In our latest knowledge-sharing session, Rajko Bacic demonstrated and defined best practices on how Intelligent Agents and MCP Servers can transform the way we develop software, not by replacing engineers, but by empowering them to deliver faster and smarter.

🚀 From Tasks to Intelligent Automation
Rajko showcased how agents can analyze, plan, and execute development steps autonomously, from reading Jira tickets and analyzing API specs to proposing implementation plans and generating tests.
This approach turns AI from a passive code assistant into an active collaborator capable of accelerating delivery while maintaining quality.

🧠 Context That Matters: MCP Servers
By integrating MCP Servers into the engineering workflow, teams gain something critical, shared context.
These servers connect systems like Jira, Confluence, and Bitbucket, allowing AI to access architecture documents, requirements, and code history in real time.

The result:
✅ Lowering misunderstandings between business and development
⚡ Faster planning and implementation
🧩 Better code alignment with architecture and team standards
💼 Business Benefits at Scale

When used strategically, these tools don’t just improve coding, they improve business outcomes.

They shorten delivery cycles, reduce review overhead, and make every hour of engineering more impactful.

That’s how organizations can increase efficiency without increasing headcount, and ensure every team member works with the same clarity and precision.

🔒 Human Expertise at the Core
As Rajko highlighted, the key is not blind automation, but orchestration, knowing when and how to use AI effectively.

The engineer remains the decision-maker, the AI just clears the path.

At Brighting, we believe that AI-assisted engineering is more than a technical evolution, it’s a new way of doing business.