Spring @Transactional Explained
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This document discusses how transactions work with the Spring framework's @Transactional annotation. When a method marked with @Transactional is called, the transactional aspect will start a new transaction or join an existing one before calling the method. After the method completes, the transactional aspect will either commit or roll back the transaction based on whether any exceptions occurred during the method call.
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For decades, Germanys industrial strength has been built on engineering expertise. Precision manufacturing, rigorous processes, and deep technical know-how have been at the core of global industrial competitiveness. Agentic AI, however, is changing the rules.
Were no longer talking about AI as just another IT tool. Were looking at a fundamental shift in whoor whatmakes engineering decisions.
Agentic AI is becoming the engineer.
Were transitioning from CoPilot AIwhich assists human engineersto Agentic AI, which independently executes tasks and decisions. This shift is crucial because it moves AI beyond being a passive assistant and turns it into an active problem-solver that autonomously handles critical aspects of industrial workflows.
CoPilot AI helps humans by providing suggestions, detecting errors, and optimizing processes collaboratively.
Agentic AI works independently, executing tasks with minimal human intervention and owning decision-making processes.
Agentic AI systems will be built to achieve specific outcomes, such as optimizing workflows, processing vast amounts of sensor data, or making supply chain decisions in real-time.
AI is not just replacing software toolsits replacing entire roles and decision-making processes. The key question industrial leaders should ask is which roles will be automated? Today, the roles most likely to be automated satisfy these criteria:
1. Routine and repetitive tasks (e.g., quality control, data entry, scheduling)
2. Decision-making based on structured data analysis (e.g., demand forecasting, preventive maintenance decisions)
3. Tasks with clear objectives and outcomes (e.g., procurement optimization, logistics management)
4. Roles not requiring emotional intelligence or nuanced human judgment (e.g., factory-floor inspections, order processing)
While AI wont replace every engineering function, the roles it can automate will be deeply transformed.
AIs impact on industrial engineering will vary across the Design-to-Operate (D2O) lifecycle. Some phases will remain human-led, while others will see rapid automation.
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