10 posts tagged with "ai"

Ways of Working at the Speed of Thought​

Product talked to a BA. The BA talked to a scrum master. The scrum master scheduled a refinement. Engineers showed up, debated the shape of the feature, poked at the data model, estimated it, and dropped it into the backlog. Eventually — maybe next sprint, maybe next quarter, maybe never — somebody wrote the code.

That was the shape of enterprise software for two decades. We built elaborate coordination machinery around a single hard fact: writing the code was the slow, expensive, error-prone step. Everything else existed to protect that scarce resource.

That fact is no longer true. And most enterprises are still running the coordination machinery for a world that doesn't exist anymore.

AI Coding Tool Comparison 2026: Claude Code vs Cursor vs GitHub Copilot vs Windsurf​

I use multiple AI coding tools every day. Not because I'm indecisive — because different tools genuinely excel at different tasks. After a year of tracking my usage through PromptConduit and monitoring releases through Havoptic, I have a data-informed perspective on where each tool shines and where it falls short.

This isn't a surface-level feature checklist. It's an honest assessment from someone who ships production code with these tools daily, tracks their release velocity, and measures their impact on productivity.

Claude Code Hooks: A Complete Guide to Automating Your AI Coding Workflow​

If you've been using Claude Code for more than a week, you've probably noticed a pattern: you keep telling it the same things. "Run prettier after editing." "Don't touch the .env file." "Run the tests before you stop." These aren't complex instructions — they're rules. And rules shouldn't depend on an LLM remembering to follow them.

That's exactly what Claude Code hooks solve. They're deterministic automation that runs at specific points in Claude Code's lifecycle, executed by the harness itself — not by Claude. If you configure a hook to format code after every edit, it will format code after every edit. No exceptions. No "I forgot."

How to Measure AI Coding Assistant Productivity: A Framework for Engineering Teams​

Here's a question I get asked constantly: "How do you know if AI coding tools are actually making your team more productive?"

It's a fair question. Engineering leaders are investing real budget in Claude Code, Cursor, and GitHub Copilot seats. Developers are restructuring their workflows around these tools. But when someone asks for data — actual numbers on impact — most teams have nothing to show.

I've been working on this problem for over a year, first as an engineering leader trying to justify AI tooling investments at Georgia-Pacific, and then by building PromptConduit to close the analytics gap. Here's the framework I've developed for measuring what actually matters.

Havoptic: I Built a Visual Release Tracker Because I Couldn't Keep Up​

Here's a confession: I can't keep up with release notes. Claude Code, Cursor, Windsurf, Gemini CLI, Copilot CLI, Codex CLI, Kiro – they're all shipping at breakneck speed, and every week there's a new version with features that could change how I work. But reading through changelogs? My eyes glaze over by paragraph two. I'm a visual person. I need to see what changed, not read a wall of text about it.

That frustration is why I built Havoptic.

PromptConduit: Building Analytics for AI Coding Assistants​

Every day, I spend hours having conversations with AI coding assistants. Claude Code helps me debug issues, Cursor generates components, and Gemini CLI answers quick questions. But here's the thing: I had no idea what I was actually asking them. What patterns emerged from my prompts? Which tools got invoked most frequently? Was I getting better at prompting over time?

These questions led me to build PromptConduit.

Claude Code Template: Accelerating AI-Assisted Development​

The future of software development is here, and it's conversational. With AI coding assistants becoming increasingly sophisticated, the way we structure and approach development projects is evolving rapidly. Today, I'm excited to share the Claude Code Template – a comprehensive starter template designed to maximize productivity in AI-assisted development workflows.

AI Agents and the Future of Development: Lessons from a Hackathon​

What happens when you give a small team of developers one week, a pile of AI tools, and the audacity to think we could build something meaningful? This is our story from the KOLO AI Hackathon – a journey into what agent-led development might actually look like.

Building AI Teams with CrewAI​

Have you ever wished you could assemble a team of AI experts to tackle your projects? Imagine having a researcher who never sleeps, an analyst who processes data in seconds, and a writer who crafts perfect content – all working together seamlessly. This isn't science fiction; it's possible today with CrewAI.

AI Agents as Enterprise UI​

In the evolving landscape of enterprise architecture, we're witnessing a paradigm shift that could fundamentally transform how businesses interact with their applications. I've observed a compelling trend: the emergence of AI agents as direct intermediaries between users and data layers, effectively replacing traditional UI components. This architectural evolution promises to streamline enterprise applications while significantly reducing infrastructure complexity.