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Bitrise is one of the few global AWS technology (software) partners who build on top of the Amazon EC2 Mac compute offering. We are proud to announce we have received recognition of our solution quality and expertise from AWS for our mobile-first CI/CD product, Bitrise on AWS.

At its simplest, AI debugging automates repetitive coding tasks like searching logs, reading stack traces and comparing sessions. But good AI debugging is a much more challenging concept that relies on focused context, runtime evidence and structured investigation paths. In this post we’ll show you how to debug with AI, not just productively but also responsibly. Let’s get into it.

‍ Every CFO has looked at the headcount report and asked the same question. Why does it take twelve people and four tools to do something that feels, on paper, like it should take three? The honest answer is usually not laziness or bloat. It is a coordination tax. Someone has to read an email, decide what it means, open three other systems to check context, type a response, update a tracker, and notify two other teams. None of that is hard work.

The most useful piece of software we came across last quarter never left someone's laptop. An operations lead at one of our enterprise clients built herself an inventory reconciliation dashboard. No ticket, no sprint, no engineer involved. She described the workflow to an AI agent one evening and had something working by the next morning. A problem her team had been raising for over a year, solved by someone who has never written production code in her life.

Model Context Protocol allows AI models like Claude to communicate with the outside world. But MCP debugging has been one of our steepest learning curves at Bugfender. Several different layers need to work together at the same time and if one thing breaks, it can scupper the whole workflow. That’s why we’re here today. To pass on hard-won knowledge, so you can jump the curve.

‍ ‍Satya Nadella said it plainly: "AI is not a feature. It is the platform shift of our generation." And he is right. Whether you are a $50 million mid-market firm or a $5 billion enterprise, the mandate from the board is the same: automate, optimise, and scale with AI. But here is the uncomfortable truth that most AI vendors will not tell you. Technology is seldom the bottleneck.

If you are thinking about applying for an Engineering role at Bitrise (which we highly encourage), you probably want to know what happens after you hit that "apply" button. This post walks you through every step. It helps you decide whether we're the right place for you, gives you clarity before the interviews, and sets you up for success even before you apply.

Xcode debugging tools integrate smoothly with the rest of the Xcode ecosystem and offer myriad benefits to developers, including powerful breakpoints and source-level visibility. This guide will help you unlock them. We’ll equip you with the knowledge to: If you’ve come for a specific piece of knowledge, here’s the full list of contents so you can go straight there.

As many other data teams do, we have a dedicated Slack channel (#data) where the whole company can ask data-related questions that get picked up by a designated, weekly-rotated data analyst (data mage). It can become tiresome quickly as the questions are fairly repetitive and it takes away precious time from other high-impact tasks. The team built clean, well-documented marts and reports in Metabase that are used regularly, but these were still missing something that makes reporting truly self-service.