Building with Google Antigravity: From AI-Assisted Coding to Agentic Software Engineering
Cloud Experts Hub
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Building with Google Antigravity: From AI-Assisted Coding to Agentic Software Engineering
36 просмотров · 8 дн. назад
Cloud Experts Hub
36 подписчиков
36 просмотров · 8 дн. назад
🚀 Building with Google Antigravity: From AI-Assisted Coding to Agentic Software Engineering | Cloud Experts Hub
What if AI could do more than write code? What if it could plan, build, test, debug, and validate entire software engineering workflows?
In this Cloud Experts Hub online session, we explore Google Antigravity and the shift from AI-assisted coding to agentic software engineering through practical demonstrations of AI agents executing real development tasks.
Discover how developers can move beyond code completion and use agentic development environments to transform natural-language requirements into working applications—with implementation plans, generated artifacts, testing, iterative fixes, and human approval.
🎥 In this session, you'll see live demonstrations of agentic software development, including browser-based research, website generation, and building a productivity application.
🔥 What You'll Learn
🔹 Google Antigravity and Agentic Engineering — Understand how AI-assisted coding evolves into autonomous, multi-step engineering workflows.
🔹 AI Agents in Action — Explore how agents interact with files, browsers, terminals, and development tools to accomplish engineering tasks.
🔹 Live Demo 1: Google News Research — Watch an agent navigate Google News, retrieve information, and synthesize relevant highlights using browser tools.
🔹 Live Demo 2: Technical Conference Website — Build a Python and Flask-based conference website from natural-language requirements, including schedules, speaker listings, and supporting application files.
🔹 Live Demo 3: Productivity App — Generate a Pomodoro timer application, run it locally, identify issues, and apply fixes through agentic execution.
🔹 Spec-Driven Development (SDD) — Learn how context, explicit specifications, architectural constraints, and acceptance criteria improve the quality of agent-generated software.
🔹 Inspectable Execution and Verification — Understand the importance of implementation plans, generated artifacts, documentation, test results, and validation evidence.
🔹 Enterprise AI Agent Governance — Explore trust boundaries, tool permissions, data access controls, auditability, cost guardrails, verification requirements, and human approval.
🧠 The Agentic Engineering Workflow
A reliable agentic development process goes beyond prompting a model to generate code.
Intent → Context → Specification → Implementation Plan → Execution → Verification → Human Review
This approach helps developers define expected outcomes, provide the right context, inspect the agent's plan, verify implementation quality, and maintain control over sensitive operations.
The key lesson: better specifications lead to better agent execution.
🛡️ Why Governance Matters
As AI agents gain access to repositories, terminals, databases, APIs, and cloud environments, unrestricted autonomy becomes an engineering risk.
Enterprise adoption requires explicit boundaries around:
Agent capabilities and tool permissions
Data access and security constraints
Testing and verification evidence
Execution audit trails
Cost and resource consumption
Human approval for sensitive operations
The goal is not autonomy without boundaries. It is controlled autonomy with verifiable outcomes and human oversight.
👨💻 Who Should Watch?
This session is for:
Software developers exploring AI-powered coding
AI engineers and agentic application developers
Cloud and enterprise architects
DevOps and platform engineering professionals
Engineering leaders interested in developer productivity
Teams adopting Spec-Driven Development and AI agent governance
💡 The Big Takeaway
Stop asking only, “Can AI write my code?”
Start asking:
“What engineering workflow can an AI agent reliably execute for me?”
The future of software engineering belongs to developers who can design the right context, define constraints, supervise execution, verify outcomes, and govern increasingly capable AI agents.
🌐 About Cloud Experts Hub
Cloud Experts Hub brings developers and IT professionals together to explore cloud technologies, AI engineering, developer platforms, and emerging architectural practices through practical sessions and demonstrations.
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💬 Join the discussion: Which engineering workflow would you automate first using an AI agent?
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