Most teams have adopted AI at exactly one point in the lifecycle — a developer with an autocomplete plugin. That's the smallest win available.
Your personal join link arrives on WhatsApp.
The bigger one is everything around it: understanding a service nobody remembers writing, working out what breaks before you change it, generating tests that target real risk, keeping documentation true, reviewing for security. These are the parts that eat the most time, and the parts where AI is least used.
This is a 90-minute session for experienced engineers on where AI genuinely helps across the SDLC, where it quietly adds risk, and how to tell the difference — with a live demonstration on a real codebase rather than a toy example.
Which stages AI helps at today, and which it doesn't
And what structure-aware retrieval does differently
False positives, silent regressions, and where review is non-negotiable
What can and cannot leave your network
A defensible starting position rather than a tool recommendation
Lead Mentor · Machine Learning, Generative AI & Agentic AI
Designs the curriculum and leads the hands-on labs, helping participants think through problems the way an AI engineer does instead of memorising tools.
Real recordings from our labs: running AI apps, code and measured results.
A lab project: FastAPI backend, Chroma vector store and Llama 3 via Groq, answering questions about LangChain documentation.
A lab notebook: a local FAISS knowledge base, a RAG pipeline on Groq LLMs, and RAGAS metrics to evaluate the answers. Shown at 2.5× speed.
Yes. Registration is free and there's nothing you have to buy.
No, but you do need real software engineering experience. This assumes you've worked on non-trivial systems.
That one is about building AI products for your users. This one is about applying AI to how your team builds software. Different audience, different outcome — some engineers care about both.
No. Tools appear in the demo, but the session is tool-agnostic and focuses on workflows that outlast any single vendor.
Yes, on a real open-source repository — not a toy example.
No. The consistent finding is the opposite: AI raises the value of engineers who understand systems deeply, and is unreliable in the hands of those who don't.
Yes, there's a live Q&A at the end.