Using GitHub Copilot for Pull Request Reviews: Benefits, Best Practices, and Real-World Experience

Jonny Hackett Agentic AI & AI-Accelerated Development, All Industries, Articles, Artificial Intelligence, Testing Leave a Comment

In this article, I’ll share how I’ve been using GitHub Copilot for PR reviews, where it provides the most value, where it falls short, and the best practices I’ve found for incorporating it into an effective code review workflow.

While most developers think of Copilot as a tool for assisting in writing code (Copilot Chat) or autocompleting code (Copilot plugin in your favorite IDE), itโ€™s during pull request reviews that I find Copilot the most impressive. GitHub Copilot can analyze code changes, generate summaries, identify potential issues, and even suggest fixes before another developer ever opens the PR…

synopsis image of delphi to .net ai code conversion delivered 40% faster than deadline

How We Used LLMs to Rewrite a Legacy Delphi Application in C#

Evan Sanning .NET, Agentic AI & AI-Accelerated Development, All Industries, Articles, Artificial Intelligence, Generative AI & LLMs, Modernization Leave a Comment

We rewrote a legacy Delphi (Object Pascal) application into a .NET C# service worker in three months, beating a five-month deadline for a client in the healthcare software space.

Here’s what actually made that possible and the pitfalls we hit using LLMs along the way.

Blog post header of what is actually working in real production systems in AI-assisted or AI-accelerated enterprise development

Enterprise AI-Assisted Development: How Teams Get Repeatable Results

Keyhole Software Agentic AI & AI-Accelerated Development, All Industries, Articles, Artificial Intelligence Leave a Comment

Learn how enterprise teams use AI coding tools with guardrails, governance, and workflow structure to improve speed without sacrificing code quality or control.

Many organizations are experimenting with AI coding tools, but fewer are measuring or achieving consistent, repeatable results from enterprise AI-assisted development in practice. The difference is not the tools. It is how engineering teams operationalize them day to day.

These observations are drawn from internal engineering roundtables and hands-on client work, where teams are actively working through how AI fits into production development workflows today.

Enterprise AI development ecosystem visualization showing connected systems and architecture

Inside Anthropicโ€™s Emerging Partner Ecosystem: What Keyhole Is Seeing and Applying in Enterprise AI

Keyhole Software Agentic AI & AI-Accelerated Development, All Industries, Articles, Artificial Intelligence, Consulting, Spring Leave a Comment

Keyhole Software was selected to participate in Anthropicโ€™s emerging ecosystem and invited to the 2026 Partner Summit. Here is what we are seeing firsthand and how we are applying it in real enterprise AI development and software delivery. AI vendors are no longer just releasing models. They are building ecosystems. Anthropic is at the forefront of this shift, building an …

AI-assisted software development workflow showing planning mode, prompting, multi-agent execution, testing, and merge process

AI Coding Tools in Enterprise Software Delivery: An Architectโ€™s Workflow

Zach Gardner Agentic AI & AI-Accelerated Development, All Industries, Articles, Artificial Intelligence, Videos 1 Comment

AI coding tools are everywhere โ€” but most teams are still experimenting in isolated demos. In this architect-level walkthrough, Keyhole Software Chief Architect Zach Gardner shows how we use tools like Claude Code in real, production delivery: with planning mode, constraints-first prompting, multi-agent workflows, and the governance required for enterprise environments.