We sat down with Byron McClain, Co-Founder of Rōnin Consulting and one of the architects behind our AI initiatives. The conversation explored what defines an actual AI agent, how companies can put agentic AI into practice, and why the future of AI represents more than just another wave of automation.
Realistically, many small businesses, as well as large enterprises, lack a developer on staff who has the time (or acumen) to take on a new AI project. In such cases, the responsibility to learn and implement AI often falls on an already stretched technical team that must also handle day-to-day operations.
Many companies jump into AI with big ambitions—often too big. This article explores why trying to solve everything with one massive AI project is a red flag and shares a smarter approach: starting small, building momentum, and scaling successful AI with clarity and confidence.
Rōnin Partner (and non-developer) Chuck Harris put Vibe Coding to the test by reviving an old passion project—a card-based battle game called Arena. With no formal dev background, he used AI to write over 4,000 lines of JavaScript and build a working prototype. His experiment proved that vibe coding is a powerful tool for rapid prototyping, when used within its limits.
This blog is a summary of a recent conversation between three Rōnins, where they provide AI answers to the most common questions they hear from clients—everything from deployment timelines and infrastructure to token costs and model selection
In a laid-back but insight-packed conversation, Julie Simpson, Marketing Manager at Rōnin Consulting, sat down with founding owner Ryan Kettrey to talk shop. They covered everything from dot-com-era nostalgia to modern Artificial Intelligence (AI) integration challenges.
Today, the question is no longer whether people are using AI but how they are using AI. As models become more powerful and access becomes easier, public AI isn’t just supporting tasks. It’s shaping decisions and entire industries.
The growth of AI agent technology will become very important for businesses in making informed, strategic decisions. This article will discuss top business considerations for implementing agentic AI and practical insights for applying this new technology into businesses.
We specialize in helping clients with large, complex codebases, but one of our biggest challenges is efficiently onboarding these clients. However, since we started using Claude Code, we have been able to streamline and optimize our processes.
Jumping straight into full-scale AI implementation without a Proof of Concept (POC) is one of the fastest ways to burn money, time, and trust. If you’re serious about AI, consider starting with a POC. If you’re not convinced, keep reading, and by the end of this article, you will be!
