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Bio, Work & Ideas

Kyle Penfound

Conference affiliation: DAgger · 2025

Kyle Penfound is a solutions engineer at Dagger with more than a decade of experience in DevOps, platform engineering, and release engineering. He builds agentic continuous integration systems that give coding agents the same containerized environments, project-specific tests, and review requirements used to deliver production software.

In 2023, Penfound advocated writing CI pipelines as portable, testable code, replacing brittle, platform-specific YAML with reproducible workflows that run consistently on laptops and CI infrastructure. He subsequently extended that approach to AI agents: existing functions for building applications, running tests, and enforcing engineering standards become tools an autonomous contributor can use.

His greetings-api repository demonstrates agents that implement feature requests, open pull requests, incorporate review feedback, review proposed changes, and diagnose failing tests. Dagger modules and GitHub Actions connect these capabilities to the application’s existing delivery process.

  • Agent tool scoping: Agents need enough flexibility to solve unfamiliar problems without unrestricted permissions or an overwhelming tool inventory. If a project already specifies how tests run, an agent should receive that dedicated testing function instead of inventing shell commands.
  • Independent verification of generated code: Asking a model to run tests is insufficient; the surrounding workflow must execute those checks separately before accepting its changes. Container isolation protects local files, while execution traces reveal tool calls, failures, and opportunities to improve prompts or tool descriptions.
  • Automated contributions, accountable review: In his writing on AI-era continuous integration, Penfound argues that coding agents increase pressure on maintainers by accelerating contributions faster than qualified human review. Portable checks, documentation, linting, meaningful tests, and automated feedback can improve incoming changes without eliminating human responsibility.

At AI Engineer World’s Fair 2025, Penfound and fellow Dagger ecosystem engineer Jeremy Adams-Casañas demonstrated a GitHub issue-to-pull-request workflow in which a scoped agent inspects a repository, modifies code, runs existing tests, and submits changes for review.

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Key ideas

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Build a Dagger workspace that lets an agent edit and test a Vue application, then reuse that agent in a GitHub issue-to-pull-request workflow.

  • An agent needs somewhere to run
    0:27 ↗
  • Make the workflow portable
    4:10 ↗
  • Build the developer tools first
    10:49 ↗
  • Give the agent a focused workspace
    22:10 ↗
  • Define the assignment, environment and prompt
    30:34 ↗
  • Put the final test outside the agent loop
    39:59 ↗
  • Ask for a greeting change
    42:44 ↗
  • Inspect the trace, then preview before export
    48:56 ↗
  • Turn an issue into an assignment
    55:20 ↗
  • Run the agent when an issue is labeled
    58:43 ↗
  • Know what the guardrails do—and what they leave open
    1:03:48 ↗
  • Extend the environment with nesting and MCP
    1:08:24 ↗
  • Review the actual result and give it another turn
    1:11:59 ↗
  • Use the environment with other agent frameworks
    1:14:40 ↗
  • Explore in the shell, then decompose larger work
    1:18:37 ↗

References