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Copy file name to clipboardExpand all lines: src/content/posts/azure-devops-agentic-pipelines/index.md
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@@ -13,7 +13,7 @@ There are four key pipeline jobs in Agentic Pipelines, mirroring that of the age
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***Setup** - Preprocessing jobs that a user may optionally specify.
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***Agent execution** - Agent completes the task specified by the user, optionally using outputs from the Setup job. The agent produces "safe outputs" that are later evaluated.
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***Threat detection** - Safe outputs are analysed for threats e.g. prompt injection, DDOS, directory traversal attacks.
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***Threat detection** - Safe outputs are analysed for threats e.g. prompt injection, DDoS, directory traversal attacks.
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***Safe output execution** - Having been deemed safe, the outputs are executed. There is no agent involvement here. Outputs are evaluated against the contract, specified in the original definition.
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The key innovation is the separation of agent action from execution. When both are combined, agentic execution cannot be audited or analysed. In a separate two stage process it can!
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### Analysis Process
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1. *Read the instructions file*: Start by reading .github/copilot-instructions.md thoroughly
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1.*Read the instructions file*: Start by reading `.github/copilot-instructions.md` thoroughly
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....
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```
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### Context
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The ./failure-summaries directory contains triage summary files from failing pipeline runs over the last 5 days. Each file represents a failed build and contains:
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• Test failures and error messages
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• Build configuration details
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• Potential root causes identified by automated triage
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The `./failure-summaries` directory contains triage summary files from failing pipeline runs over the last 5 days. Each file represents a failed build and contains:
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- Test failures and error messages
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- Build configuration details
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- Potential root causes identified by automated triage
Copy file name to clipboardExpand all lines: src/content/posts/my-revised-metric/index.md
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@@ -13,7 +13,7 @@ Here are a few examples that have come from injecting this mindset into my devel
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### Decreasing my time-to-awesome with improved agent time-to-awesome
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Before, I would spot issues while navigating a codebase but ignore them to stay focused on the task I set out to complete. Now, I have built a VS Code extension that lets VS Code Copilot create Azure DevOps for Github copilot issues contextually. My time to agent time-to-awesome is significantly reduced and the agent begins work outside my primary development flow.
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Before, I would spot issues while navigating a codebase but ignore them to stay focused on the task I set out to complete. Now, I have built a VS Code extension that lets VS Code Copilot create Azure DevOps work items for GitHub Copilot issues contextually. My time to agent time-to-awesome is significantly reduced and the agent begins work outside my primary development flow.
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### Decreasing agent time-to-awesome with improved context
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