Earl Hayes

Staff / Principal engineer

Earl Hayes

I own products end to end — architecture, store release, and the CI that keeps it alive.

Lately that includes the internal AI tooling other engineers run — and rebuilding my own delivery around it.

[TWO SENTENCES OF POSITIONING: the specialty, the differentiator, and the kind of problem Earl is the right person for.] D2 fixes the shape — .NET and Azure depth, cross-platform breadth, AI-assisted delivery — but the sentences are Earl's to write. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore.

Résumé Case studies

Scope

Reach and consequence

To a hiring committee, volume answers "how much did you do" and scope answers "how far did your judgment reach". These are the second question.

Selected work

Decisions, argued in full

Each one states the situation, the constraints, the decision, the tradeoff, the outcome and the retrospective — including the parts that did not go well.

Independent Placeholder

AI tooling engineers actually run

[ONE SENTENCE: what the tooling does, who runs it, and what it removed from the working week.] Lorem ipsum dolor sit amet, consectetur adipiscing elit.

  • LLM tooling
  • AI agents
  • Python
  • CI/CD

Day-job scope · Shipped artifact Placeholder

A platform migration under a running product

[ONE SENTENCE a hiring manager can read on a card: what shifted, how far it reached, and what it cost.] Sed do eiusmod tempor incididunt ut labore.

  • .NET MAUI
  • Xamarin
  • C#
  • Azure DevOps

Day-job scope Placeholder

Architecture other teams build on

[ONE SENTENCE: what the foundation is, who adopted it, and what starting from it changed.] Ut enim ad minim veniam, quis nostrud exercitation ullamco.

  • .NET MAUI
  • C#
  • SQLite
  • Dependency injection

Shipped artifact Placeholder

Building the thing nobody else would

[ONE SENTENCE: what was built, why it had to be built, and what shipping it alone proves.] Duis aute irure dolor in reprehenderit in voluptate velit.

  • C
  • Linux
  • Reverse engineering

AI in practice

Two claims, kept separate

Influence

Tooling other engineers run

Internal AI tooling and agents, built and shipped as something [N] engineers use as part of their normal workflow. [WHAT IT DOES, IN ONE LINE.] It is a concrete artifact rather than an approach, which is why it is the evidence this section leads with.

Throughput

My own delivery, rebuilt around it

AI-assisted development substantially changed what I can ship alone. [TASK] went from [BEFORE] to [AFTER]; [TASK] from [BEFORE] to [AFTER]. Stated as before-and-after because that is what was actually observed — no multiplier, and no claim that the practice spread beyond me.

Range

Shipped, outside the day job

Store titles across three platforms, web applications, open source, and driver work written because a vendor would not supply it. Evidence of execution rather than of scope.

Stack

Depth, breadth, and delivery

AI & LLM

  • LLM tooling
  • AI agents
  • AI-assisted development
  • Internal developer tooling
  • Review of generated code

Depth

  • C#
  • .NET
  • .NET MAUI
  • Xamarin
  • ASP.NET Core
  • Azure

Breadth

  • TypeScript
  • React
  • Node
  • Python
  • C
  • SQL

Delivery

  • CI/CD
  • Azure DevOps
  • GitHub Actions
  • App Store
  • Google Play
  • Microsoft Store

Practice

  • Architecture review
  • Mentoring
  • Onboarding & docs
  • Technical writing

Résumé

The page and the PDF are generated from the same data, so they cannot disagree. No form and no email gate — that is a lead-capture pattern, and this is not a sales page.

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Contact

Get in touch

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