Evidence note: Metrics in this note refer to repository tests or controlled scenarios unless a live production source is explicitly linked.
The shift from traditional coding to agentic software engineering is the most profound developer transition in a generation. Yet, most tutorials teach simplistic one-line prompts rather than systematic agent orchestration, custom rules, and Model Context Protocol (MCP) integrations.
Through kaiss.tech, I created an educational platform and curriculum teaching developers how to harness Google Antigravity IDE, multi-agent workflows, and verifiable test-driven development.
The Builder Mindset: Great AI engineers don't let models hallucinate in uncontrolled loops. They construct deterministic validation harnesses, architectural boundaries, and test gates that channel stochastic LLM power into production software.
1. The 3-Tier Agentic Curriculum
- Tier 1: Mental Models & Planning: Transitioning from code typing to architectural specification and iterative review.
- Tier 2: Tooling & MCP Protocols: Connecting local terminal executors, AST search tools, and database debuggers.
- Tier 3: Autonomous Verification: Writing self-healing test loops where agents catch and repair their own regressions.
Sources, Code & Further Reading
- • Educational Portal: instagram.com/kaiss.tech — Daily agentic AI engineering guides.
- • Google Antigravity Documentation: Agent customization system & rule schemas.