Introduction
The IT industry has always evolved rapidly. We moved from client-server systems to web applications, from monoliths to microservices, from data centers to cloud computing, and now into the age of Artificial Intelligence.
Alongside technological changes, another challenge has always existed inside organizations: people, roles, expectations, recognition, and workplace politics.
Developers sometimes feel that project managers receive credit for technical work. Testers may feel undervalued compared to developers. Support engineers often solve production crises but remain invisible. Managers face pressure from business leaders while balancing delivery commitments. Businesses pursue profitability and utilization targets, which can sometimes create tension between people and performance metrics.
The arrival of AI has amplified these concerns:
- Teams are expected to deliver more.
- Productivity expectations continue to rise.
- Technical assessments still emphasize syntax and memorization.
- Professionals worry about remaining relevant.
- Some fear replacement by AI tools.
The future of IT, however, is not about one role winning over another. It is about teams learning to work together while leveraging AI effectively.
Every Role Exists for a Reason
A software product succeeds because multiple disciplines work together.
Project Managers
Responsibilities:
- Scope management
- Stakeholder communication
- Risk management
- Budget management
- Timeline management
- Escalation handling
Good project managers remove obstacles.
Poor project management occurs when:
- Status reporting replaces leadership.
- Credit is centralized.
- Team contributions are not recognized.
- Visibility becomes more important than delivery.
Developers
Responsibilities:
- Solution design
- Coding
- Performance optimization
- Defect fixing
- Technical innovation
Developers create the software, but software alone does not create business value without successful delivery.
Test Engineers
Responsibilities:
- Quality assurance
- Test automation
- Regression testing
- Risk identification
- Customer experience validation
Many production failures are prevented by good testing teams.
Support Engineers
Responsibilities:
- Production support
- Incident management
- Root cause analysis
- System stability
- Customer satisfaction
Support teams often work during outages, weekends, and critical incidents.
Product Managers and Business Teams
Responsibilities:
- Understanding customer needs
- Defining priorities
- Market analysis
- Revenue growth
- Product strategy
Without customers, there is no software.
Why Politics Happens
Politics often emerges because organizations reward:
- Visibility
- Presentation
- Individual recognition
- Short-term results
instead of:
- Collaboration
- Knowledge sharing
- Team outcomes
- Long-term value
Common frustrations include:
- Managers presenting team work as their own.
- Teams competing for recognition.
- Credit flowing upward.
- Employees feeling invisible.
The problem is rarely the role itself.
The problem is misaligned incentives.
AI Has Changed Expectations
Many organizations simultaneously say:
Use AI to become more productive.
While also saying:
Deliver more with the same or smaller teams.
Employees may experience:
- Increased pressure
- Constant learning expectations
- Frequent technical assessments
- Fear of becoming obsolete
The reality is:
AI increases productivity, but it also changes what skills are valuable.
Why Memorizing Syntax Matters Less
In the past:
- Developers memorized APIs.
- DBAs memorized SQL syntax.
- Testers memorized commands.
Today:
- AI can generate code.
- AI can write SQL.
- AI can suggest test cases.
The real value now lies in:
- Problem solving
- System thinking
- Architecture
- Business understanding
- Decision making
Knowing every method in Java Streams is less important than understanding:
When should Streams be used?
Similarly:
Remembering Spring annotations matters less than understanding dependency injection.
The Future Skills for Every Role
Common Skills Required Across All Roles
1. AI Literacy
Everyone should understand:
- Prompt engineering
- AI limitations
- AI validation
- Responsible AI usage
2. Communication Skills
Clear communication reduces politics.
People who explain problems well often influence decisions positively.
3. Problem Solving
AI generates answers.
Humans identify the right problems.
4. Data Interpretation
All roles increasingly rely on:
- Metrics
- Dashboards
- Analytics
- KPIs
5. Collaboration
Future organizations reward:
- Cross-functional work
- Knowledge sharing
- Mentoring
How Developers Stay Relevant
Developers should focus on:
- Architecture
- Design patterns
- Cloud technologies
- AI-assisted development
- System design
- Performance optimization
Learn:
- Spring Boot
- Microservices
- Kubernetes
- Cloud platforms
- AI coding assistants
AI can generate code.
Developers still decide:
- What to build
- Why to build it
- How to integrate it
How Testers Stay Relevant
Modern testing requires:
- Automation
- API testing
- Performance testing
- AI-assisted testing
- Test data generation
Learn:
- Selenium
- Playwright
- Postman
- JMeter
- AI-based test generation
Quality engineering is becoming more important, not less.
How Project Managers Stay Relevant
Modern project managers must become:
- Delivery leaders
- Risk managers
- Facilitators
- AI-enabled planners
Learn:
- Agile metrics
- Data-driven management
- AI productivity tools
- Technical fundamentals
The future PM asks:
How can I remove obstacles?
rather than:
What is the status?
How Support Engineers Stay Relevant
Support engineers should develop:
- Observability skills
- Monitoring
- Root cause analysis
- Automation
- Cloud operations
Learn:
- Grafana
- Prometheus
- Splunk
- Kubernetes
- Incident management
Production knowledge is highly valuable.
How to Reduce Politics
1. Make Work Visible
Maintain:
- Architecture documents
- Design decisions
- Technical proposals
- Delivery metrics
Visibility reduces attribution problems.
2. Share Credit Publicly
Good leaders say:
The team achieved this.
Not:
I delivered this.
3. Document Contributions
Maintain:
- Sprint accomplishments
- Technical achievements
- Production improvements
This supports fair evaluations.
4. Avoid Information Silos
Knowledge hoarding creates politics.
Knowledge sharing builds trust.
5. Mentor Others
People who help others become influential without politics.
AI Will Not Replace Teams
AI is extremely good at:
- Generating code
- Writing documentation
- Creating test cases
- Summarizing information
AI struggles with:
- Organizational context
- Business priorities
- Human relationships
- Leadership
- Negotiation
- Accountability
Future teams will likely look like:
- Smaller teams
- Higher productivity
- Stronger collaboration
- AI-assisted workflows
Recommended Training for Everyone
| Skill | Developer | Tester | PM | Support |
|---|---|---|---|---|
| AI Tools | ✓ | ✓ | ✓ | ✓ |
| Prompt Engineering | ✓ | ✓ | ✓ | ✓ |
| Agile | ✓ | ✓ | ✓ | ✓ |
| Cloud Basics | ✓ | ✓ | ✓ | ✓ |
| Communication | ✓ | ✓ | ✓ | ✓ |
| Data Analysis | ✓ | ✓ | ✓ | ✓ |
| Security Basics | ✓ | ✓ | ✓ | ✓ |
Recommended Learning Paths
Developers
- Java 17+
- Spring Boot
- Cloud
- AI-assisted coding
- System Design
Test Engineers
- Automation
- API Testing
- Performance Testing
- AI-based testing
Project Managers
- Agile Leadership
- Product Thinking
- Metrics
- Technical Fundamentals
Support Engineers
- SRE concepts
- Monitoring
- Automation
- Cloud Operations
Final Thoughts
Technology changes every few years.
Roles evolve.
Tools change.
AI will continue to transform the workplace.
However, organizations still succeed because people:
- Solve problems.
- Build relationships.
- Share knowledge.
- Help each other.
- Deliver value together.
The future belongs neither to managers nor developers nor AI tools.
It belongs to teams that combine:
- Technical skills
- Business understanding
- Collaboration
- Continuous learning
The most valuable professional in the AI era is not the person who remembers the most syntax.
It is the person who learns continuously, adapts quickly, helps others succeed, and uses AI as a partner rather than viewing it as a competitor.