fieldforge-ai

FieldForge AI turns real-world work problems into practical solutions, prototypes, and next steps.

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Inspiration

FieldForge AI was inspired by a problem I have repeatedly seen in blue-collar work, agriculture, maintenance, and hands-on problem-solving: the person who understands a problem best often does not have access to the right engineer, product designer, manufacturer, business mentor, or technical expert.

Farmers, ranchers, mechanics, tradespeople, contractors, technicians, inventors, and hobbyists solve practical problems every day. They know what is inefficient, unsafe, expensive, difficult, or missing because they experience it firsthand. However, many useful ideas never move forward because the person does not know what to do next, how to explain the idea, whether it is realistic, or whom to contact.

I am a nontraditional founder with ADHD, learning disabilities, executive-functioning challenges, and a major transportation barrier. I generate practical business and invention ideas, but I often need help turning scattered thoughts into organized plans. That experience directly shaped FieldForge AI.

The project is based on a simple belief:

Practical knowledge should not be wasted because the person who has it lacks coding experience, money, professional connections, or a traditional technical education.

What it does

FieldForge AI helps users turn real-world work problems into organized, practical next steps.

A user describes a problem involving equipment, tools, workflow, agriculture, maintenance, repair, fabrication, or a possible invention. FieldForge guides the user through questions such as:

  • What field, trade, or activity is involved?
  • What equipment, tools, or materials are available?
  • What has already been tried?
  • What cost, time, safety, size, weather, transportation, or experience constraints exist?
  • Is the goal to repair, improve, replace, or invent something?

FieldForge then organizes the situation into:

  1. A clear problem statement
  2. Possible causes
  3. Safety concerns
  4. Repair or improvement options
  5. Modification or invention possibilities
  6. Prototype requirements
  7. Testing steps
  8. Business, manufacturing, or licensing possibilities
  9. The type of professional, program, or organization that may be able to help
  10. A manageable list of next actions

The goal is not to replace mechanics, engineers, licensed tradespeople, veterinarians, attorneys, or other qualified professionals. FieldForge helps users understand the problem, document what they know, prepare better questions, and identify the safest and most realistic next step.

How we built it

I began by narrowing a large product vision into one repeatable workflow:

Describe the problem → identify constraints → explore solutions → plan a prototype → test the idea → choose the next professional or business step

I used ChatGPT to organize my original notes, define the user experience, improve the project description, and translate real-world ideas into a structured product concept.

The prototype was built as a lightweight browser-based webpage using HTML, CSS, and JavaScript. I intentionally designed it to work without paid hosting, paid development software, or paid API usage because affordability and accessibility were important project constraints.

The current prototype allows a user to:

  • Choose a field or type of work
  • Describe a practical problem
  • Record available tools, materials, budget, and limitations
  • Identify safety and environmental concerns
  • Generate a structured FieldForge problem-solving prompt
  • Use GPT-5.6 to analyze the situation
  • Return the response to the project workflow
  • Save and organize the resulting practical plan

OpenAI Codex was used to review, test, refine, and improve the prototype code. Codex helped translate the project requirements into a clearer working structure and identify improvements that would have been difficult for me to complete independently.

Challenges we ran into

Building without a traditional technical background

I am not a professional software developer. One of my biggest challenges was learning the difference between having an AI product idea and creating a small working demonstration of that idea.

I had to stop trying to design the entire future platform and focus on one useful workflow that could be clearly demonstrated.

Keeping the project focused

FieldForge could eventually support farming, ranching, mechanics, pool service, construction, fabrication, outdoor equipment, maintenance, and many other fields.

Trying to include every industry and feature in the first version would have made the prototype confusing and unrealistic. I learned to use individual field problems as demonstration cases rather than allowing one example to become the entire product.

Working around disability-related barriers

ADHD, learning disabilities, executive-functioning challenges, and transportation limitations affected how I completed the project.

I needed:

  • Written instructions
  • Short, numbered steps
  • One decision at a time
  • Plain-language explanations
  • A clear checklist
  • The ability to plan and review the project from a phone while traveling as a passenger

These barriers also influenced the product’s design. FieldForge should not give users an ideal solution that ignores their actual circumstances. It should consider the tools, money, time, health, transportation, location, and experience they really have.

Building with no available budget

I could not spend money on API usage, hosting, software, or professional development services.

That limitation led me to create a prototype that runs directly in a browser and uses a guided GPT-5.6 workflow without requiring the user to expose an API key or activate paid API billing.

Balancing usefulness and safety

Many blue-collar and agricultural problems involve electricity, pressure, heavy machinery, chemicals, animals, structural loads, fire, fuel, hydraulics, or work that requires licensing.

The project needed to distinguish between:

  • Low-risk planning and inspection
  • Tasks that require a trained or licensed professional
  • Situations where work should immediately stop because of a safety risk

Accomplishments that we're proud of

I am proud that I turned a broad idea into a working and understandable prototype despite having no traditional software-development background and no available project budget.

I am also proud that the prototype:

  • Centers the knowledge of workers and hands-on problem-solvers
  • Accounts for real constraints instead of assuming unlimited money, transportation, equipment, or professional support
  • Provides an organized path from a rough problem to practical next steps
  • Includes safety boundaries rather than presenting AI suggestions as guaranteed answers
  • Can be used from a basic web browser without paid hosting or API access
  • Demonstrates that a nontechnical founder can use AI tools to begin turning lived experience into a functional product

The greatest accomplishment is not that FieldForge knows everything. It is that the project demonstrates a repeatable method for helping someone move from confusion to a clearer and safer next step.

What we learned

The biggest lesson I learned is that being a founder does not mean personally knowing how to perform every technical task.

My role is to understand the problem, explain the user’s needs, define the workflow, evaluate whether the results are practical, and make product decisions. AI tools can help translate that real-world knowledge into software and organized systems.

I also learned that a strong prototype does not need to contain the entire business vision. It needs to demonstrate one meaningful outcome clearly.

FieldForge became stronger when I changed the goal from:

Build an AI that knows everything about every trade.

to:

Build a repeatable system that helps one person move from a real-world problem to a safer, more organized next step.

I also learned that accessibility features often improve a product for everyone. Plain language, short steps, saved progress, structured questions, and visible next actions are useful not only for people with disabilities, but also for workers who are busy, tired, under pressure, or completing tasks in the field.

What's next for fieldforge-ai

Future versions of FieldForge AI could include:

  • Photo, sketch, manual, and document uploads
  • Voice-based problem descriptions
  • Equipment make-and-model identification
  • Location-aware expert and program recommendations
  • Connections to official manuals and safety documentation
  • Prototype version and testing-result tracking
  • Materials, price, and manufacturing comparisons
  • CAD and 3D-printing support
  • Connections to agricultural extension offices, technical schools, makerspaces, manufacturers, patent clinics, and Small Business Development Centers
  • Specialized modes for agriculture, mechanics, trades, maintenance, invention development, and hobby projects
  • Project memory that stores measurements, decisions, costs, contacts, test results, and next steps
  • Tools that help users decide whether to repair, fabricate, manufacture, license, or build a service around a solution

The long-term vision is for FieldForge AI to become a practical bridge between field experience, technical problem-solving, product development, and entrepreneurship.

Built With

  • OpenAI GPT-5.6
  • OpenAI Codex
  • ChatGPT
  • HTML
  • CSS
  • JavaScript
  • GitHub

Founder

Justin Crawford Founder, All Element Innovations LLC

Built With

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