Leveraging AI and Incident Transparency for Software Engineer Growth

Growing Yourself as a Software Engineer, Using AI to Develop Software

Suhail Patel at QCon London 2025 highlighted how sharing work and owning incidents drive growth. He cited that 80% of engineering work is derivative, yet transparency turns challenges into learning opportunities.

Why This Matters

Ideal software development assumes perfect execution, but real-world projects face inevitable failures. Normalizing incidents—rather than hiding them—builds trust and fosters systemic learning. Patel noted that unaddressed issues erode team credibility, while transparent resolution can become a “positive advertisement” for engineering practices. The cost of poor incident management includes repeated errors, lost trust, and missed opportunities for collective improvement.

Key Insights

• “80% of engineering work is derivative,” said Patel, emphasizing collaboration over originality.
• “Sagas over ACID” for distributed systems, as incident resolution requires flexible, context-aware workflows.
• Monzo’s static analysis tools and API-scope guardrails demonstrate how AI integration can be secured through deliberate design.

Practical Applications

• Use Case: Internal unconference-style talks at Monzo to foster peer feedback on draft documentation.
• Pitfall: Dismissing AI tools due to imperfect outputs risks missing opportunities for automation, without proper guardrails.

References:

• https://www.infoq.com/news/2025/12/develop-software-AI/