It is more than autocomplete. Production AI-assisted software development includes coding copilots, test generation, agentic refactoring, RAG knowledge bots for codebases, and governed tool access to tickets, repos, and cloud APIs.
Nitin Rana focuses on enterprise-safe patterns: model routing, evaluation, secret hygiene, and human approval for high-risk changes.
Use AI for boilerplate, migrations, and documentation drafts—then enforce human review for security-sensitive and payment-adjacent code.
Ground assistants with RAG over internal docs and runbooks so answers cite your systems, not generic internet guesses.
For product features, apply agentic AI: planners + tools (MCP) that can query hospitality systems safely.
Teams often need private models for proprietary code and guest data. Nitin Rana documents custom LLM approaches using Llama-class models for on-premises or VPC serving, hybrid routing, and gated tool use—see the dedicated article on custom LLMs with Llama.
Define allowed data classes in prompts, redact secrets, log model usage, and keep PCI/GDPR/SOC 2 controls intact when AI touches production systems.