Einblicke aus erster Hand in die Welt der industriellen IoT-, Daten und digitalen Lösungen.
Effective AI-assisted development depends less on clever prompts and more on the engineering practices around the agent. Clear context, a repeatable spec → grill → plan → implement → verify workflow, and strong review gates help teams catch avoidable failures before they become rework. Agents tend to fail in recognizable ways, so teams need current documentation, reusable skills, and deliberate safeguards around planning, implementation, and review. The real leverage comes from building the scaffolding around AI: context curation, verification, documentation, and human judgment.
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AI coding agents have not removed the need for software developers, but they have changed where developer judgment matters most. Less effort goes into typing implementation code, and more effort moves into writing clear specifications, steering agent work, and reviewing the results critically. This shift makes product clarity, technical intent, review culture, and verification more important than ever. The teams that benefit most from AI agents are not the ones generating the most code, but the ones most disciplined about intent, context, and quality.
Helen is transitioning from combustion-based energy production to a carbon-neutral system by 2030 and aims to end all combustion by 2040. To support this shift, Helen partnered with Brightly to develop a robust, scalable data platform that enables real-time monitoring, forecasting, and optimisation across their energy infrastructure. This blog post describes our partnership and the solution we have built together.
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If you’re attending the Data Innovation Summit this year, I’d love to see you there. Whether you’re exploring your next move in data and AI or just want to trade ideas, please come by and say hi. You can meet our team at booth A2, join our session with Helen on district heating, or book a 1:1 meeting to talk more in-depth about your goals.
At Santen Pharmaceutical, Brightly designed and implemented ChatAIRI, a generative AI tool that enables quick analysis of a vast amount of regulatory data. Read more about how we used AI to tackle a real-world problem efficiently.
Brightly joins the LifeFactFuture research program to lead the Technology Excellence Work Package in a consortium of university entities, leading life science manufacturers as well as data and technology companies.
Gemäß unseren Plänen zur Expansion in die DACH-Märkte haben wir im März 2024 ein Büro im Herzen Mitteleuropas eröffnet.
Software testing is the unsung hero of the various development disciplines. Often the testing is seen as ‘Complex!’ ‘Time-consuming!’ and ‘Tedious!’ But as a systematic part of your development processes, it makes developers’ work smoother, easier, and cost-effective while making your product solid, bug-free and future-proof. Here are some ways to leverage testing to improve your product and help your developers do their best work.
Gemäß unseren Plänen zur Expansion in die DACH-Märkte haben wir im März 2024 ein Büro im Herzen Mitteleuropas eröffnet.
The hype is strong with AI. As we're bombarded with AI-related topics, it might seem imperative to move quickly, but it's equally important to ensure that we're solving the right problems. Read more to learn how use a problem-solving mindset to make your AI project successful.
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Modern data solution development has surprisingly many similarities with the innovation process. In this blog, I describe how to recognize innovation phases when developing data and analytics cases.
This blog post delves into the application of modern AI for extracting meaningful insights from the turmoil of social media discourse. We showcase this technique by examining the social media conversations about the ongoing labor market reforms and political strikes in Finland.
