TLDR: Agentic AI is fundamentally changing the software development lifecycle (SDLC) by integrating autonomous agents with human intelligence. Bloomfilter Inc., in partnership with Celonis SE, has introduced solutions like ‘Celonis for the Software Development Lifecycle’ and ‘Celonis Agent Miner’ to create a process intelligence graph. This approach has enabled companies like Schaeffler AG to significantly improve workflow efficiency and customer experience, particularly in highly regulated sectors facing competitive pressures. The key lies in understanding and optimizing the interaction between AI agents and human teams.
Artificial intelligence, specifically agentic AI, is rapidly reshaping the software development lifecycle (SDLC), moving beyond traditional human-centric coding to a collaborative ecosystem of AI agents and human developers. This transformation is being spearheaded by companies like Bloomfilter Inc., which, in partnership with Celonis SE, is deploying agent-powered business solutions to modernize software development workflows.
Erik Severinghaus, co-founder and co-chief executive officer of Bloomfilter Inc., highlighted the dramatic shift in the industry, stating, “Three years ago, we thought of software development as carbon-based meat sacks banging paws on keyboards in order to make code happen. Well, think about how the world has changed now. You cannot model the software development process anymore if you can’t model how the agents and the humans are interacting.” This sentiment underscores the necessity of understanding the intricate interplay between AI and human contributions in modern software creation.
Bloomfilter recently unveiled ‘Celonis for the Software Development Lifecycle’ and ‘Celonis Agent Miner.’ These innovative tools are designed to combine the efforts of AI agents and human teams into a unified process intelligence graph. Michael Eichinger, head of PMT Software at Schaeffler AG, a prominent supplier of bearings and automotive parts, attested to the effectiveness of these solutions. According to Eichinger, these tools have been instrumental in identifying and addressing inefficiencies within Schaeffler’s workflows, ultimately leading to an improved customer experience.
Eichinger emphasized the importance of process understanding: “I would like to really understand how we are working … to improve and to increase the efficiency. The similarity is software but the way of working is really drastically different. We have to understand where we are. And if we know where we are, we can go in the direction to improve the right elements.” This highlights a strategic shift towards data-driven process optimization facilitated by agentic AI.
Both Severinghaus and Eichinger agree that observability – the ability to monitor and understand both the agentic and human elements within a company – is crucial for the future success of agentic AI. They pinpoint significant opportunities in highly regulated industries that are simultaneously under competitive pressure to evolve. Severinghaus explained, “The only way out of that box is to improve the process because you can’t strip the process down. We focus on the software development lifecycle use case but we do find that the industries where there’s regulatory and competitive pressure together really creates … a lot of demand for us.” This indicates that agentic AI offers a vital pathway for these industries to innovate while maintaining compliance.
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The collaboration between Bloomfilter and Celonis, as discussed at Celosphere 25, signifies a pivotal moment in the evolution of software development, promising smarter, faster, and more resilient software through continuous learning and adaptive autonomous systems.
