AI-assisted coding tools are becoming part of everyday development workflows. From IDE assistants to chat-based helpers, many teams already rely on them to write, refactor, and review code. Yet real-world usage often reveals trade-offs that are not obvious in demos or marketing materials.
This webinar takes a practical, experience-driven look at how AI tools are actually used in software development today, where they deliver measurable value, where they fall short, and what engineering teams should consider before relying on them at scale.
Rather than focusing on specific vendors or tools, the session explores tool-agnostic patterns, workflow implications, and architectural considerations observed in real projects.
What we’ll cover:
- Common AI coding tools and how teams use them in practice
- Where AI fits in the coding lifecycle, and where it doesn’t
- Productivity gains: what can be measured versus what is only perceived
- Integrating AI into existing development workflows (local dev, PRs, CI)
- Security, compliance, and intellectual property considerations
This session is designed for teams reviewing their current use of AI in development or considering wider adoption. It will help you understand which coding tasks benefit
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AI-assisted coding tools are becoming part of everyday development workflows. From IDE assistants to chat-based helpers, many teams already rely on them to write, refactor, and review code. Yet real-world usage often reveals trade-offs that are not obvious in demos or marketing materials.
This webinar takes a practical, experience-driven look at how AI tools are actually used in software development today, where they deliver measurable value, where they fall short, and what engineering teams should consider before relying on them at scale.
Rather than focusing on specific vendors or tools, the session explores tool-agnostic patterns, workflow implications, and architectural considerations observed in real projects.
What we’ll cover:
- Common AI coding tools and how teams use them in practice
- Where AI fits in the coding lifecycle, and where it doesn’t
- Productivity gains: what can be measured versus what is only perceived
- Integrating AI into existing development workflows (local dev, PRs, CI)
- Security, compliance, and intellectual property considerations
This session is designed for teams reviewing their current use of AI in development or considering wider adoption. It will help you understand which coding tasks benefit from AI assistance, how to integrate these tools into existing workflows, and what to watch for from a quality, security, and maintainability perspective.
CIGen | AI agent development services | AI strategy consulting | Azure consulting & development
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