SHAMS Network Planner

The description states that SHAMS Network Planner is an AI-powered assistant designed to generate practical network plans for homes, businesses, and underserved communities. The author claims it converts user inputs like number of users, coverage area, internet source, and budget into structured recommendations including device suggestions, cost estimates, and ready-to-send proposals.

The project appears to be a mobile-first web application built during an OpenAI Build Week hackathon using Codex and GPT-5.6. It combines AI reasoning with deterministic safety rules to avoid unsafe or unsupported recommendations.

Key commercial signals are absent: no revenue, customers, pricing, traction or adoption data are provided. The description is entirely self-reported and unverified.

The description states that SHAMS Network Planner is:

• An AI-powered assistant
• A mobile-first web application
• Built using Codex and GPT-5.6 during OpenAI Build Week
• Designed to turn basic connectivity needs into practical network plans
• Capable of generating:
  • Recommended network topology
  • Suggested routers, access points, antennas, and supporting equipment
  • Bandwidth and capacity recommendations
  • Power and PoE compatibility warnings
  • Coverage assumptions and installation guidance
  • Preliminary cost estimate
  • Customer-ready proposal
  • WhatsApp message for sharing

The system is described as not replacing certified network engineers but clearly displaying assumptions and recommending professional verification for complex deployments.

The description states that SHAMS Network Planner was inspired by the need to make practical network planning easier, faster, and more accessible in underserved communities where professional consultation is expensive or unavailable.

It positions itself as an AI assistant that simplifies technical network design for users without deep networking knowledge. The author claims it combines AI reasoning with practical domain knowledge and strict validation to produce reliable recommendations.

The project evolved from a hackathon prototype into a longer-term vision including features like interactive diagrams, map-based planning, local pricing catalogs, and multilingual support.

The description states that SHAMS Network Planner targets:

• Homes
• Businesses
• Underserved communities

It is specifically designed for users who struggle to choose the right networking equipment or build networks without a clear technical plan. The author notes that professional network consultation can be expensive or unavailable, especially outside major cities.

The target customer profile appears to include people with limited technical knowledge who need practical guidance for internet connectivity planning in areas where expert support is difficult to reach.

Not evidenced.

The description does not contain any information about pricing models, monetization strategies, revenue streams, or commercial arrangements. There are no claims about how the product will generate income or what customers will pay for its use.

The description states that SHAMS Network Planner is being built as a mobile-first web application using:

• Codex
• GPT-5.6
• Next.js
• React
• TypeScript
• Tailwind CSS
• OpenAI APIs

It uses Codex for:

• Application architecture design
• User interface building
• Validation rule implementation
• Code writing and review
• Testing
• Error identification and repair
• Technical documentation preparation

GPT-5.6 is used to convert user requirements into structured recommendations and clear explanations.

The system combines AI reasoning with deterministic safety rules to check for issues like voltage, PoE compatibility, unrealistic coverage expectations, and excessive user capacity before displaying recommendations.

Not evidenced.

There are no claims about revenue, customers, adoption rates, usage metrics, or any traction data. The project is described as a prototype built during a hackathon with no indication of market testing, customer feedback loops, or product-market fit validation.

Not evidenced.

The description does not mention existing competitors, market size, competitive positioning, or how SHAMS Network Planner differentiates from other network planning tools or AI assistants in the space. No information about the broader market landscape is provided.

• Unproven commercial viability: The description contains no evidence of revenue, customers, or pricing models.
• Prototype status: The project is described as a hackathon prototype with no indication of product-market fit or scalability beyond the initial build week.
• Technical risk: The system relies on AI to convert field experience into software rules, which may be difficult to implement reliably.
• Trust and liability concerns: While the system claims to display assumptions, there's no evidence of how it will handle uncertainty or prevent unsafe recommendations.
• Limited team capacity: Only one team member is mentioned, raising questions about execution capability for a complex technical product.

1. What specific revenue model do you plan to implement once this becomes more than a prototype?
2. How will you validate that the AI recommendations are accurate and safe for real-world deployment?
3. What is your strategy for building trust with users who may be making critical infrastructure decisions based on these recommendations?
4. How do you plan to scale beyond the current hackathon prototype?
5. What specific technical challenges have you encountered in converting field experience into software rules?
6. How will you handle liability or errors in network planning that could lead to customer loss or safety issues?