hand-writing Terraform off a Slack message and hoping the scope matches what was actually asked for.&lt;BR /&gt;&lt;BR /&gt;I spent the weekend building a pipeline that closes that gap. A Databricks Unity Catalog access request goes from an ADO ticket to an applied grant, with an actual LLM agent doing the validation in between, and a human still required to review and merge every single change before anything touches Databricks.&lt;BR /&gt;&lt;BR /&gt;How it works: someone submits a request through a form, that opens an ADO ticket. A webhook wakes up an Azure AI Foundry agent, it checks the request against live Unity Catalog and decides if it holds up. If it does, it opens a GitHub PR with its reasoning written into the description. Someone reviews it and merges. CI applies the grant, ticket closes itself out.&lt;BR /&gt;&lt;BR /&gt;The design choice I'm most confident about: the agent has exactly 3 tools, and none of them can touch production. It can read the ticket, check Unity Catalog, and open a PR. That's it. It proposes, a human merges. No credential anywhere in the system lets it apply anything on its own.&lt;BR /&gt;&lt;BR /&gt;What I like most about the result: every grant now traces back to a ticket, a PR with the agent's actual reasoning attached, and a person who approved it. That audit trail didn't exist before.&lt;BR /&gt;&lt;BR /&gt;All built on a small personal Azure setup, not an enterprise budget. Functions, AI Foundry, Terraform CI/CD.&lt;BR /&gt;&lt;BR /&gt;Repo's here if anyone wants to look at the code: &lt;A href="https://github.com/vijayakunuri1/unity-catalog-governance-agent" target="_blank" rel="noopener"&gt;https://github.com/vijayakunuri1/unity-catalog-governance-agent&lt;/A&gt;&lt;BR /&gt;&lt;BR /&gt;If you're doing access governance today: is a narrow-tool agent with a hard human gate something you'd actually trust in your pipeline, or does "agentic" only make sense once it can act without you?&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Mon, 24 Aug 2026 04:09:05 GMT</pubDate>
    <dc:creator>vijayakunuri1</dc:creator>
    <dc:date>2026-08-24T04:09:05Z</dc:date>
    <item>
      <title>An AI agent that validates and PRs your Unity Catalog access requests, and knows when to say no</title>
      <link>https://community.databricks.com/t5/data-engineering/an-ai-agent-that-validates-and-prs-your-unity-catalog-access/m-p/166267#M55551</link>
      <description>&lt;P&gt;&lt;SPAN class=""&gt;&lt;SPAN&gt;Most access requests still go through a person hand-writing Terraform off a Slack message and hoping the scope matches what was actually asked for.&lt;BR /&gt;&lt;BR /&gt;I spent the weekend building a pipeline that closes that gap. A Databricks Unity Catalog access request goes from an ADO ticket to an applied grant, with an actual LLM agent doing the validation in between, and a human still required to review and merge every single change before anything touches Databricks.&lt;BR /&gt;&lt;BR /&gt;How it works: someone submits a request through a form, that opens an ADO ticket. A webhook wakes up an Azure AI Foundry agent, it checks the request against live Unity Catalog and decides if it holds up. If it does, it opens a GitHub PR with its reasoning written into the description. Someone reviews it and merges. CI applies the grant, ticket closes itself out.&lt;BR /&gt;&lt;BR /&gt;The design choice I'm most confident about: the agent has exactly 3 tools, and none of them can touch production. It can read the ticket, check Unity Catalog, and open a PR. That's it. It proposes, a human merges. No credential anywhere in the system lets it apply anything on its own.&lt;BR /&gt;&lt;BR /&gt;What I like most about the result: every grant now traces back to a ticket, a PR with the agent's actual reasoning attached, and a person who approved it. That audit trail didn't exist before.&lt;BR /&gt;&lt;BR /&gt;All built on a small personal Azure setup, not an enterprise budget. Functions, AI Foundry, Terraform CI/CD.&lt;BR /&gt;&lt;BR /&gt;Repo's here if anyone wants to look at the code: &lt;A href="https://github.com/vijayakunuri1/unity-catalog-governance-agent" target="_blank" rel="noopener"&gt;https://github.com/vijayakunuri1/unity-catalog-governance-agent&lt;/A&gt;&lt;BR /&gt;&lt;BR /&gt;If you're doing access governance today: is a narrow-tool agent with a hard human gate something you'd actually trust in your pipeline, or does "agentic" only make sense once it can act without you?&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 24 Aug 2026 04:09:05 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/an-ai-agent-that-validates-and-prs-your-unity-catalog-access/m-p/166267#M55551</guid>
      <dc:creator>vijayakunuri1</dc:creator>
      <dc:date>2026-08-24T04:09:05Z</dc:date>
    </item>
    <item>
      <title>Re: An AI agent that validates and PRs your Unity Catalog access requests, and knows when to say no</title>
      <link>https://community.databricks.com/t5/data-engineering/an-ai-agent-that-validates-and-prs-your-unity-catalog-access/m-p/166310#M55554</link>
      <description>&lt;P&gt;Honestly, the “make it repeatable” point is huge. The tool matters less than having a workflow you can rerun without manually fixing the same mess every time.&lt;/P&gt;</description>
      <pubDate>Mon, 24 Aug 2026 12:53:20 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/an-ai-agent-that-validates-and-prs-your-unity-catalog-access/m-p/166310#M55554</guid>
      <dc:creator>ThiamLee</dc:creator>
      <dc:date>2026-08-24T12:53:20Z</dc:date>
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