Accelerating MES Platform Development Through AI-Driven Engineering Training

A rapidly growing MES (Manufacturing Execution System) software company needed to scale its engineering capabilities to keep up with rising customer demand, fast-changing manufacturing requirements, and an expanding feature roadmap.

While the engineering team understood the potential of AI-assisted development tools like GitHub Copilot, they lacked a structured approach to safely and effectively integrate AI into their workflows. The leadership team wanted to accelerate developer productivity, reduce cycle time, and improve software quality—without sacrificing reliability in a mission-critical manufacturing environment.

Connective Consulting was engaged to deliver a comprehensive AI Development Workshop tailored to the needs of an MES software organization. The workshop equipped engineers with practical skills, safety guardrails, and repeatable workflows to effectively apply AI tools to MES development. AI Development Workshop

Fast-growing MES companies face unique pressures:

• Rising customer expectations for real-time performance, precision, and reliability

• Large and complex codebases that support production lines, scheduling, traceability, and OEE analytics

• Short release cycles driven by manufacturing SLAs

• High cost of defects due to downtime or production-impacting issues

• Talent scaling challenges as engineering demand outpaces hiring

In this environment, the company saw AI as a way to augment developers—not replace them—and accelerate their roadmap. But key gaps remained:

• Limited understanding of when and how to use AI in MES development

• Lack of consistency across engineers experimenting with AI tools

• No guardrails to protect production-critical code

• Difficulty applying AI tools to legacy and highly-integrated MES components

• Low confidence in prompt engineering, agent workflows, and LLM reasoning

The organization needed a structured, actionable AI enablement program—not a high-level overview.

Connective designed a specialized training program grounded in real MES engineering challenges: legacy code integration, test automation, safe deployments, and rapid prototyping of new modules.

• How AI applies to industrial and operations software

• Realistic productivity expectations (skill curves, J-curve adoption)

• Why AI excels in routine coding, prototyping, test generation, and documentation AI Development Workshop

Hands-on demos and exercises using:

• GitHub Copilot

• Agentic coding tools (Cursor, Claude Code, Roo Code)

• Model comparison using Amazon Bedrock

Developers learned to:

• Generate MES components faster

• Refactor legacy code safely

• Automate testing workflows

• Build prototypes for manufacturing dashboards, APIs, and integrations AI Development Workshop

Using the CRISPE and Zero/Few-Shot frameworks, teams learned to prompt AI for:

• Equipment interface patterns

• Data transformation logic

• Manufacturing workflows (recipes, routing, traceability)

• Schema design

• Industry-specific error handling

Developers immediately saw improvements in accuracy and speed. AI Development Workshop

Crucial for MES software, engineers learned:

• How to prevent the AI from making destructive changes

• How to use TDD + AI as a safety net

• How to avoid hallucinations in large, interconnected MES codebases

• When not to use AI

• Cost management and premium model usage AI Development Workshop

This section directly addressed the company’s greatest concern: maintaining reliability inside manufacturing environments.

Engineers were taught structured patterns for complex MES features:

• Propose → Refine → Execute workflow

• Memory-bank pattern for multi-step MES feature development

• Layer-by-layer implementation (DB → Service → API → UI)

• How to treat AI like a “brilliant but inexperienced developer”

The result: safer, more predictable use of AI on a mission-critical platform. AI Development Workshop

Engineers collaborated on an MES-relevant coding problem using AI tools as part of the team. Benefits included:

• Shared understanding

• Real-time exposure to AI decision-making

• Team alignment on best practices AI Development Workshop

• Faster development cycles, particularly for UI components, APIs, and routine transformations

• Improved code quality through AI-driven test generation and documentation

• Higher developer confidence in applying AI to real MES code

• Clear safety protocols that reduced risk in production environments

• Consistent prompting patterns across the engineering organization

• Faster ability to release features supporting new manufacturing workflows

• Shortened onboarding time for new developers

• Reduced pressure on senior engineers

• Better scalability for a fast-growing customer base

• Stronger engineering culture built around modern tooling

Engineers shared that the workshop:

• “Immediately changed how I approach problems.”

• “Removed my fear about using AI in production code.”

• “Showed me practical techniques—not just theory.”

• “Helped me understand where AI actually creates value in MES systems.”

The engagement positioned the MES company to:

• Confidently integrate AI into software development

• Improve velocity without compromising manufacturing reliability

• Build a sustainable AI-assisted delivery culture

• Stay competitive in a rapidly evolving industrial tech landscape

Connective’s training gave the engineering team the skills, guardrails, and workflows needed to safely leverage AI as a strategic advantage in MES development.