AI-Agentic Development Workflow

For longer-running projects, AI-assisted development needs a repeatable workflow: how work is planned, what context is loaded, what gets documented, how progress is reviewed, and how the next session continues without starting from zero. The recurring challenges are context management, documentation, and orientation. Maintaining quality as projects grow requires treating the workflow itself as an engineering problem. About the speaker Vardan Arakelyan is a Software Engineer at Silvaco Inc, with a background spanning software development, QA engineering, and systems architecture. His practice with AI-assisted development is grounded in real engineering environments where workflow discipline and context continuity aren't optional extras, they're the difference between AI being useful and being noise. Who is this for?Developers with hands-on experience; juniors who are already building, mids and seniors looking to systematize their AI usage. If you've worked with AI coding tools and want to take it to the next level, this is for you. What you'll take away: