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Workshop Proposal

From Prompts to Production: AI Engineering Mastery

AI-Accelerated Development, Self-Healing CI/CD Loops & Adaptive Tests. A decade of experience building hard-tech systems. Now an AI Engineer teaching teams how to ship faster with tools that actually work in production.

DurationHalf Day (4 Hours)
FormatLive Coding + Labs
AudienceEngineers, QA, DevOps & Leadership
Vipul Gupta

Vipul Gupta

AI Engineer building production agents. Previously shipped systems at Balena that saved $250K+ annually.

GitHub Star 2025Google Cloud Architect10 Years OSS
127+Technical Sessions Delivered
$270K+Saved in AI infra costs
45,000+People Educated

Expected Results

Based on implementations at Balena and teams trained. Measured outcomes, not projections.

40%
Faster Development
Feature request to production-ready code
55%
Faster Reviews
Code review cycles with AI-assisted checks
3-5x
Test Coverage
Automated test scenarios per sprint
35%
Fewer Bugs
Reduction in production incidents
80%
Tool Adoption
Engineers using AI tools daily at 90 days
$38K
Annual Savings
Varies by team size (10-50 engineers)

Learn from a Practitioner

Production-tested techniques from someone who builds AI systems daily, not just talks about them.

Vipul Gupta

Vipul Gupta

AI Engineer @ Command Code · Founder, Mixster · Ex-Balena

GitHub Star 2025Google Cloud Architect10 Years OSS

Vipul builds neuro-symbolic AI agents at Command Code that learn developer preferences and coding styles. Previously, he led product and engineering at Balena, where he built Leviathan—the first open-source Hardware-in-the-Loop testing system for IoT. It reduced OS release cycles from 6 weeks to 3 hours and delivered $250K+ in annual savings.

Over the past decade, he has delivered 127+ technical sessions at conferences including GDG DevFest, OpenSSF India, Open Source Summit (Europe & Japan), PyCon India, and Mozilla Festival. He has contributed to open source since 2016, completed Google Summer of Code twice, and helped grow GitTogether Delhi to 5,000+ members.

What Your Team Will Learn

💻

Production Code Generation

Master AI assistants (Copilot, Claude, Cursor) for writing, refactoring, and debugging real code with tests.

🧪

Self-Healing Test Automation

Create test frameworks that adapt when UI changes. Generate test suites from requirements.

🔧

CI/CD Integration

Integrate AI into your pipelines. Automate code review, security scanning, and quality gates.

📈

Adoption Strategy

Get a roadmap for rolling out AI tools with clear metrics to measure success.

Capstone Project

Leave With Working Code

Every participant completes a hands-on capstone project using their own codebase or a provided sample. You don't just learn concepts—you build something real that proves immediate ROI to your team.

🚀
Option A: AI-powered feature in YOUR codebaseBring a real task from your backlog
🧪
Option B: Self-healing test suite for YOUR appConvert existing brittle tests to adaptive ones

"Vipul's LLM evals talk was thoughtful, relevant, and deeply technical. His leadership in the GitTogether community reflects his commitment to fostering collaboration."

Arun Singh

Tech Lead - India, Tech Mahindra

Session Overview

Structured progression from fundamentals to implementation. Every session includes working code you take home.

Session 1 · 45 min
Live Demo
AI Coding Landscape
Interactive Discussion + Demonstrations

Understand where AI coding tools actually are today. Benchmark your team's readiness and identify quick wins.

Current state of AI coding assistants
SWE-bench scores & what they mean
GitHub Copilot vs Claude vs Cursor
When to use each tool
Team readiness assessment
ROI baseline metrics
Team assessment reportBaseline metrics dashboardTool comparison matrix
Session 2 · 75 min
3 LabsLive Coding
Hands-On Code Generation
Live Coding + Pair Programming

This is where you write code. Watch a complete feature built live, then build one yourself with AI assistance.

Prompt engineering basics
Context window management
Multi-step problem decomposition
Iterative refinement patterns
AI pair programming workflows
When AI helps vs. hurts
Working REST API you built20+ prompt patterns playbook
Session 3 · 90 min
3 LabsFramework Build
AI-Powered Test Automation
Framework Building + Live Testing

Build test frameworks that don't break when your UI changes. Especially valuable for teams drowning in flaky tests.

Self-healing test architecture
Semantic vs brittle selectors
AI-powered element location
Test data generation
Flaky test detection patterns
CI/CD integration strategies
Self-healing test frameworkCI/CD pipeline configFlaky test strategy
Session 4 · 30 min
Q&A
Implementation Strategy
Planning + Discussion

Turn what you learned into an action plan. Build a realistic adoption roadmap for your specific team.

Phased rollout strategy
Week 1 pilot program
Month 1 team adoption
Tool selection criteria
Governance & guardrails
Measuring success
90-day adoption roadmapGovernance policy templateROI metrics dashboard

"HUGE gratitude to Vipul for being the most supportive and incredible mentor. An amazing GitHub Copilot talk from beginner to advanced level."

Nitya Pandey

GitHub Campus Expert · Engineering @ Soti

Workshop Deliverables

Everything included in the base workshop.

📦

Code & Templates

  • Complete GitHub repo with workshop code
  • Production-ready templates
  • CI/CD pipeline configurations
  • Self-healing test framework starter
📚

Documentation

  • Workshop slide deck (PDF)
  • Prompt engineering cheat sheets
  • Quick reference guides per tool
  • Best practices playbook
🛠️

Setup Guides

  • Step-by-step tool installation
  • IDE integration tutorials
  • Configuration examples
  • Troubleshooting guide
📊

Planning Tools

  • ROI calculator spreadsheet
  • Adoption roadmap templates
  • Governance guidelines
  • Metrics dashboard templates
🤝

Post-Workshop SupportIncluded Free

The learning doesn't stop when the workshop ends

1 Follow-Up Call (30 min)
7-Day Email Support
Session Q&A Documentation