AI-201
AI for High-Performing Software Teams
How We Conduct Training :
O&B Headquarters (3F Carlos J. Valdes Building, 108 Aguirre, Legazpi Village, Makati City)
Client's premises (Private sessions available with a minimum number of participants)
Course Overview
Many organizations invest in AI tools but fail to see improvements in delivery speed, product value, or team performance. This creates an AI Effectiveness Gap: increased activity with limited business impact and rising technical debt. This workshop closes that gap in a wholesome way. We don’t teach people how to use tools; we help teams transform how they work—using AI as a high-speed accelerator for the entire Software Development Lifecycle (SDLC).
All this in a safe space to experience what works (and what doesn’t) before implementation.
AI handles the labor; your professionals provide the domain expertise and validation. We don’t teach you to chase the latest AI star, no FOMO. We give you a stable, role-based methodology that remains effective even as LLM models change.
Learning Outcomes
- Knowing the basics of how to use AI context engineering in the whole SDLC and with the coordination between teams in mind
- Learning about the limits of AI and how to work around it
- Understanding how to use existing roles to great effect in coordination with the whole team and how this will save you time and improve your output quality
- Documentation is now a breeze and becoming really useful and easy to keep up to date.
Course Outline
- Vibe Coding and Prompt Engineering explained
- Real world workflows in the SDLC and what’s good with them
- What helps and what hinders performance?
- Going beyond vibing and optimizing prompts by using context engineering
- Establishing role-based AI workflows; reducing friction between hand-offs
- Sustainable coding practices (for Developers)
Software and Hardware Requirements
Your own laptop, access to a paid AI account if possible (Anthropic, OpenAI, Gemini, etc.)
FACILITATOR: PATRICK SCHELLER
Seasoned Head of Development and Infrastructure with more than three decades of experience across diverse industries and technology landscapes. Extensive expertise in leading complex software development initiatives, modernizing technology stacks, optimizing SDLC frameworks, and building high-performing engineering teams.
Over the past year, he has dedicated significant time to researching and experimenting with the integration of artificial intelligence into professional software development workflows. His work focuses on practical applications of AI in engineering environments, including developer (and other roles) productivity, AI-assisted coding, workflow automation, and the integration of AI tools into existing development processes.
Register to AI-201 now
Training Schedules :
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