Mapping the First Wave of Vibe-Coded Supply Chain Applications
A Dataleo assessment of emerging AI-built planning software
Executive Summary
AI-assisted application development is rapidly entering Supply Chain Planning. Practitioners are now building planning applications, inventory tools, S&OP platforms and manufacturing extensions using AI coding assistants rather than traditional development teams. Dataleo reviewed the most visible public examples to assess process coverage, strengths, weaknesses and enterprise readiness.
1. Knut Alicke's S&OP Application
Source: https://knutalicke.substack.com/p/how-i-vibe-coded-an-s-and-op-app
Perhaps the most complete publicly demonstrated vibe-coded planning application to date. Demonstrated capabilities include executive dashboards, demand planning, supply planning, capacity planning, inventory management, supplier risk monitoring, scenario simulation and BOM pegging.
Strengths: Broad process coverage, strong planning relevance, compelling demonstration of domain expertise combined with AI-assisted development.
Weaknesses: Limited visibility on Version Control, testing methodology, deployment governance, auditability and integration architecture.
Sweet Spot: Mid-sized manufacturers, consumer goods companies and planning transformation programs.
Dataleo Score: Business Value ⭐⭐⭐⭐⭐ | Innovation ⭐⭐⭐⭐⭐ | Scalability ⭐⭐⭐ | Governance ⭐⭐ | Enterprise Readiness ⭐⭐⭐
2. Mahmoud Moursy's Inventory & Demand Planning Application
Source: https://www.linkedin.com/posts/mahmoud-moursy-43b7a1105_supplychain-demandplanning-inventorymanagement-ugcPost-7466412074387177472-uSWT
A focused planning application centered on inventory management, replenishment and demand planning workflows. Demonstrated screens include inventory visibility, SKU analysis, forecast management and replenishment recommendations.
Strengths: Practical use case, rapid deployment potential, immediate value for planners and inventory managers.
Weaknesses: Limited visibility on forecast explainability, governance controls, planning policy management and documentation standards.
Sweet Spot: Distribution companies, consumer goods organizations and Excel-heavy planning environments.
Dataleo Score: Business Value ⭐⭐⭐⭐ | Innovation ⭐⭐⭐⭐ | Scalability ⭐⭐⭐ | Governance ⭐⭐ | Enterprise Readiness ⭐⭐⭐
3. SAP Digital Manufacturing Extensions
Source: https://community.sap.com/t5/supply-chain-management-blog-posts-by-sap/vibe-coding-sap-digital-manufacturing-custom-plugins-widgets-and-extensions
Unlike most examples, SAP focuses on AI-generated extensions, widgets and operational plugins within an existing enterprise platform. Demonstrated use cases include manufacturing dashboards, POD extensions and shopfloor monitoring tools.
Strengths: Existing enterprise architecture, stronger governance baseline, native integration and easier industrialization.
Weaknesses: Still requires extension governance, release controls, security reviews and lifecycle management.
Sweet Spot: Existing SAP Digital Manufacturing customers.
Dataleo Score: Business Value ⭐⭐⭐⭐ | Innovation ⭐⭐⭐ | Scalability ⭐⭐⭐⭐ | Governance ⭐⭐⭐⭐ | Enterprise Readiness ⭐⭐⭐⭐⭐
4. AI-Built Planning Engines
Sources: Alain Matar IBP engine discussions and IBF article on planning automation: https://ibf.org/knowledge/jbf-articles/vibe-coding-with-llms-for-supply-chain-planning-automation-1491
Several practitioners have demonstrated AI-generated planning engines attempting to reproduce capabilities traditionally associated with APS platforms such as forecasting, inventory optimization, supply planning and scenario modeling.
Strengths: Challenges traditional software economics and accelerates experimentation.
Weaknesses: Significant governance, explainability, master data and lifecycle ownership risks.
Sweet Spot: Innovation labs and controlled experimentation environments.
Dataleo Score: Business Value ⭐⭐⭐⭐ | Innovation ⭐⭐⭐⭐⭐ | Scalability ⭐⭐ | Governance ⭐ | Enterprise Readiness ⭐⭐
Dataleo Takeaway
The most important signal is not that AI can build planning applications. The signal is that planners can now build software. The next competitive advantage will be the ability to govern hundreds of planner-built applications through AI Governance, validation, ownership models, testing standards and deployment processes.
The Dataleo team is developing a framework specifically designed for AI-built supply chain applications to help organizations balance experimentation speed with enterprise control.