Share Description
This course is an intermediate-level course on Pluralsight created by Praveenkumar Bouna, designed to help developers transition from basic AI code completion to fully autonomous, agent-driven software development. Spanning concise, high-impact modules, this course focuses on leveraging Google Antigravity a platform engineered to orchestrate intelligent AI agents across editor, terminal, and browser environments. Learners explore the core concepts of the agent-first paradigm, discover how multi-agent coordination works concurrently, and master the art of turning high-level goals into end-to-end feature implementations. By demonstrating how to monitor agents, evaluate structured artifacts, and configure safety controls, this course bridges the gap between raw AI code generation and reliable, production-ready development workflows.
Topics This Course Covers
- The Agent-First Development Paradigm: Understanding how autonomous AI agents operate across editor, terminal, and browser contexts.
- Multi-Agent Orchestration & Artifacts: Coordinating multiple agents working concurrently and using structured artifacts to inspect, validate, and verify outputs.
- Goal-Driven Feature Implementation: Formulating clear, high-level objectives that guide AI agents through multi-step software development tasks.
- Safety Controls & Approval Gates: Implementing safe-execution policies, approval gates, and human-in-the-loop controls to prevent unexpected code execution.
- Version Control Integration & Team Collaboration: Seamlessly integrating agentic workflows into existing Version Control Systems (VCS) for multi-agent coordination.
- Optimization Strategies: Evaluating model selection choices to balance performance, cost, latency, and context efficiency for team-wide scalability.
Who Will Be Benefitted Taking This Course
- Software Engineers & Full-Stack Developers: Developers looking to evolve past standard inline AI completions into building autonomous, end-to-end feature workflows.
- DevOps Engineers & Technical Leads: Professionals responsible for designing safe, scalable, and reproducible developer environments integrated with version control.
- AI & Engineering Managers: Leaders interested in evaluating Google Antigravity to accelerate feature delivery and boost team engineering throughput safely.
- Solutions Architects: Technical practitioners tasked with setting up model selection strategies and approval gates to balance cloud costs, latency, and system safety.
Why Take This Course
Modern software engineering requires more than simple inline code completions; it demands intelligent systems capable of planning, executing, and verifying complex software features independently. Taking this course equips you with actionable skills to adopt Google Antigravity effectively without sacrificing quality or security. Rather than letting AI tools run as unmonitored black boxes, you will learn how to configure approval gates, manage workspace permissions, and select optimal models for balance between cost and latency. By mastering how to direct parallel agents, validate intermediate artifacts, and integrate workflows into team version control, you will dramatically shorten feature delivery timelines and gain a competitive edge in agentic software engineering.
