AI agents are transforming software development faster than many anticipated just a year ago. Over the past year, we have trained development teams and organizations in agentic development, and in doing so, we have observed that the biggest challenges are no longer technological. Competitive advantage is derived from the ability to envision the new, build secure operating models, and master the orchestration of agents as part of daily team routines.

Creative professionals need to pause from time to time and make space for experimentation. The best way to understand new tools is to use them for open-ended exploration of ideas that genuinely interest you. Kipinä's Friday hackathon comprised four hours free of specs, backlogs, or predefined problems—just an opportunity and the curiosity to see what happens when we combine years of expertise with modern AI tools.

Locally hosted AI gives businesses greater control, enhanced security, and predictability in leveraging artificial intelligence. This blog explores three key insights: why maintaining your own environment reduces risk, how models maintain stability, and why the best solutions stem from combining local and cloud-based AI deployments.

Kipinä Software originated five years ago from four core ideas: the best team wins, appreciation attracts top talent, well-functioning experts create value for clients, and meaning alongside balance are at the heart of business. Born from these concepts, the company has grown into a community of 40 experts, achieving high customer satisfaction and B Corp certification – but what matters most is not growth or the numbers, but how we got here and why these original beliefs are more relevant today than ever before.

Kipinä is now a Certified B Corp. The international B Corp certification reinforces our commitment to responsible digital development, transparent business practices, and sustainable software operations. This certification makes tangible how we combine technology, business objectives, and long-term impact — in a measurable way evaluated by a third party. Read what the certification means for our clients and explore our 2026 sustainability report.

In theory, closed AI models running on external servers would be enough. In reality, organizations must consider risks related to information security, geopolitics, bias, service availability, and cost control. One practical way to gain more control is running and fine-tuning open-weight models on your own hardware. In this post, Jari shares what it took to build and run a local AI workstation at Kipinä — from key decisions to real-world hurdles.

Kipinä Breakfast Club brought together 40 business leaders and digital decision-makers to discuss artificial intelligence, cybersecurity, and the future of digital development. The discussion highlighted five key themes: trust as a competitive advantage, the role of humans in the age of AI, psychological safety, resilience, and structures that enable new value—based on the Collective Vision 2026 mindset.

In the rapidly evolving landscape of technology, we are forced to ask ourselves a difficult question: In one word, what human skill is the most crucial in the age of AI?

As we’re heading into 2026, businesses must prepare for a future where humans and machines collaborate rather than compete. But with AI becoming exponentially better, why should humans keep learning at all?

AI can write code in a matter of hours, but comprehension and security do not materialize just as quickly. This lightweight experiment revealed how AI-driven software development can introduce critical vulnerabilities if best practices are compromised – and why the human role in understanding the codebase remains indispensable.

The Nordic Business Forum 2025 provided guidelines for the future. We picked up four insights on technology, culture and leadership - read the Kipinä round-up.

Agentic coding is revolutionising software development. When combined with documentation, test-driven development and quality management, AI agents can accelerate coding and deliver sustainable business growth. The Artificial Septelligence event delved into real-world examples of how AI is transforming everyday software development.

The next wave of artificial intelligence demands more than just cutting-edge technology: it requires precise problem definition, high-quality data, business-driven implementation, robust security, and a human-centric approach alongside technology. Kipinä's experts outline five key perspectives to ensure your AI solutions are genuinely scalable, secure, and impactful.

Artificial intelligence has been utilized in digital solutions for a long time, but the current pace of advancement is exceptionally rapid. Kipinä's CTO Jari Huilla pauses to ask: What lies at the root of today's challenges regarding the limited context windows of large language models? Take a look under the hood at the mathematical boundary conditions of the transformer architecture and discover how to navigate these constraints now and in the future.

Empathy, ego, and artificial intelligence – what happens when humans dare to be incomplete in the presence of AI?
Agile Coach Arto Kellokoski explores the interplay between artificial intelligence and humanity in his blog. He writes about psychological safety, the impact of the ego on decision-making, and how AI can act as an emotional sounding board – supporting reflection and presence, not just efficiency.

There is a lot of talk about AI solutions, but less about what they are actually built on. The answer is simple: data. And not just any data, but high-quality, reliable, and business-driven data.

Antti Rintala, a consultant at Kipinä, has outlined in his blog series the foundation required to leverage artificial intelligence. In this summary, we compile key perspectives that help build a solid foundation not only for AI solutions, but also for sustainable data-driven management.

An AI solution often sounds like it involves a massive amount of mathematics, black boxes, and consultant jargon. But when you look at it from a practical standpoint, building an AI product is ultimately not that mystical. It requires the same thing as any successful product: a clear problem, a bold vision, and a great team.

In this blog, I discuss two very different customer cases at Kipinä – and what we learned from them about building an AI product. The first story starts from a doctor's everyday life. The second stems from a global objective to make ESG measurable.

Kipinä Software is growing and evolving, and now our team of top-tier professionals is expanding further: Jari Huilla will start as Kipinä's Chief Technology Officer (CTO) at the beginning of April.

Jari's exceptional journey into technology began with coding at the age of 9, and his professional career kicked off impressively at age 15 at the Nokia Research Center. More than 20 years have passed since then, encompassing entrepreneurship, startups, growth companies, projects ranging from small to large, and roles from coder to leadership positions.

Otava places a strong emphasis on accessibility, viewing it as an integral part of application development on par with any other phase of the engineering process. Therefore, as a developer passionate about accessibility, it has been remarkable to participate in building Otava's new digital learning platform. Read our blog to learn more about how accessibility has been woven into the core of Otava's service development.

Every developer recognizes the risks posed by time constraints, pressure, and high personal standards when relying on something—such as a third-party library, an out-of-the-box solution, or a colleague's recommendation—that they do not fully understand. Attending the annual AWS re:Invent technology conference in Las Vegas truly opened my eyes to my responsibility as a developer when utilizing AI-generated code.

“As developers and clients, do we sufficiently recognize the ongoing race between AI and cybersecurity in software development? Do we acknowledge the risks of tight schedules and ever-accelerating momentum?”

The planning and preparation phases of digital projects are invariably challenging and time-consuming. Complex architectures and solutions requiring deep technical expertise often become a source of headaches, introducing a sense of uncertainty into the procurement process. At worst, the process is fueled by the most toxic element of all—hurry. How do you choose the right partner for a digital development project? What external expertise is required? What will the total cost be?