Multicloud AI & ERP / Agentic AI & Cloud AI Infrastructure
Why it matters
Software delivery speed is a competitive advantage. Coding agents can take on routine changes, upgrades and test writing, freeing engineers for design, but only teams with good specs, tests and reviews capture the gain safely.
How it works
How a coding agent ships a change
A spec or issue describes the change. The agent reads the code and plans, edits files and runs tests, then opens a pull request. A human reviews and approves the merge, and CI/CD deploys as usual.
AWS, Azure and Google Cloud compared
| AWS | Azure | Google Cloud | |
|---|---|---|---|
| IDE agent | Kiro | GitHub Copilot agent mode | Gemini Code Assist agent mode |
| Background agents | Frontier agents | Copilot coding agent | Gemini CLI and agents |
| Spec-driven development | Kiro specs | Issues and instructions | Specs and prompts |
| Code review | Pull request reviews | Copilot code review | Gemini code review |
| Legacy tool | Q Developer (plugins supported to 2027) | Not applicable | Not applicable |
What makes each cloud different
AWS
Kiro is AWS's spec-driven agentic IDE and the successor to the Q Developer IDE experience, writing requirements and designs before code. AWS's frontier agents take on longer autonomous tasks.
Azure
GitHub Copilot spans completions, chat, agent mode in VS Code, a coding agent that works on a branch from an assigned issue and AI code review, with MCP connections to tools.
Google Cloud
Gemini Code Assist brings agent mode to the IDE, the open-source Gemini CLI brings agents to the terminal, and Gemini reviews pull requests.
Design decisions that matter
- 01Specs before code
Clear requirements make agents accurate.
- 02Tests as the safety net
Agents must run and pass them.
- 03Humans approve merges
Every agent change is reviewed.
- 04Measure outcomes
Cycle time and defect rates, not lines of code.
Common mistakes we see
- No tests to check against. Agents produce plausible but broken code.
- Rubber-stamp reviews. Volume rises, quality falls.
- Secrets in context. Agents should never see production credentials.
A practical 30-day plan
- Week 1
Pick a team and a class of routine tasks.
- Week 2
Set coding standards and agent instructions.
- Week 3
Run agents on real issues with full review.
- Week 4
Measure cycle time and quality, then expand.
How NTS helps
NTS helps engineering teams adopt AI coding agents with Kiro, GitHub Copilot and Gemini Code Assist, including standards, guardrails, test strategy and measurement of real productivity gains.
What you get
- An AI coding policy with clear guardrails
- Secure setup of Kiro, GitHub Copilot or Gemini Code Assist
- Spec-first and test-first workflows for agents
- A dashboard measuring real productivity gains
Typical outcomes
- Faster delivery from the same team
- Agent changes that pass tests and review the first time
- No secrets or sensitive code leaking into prompts
How we work with you
- 1Assess
A focused review of your AI coding adoption across AWS, Azure and Google Cloud. We look for the gaps we find most often: no tests to check against, rubber-stamp reviews and secrets in context.
- 2Design
A target architecture and roadmap built on the decisions that matter most: specs before code, tests as the safety net, humans approve merges and measure outcomes.
- 3Build
Hands-on delivery alongside your team. We pick a team and a class of routine tasks, set coding standards and agent instructions, run agents on real issues with full review, and finally measure cycle time and quality, then expand.
- 4Run and improve
We review usage and quality metrics with your leads, roll out new agent features safely and coach teams as the tools evolve.
Why teams choose NTS for AI coding adoption
- Engineers helping engineers
Our architects use AI coding agents every day, so the guidance comes from practice, not theory.
- Speed with safety
Tests, code review and secret scanning keep agent-written code production-grade.
- Results you can measure
We track cycle time, review effort and quality, not just lines of code.
Book a free 30-minute review
Talk to an NTS architect about your AI coding adoption on AWS, Azure and Google Cloud.