Why the Future of Automation Lies Not in the Number of Developers, but in the Accessibility of AI Agents Traditional automation requires time, budget, and the involvement of IT teams. But what if every employee could automate their own processes independently? Agentic Workforce is transforming the very principle of how work is organized. People set goals, agents perform tasks, and the platform provides the tools, access, security, and control. I’ll share our experience building and implementing the Agentic Workforce product in an enterprise organization, the architecture of the agent platform, managing digital agents, and how we envision the transformation of corporate automation.

Imagine two mission-critical systems exchanging sensitive data, when either system, or the network between them, could be compromised. We’ll build the integration architecture step by step, introducing trust boundaries, identities, access control, data minimisation, encryption, and other security controls that limit blast radius. We’ll show how layered architectural decisions can keep systems secure and resilient even when individual controls fail.

Over the past few months we have been building one of the subdomains of our lending project, with most of the code written by AI under architectural supervision: 100 stories in 26 days, 12 repositories, ≈218,500 lines of code, 44 ADRs, including PCI DSS and National Bank of Ukraine requirements, where the cost of an architectural mistake is quite high. This experience changes the way we look at the architect's work when planning project decisions. Although AI tools help automate and accelerate development, in fact it is the human who remains responsible for the result. By default, AI does not think strategically and often picks the simplest implementation path, which can lead to negative outcomes in the future unless a human explicitly describes the strategy when setting the task. So the more autonomy we want from AI, the higher the qualification required of the human beside it: there remain decisions that cannot be delegated, no matter how smart the next model gets. Modern methodologies (ADR, quality gates, ATAM, TOGAF) are transforming in the age of AI and make it possible to achieve a higher-quality result with higher autonomy. That is what we will talk about in my presentation. This talk is for architects, team leads, and senior engineers who have already tried AI and strive to increase the effectiveness and autonomy of their teams.