The SQL Business Rule has long been the superpower of the Code On Time developer. It allows you to inject validation, logging, and custom data processing directly into your application using the language you know best—SQL. For high-performance, database-specific tasks, it remains the gold standard.

But as the Code On Time platform evolves with the Digital Workforce, Builder Edition, and AI Scaffolding, there are specific scenarios where you might need a different kind of tool.

This is where the [ProjectNamespace].Data.SqlText utility class shines.

It isn't about replacing the SQL rules you love; it's about extending your reach to platforms and technologies where raw T-SQL or PL/SQL cannot go.

1. The Key to the Builder Edition (SQLite)

The Builder Edition allows you to build unlimited commercial applications for free and accelerated by the Digital Workforce. To make this portable and lightweight, it defaults to using SQLite.

While SQLite is a powerful database engine, it does not support the rich procedural languages (like T-SQL or PL/SQL) that drive standard SQL Business Rules.

• The Challenge: How do you write server-side validation logic (e.g., "Check if Customer exists") in an app running on SQLite?
• The Solution: Type: Code business rules using the SqlText class. This allows you to write standard SQL queries wrapped in C# or VB.NET, which the framework automatically translates for SQLite. It is the only way to build complex server-side logic for Builder Edition apps.

2. A Blueprint for AI Scaffolding (GEN)

We are introducing GEN (Scaffolding) capabilities that allow you to "export" your application logic to completely different technology stacks, such as Next.js, Python, or standard ASP.NET Core APIs.

• The Challenge: An AI agent cannot easily translate a block of raw T-SQL into a Node.js API route because the logic is "locked" inside the database dialect.
• The Solution: Logic written with SqlText acts as a "White Box" for the Axiom Engine. The AI can read your C# code, understand the intent, and natively re-implement it in the target language. If you plan to use your app as a specification for a custom build, SqlText ensures your business rules travel with you.

3. Debugging with "Pro Code" Tools

For complex logic, nothing beats a real debugger.

• The Advantage: Unlike SQL scripts, Type: Code rules live in your project's source files. You can use the "Edit Code" action to open your rule in Visual Studio, set breakpoints, and step through your logic while the app runs. It combines the speed of the App Studio with the precision of a professional IDE.

Learn the Pattern

We have released a comprehensive tutorial to help you add this tool to your belt. Whether you are building a portable app for the Builder Edition or preparing a specification for the Digital Workforce, this guide shows you how to write secure, database-agnostic logic.

Read the Tutorial: Using the SqlText Class in "Code" Business Rules
Master the tools that let you build anywhere, for any platform.

We are living through an "Intelligence Boom."

The latest Large Language Models (LLMs) can pass the Bar Exam, write Shakespearean sonnets about your quarterly earnings, and debug complex Python scripts in seconds. They are, by all accounts, geniuses.

But there is a problem.

If you ask that genius AI to perform a simple, mundane task—like "Update this customer's phone number"—it hits a wall.

It might say: "I cannot access your database directly."

Or worse, if you’ve rigged up a custom connection, it might say: "I’ve updated the number," while secretly hallucinating a format that breaks your downstream SMS provider.

Potential vs. Kinetic Energy

The current generation of Enterprise AI is stuck in a state of Potential Energy.

It has the potential to reason about your business, but it lacks the Kinetic Energy to actually move it forward.

It is a Brain in a Jar.

It sits on a shelf (or in a chat window), disconnected from the physical reality of your business data. It can observe, analyze, and comment, but it cannot touch.

The "90/10" Reality of Business

This is a critical failure because business is not 90% "Thinking." Business is 90% Doing.

• 10% Inference (The Brain): "Analyze these sales trends." "Draft a polite email." "Summarize this meeting."
• 90% Operations (The Hands): "Post this invoice." "Update that inventory count." "Schedule the installation." "Flag this account for review."

Most AI technology providers are selling you engines that excel at the 10% but are paralyzed at the 90%. They offer you a "Copilot" that can explain the flight manual in perfect detail but cannot actually reach the control stick.

The Trap of "Building Hands" (MCP)

To solve this, the industry has rallied around concepts like the Model Context Protocol (MCP) or "Function Calling." The idea is simple: You write code to give the AI a "Hand."

• You write a function: update_phone_number(id, number).
• You teach the AI how to use it.
• You pray the AI uses it correctly.

The problem? You have to build a new hand for every single action in your enterprise. If you have 1,000 database tables, you are looking at building 5,000+ custom tools. And once you build them, you have to write "Safety Manuals" (System Prompts) to ensure the AI doesn't accidentally delete the wrong record.

It is expensive, risky, and fragile. It turns your development team into "Prosthetics Engineers."

The Solution: Give the Brain a Body

At Code On Time, we believe you shouldn't have to build hands from scratch. You already have them.

Your existing business applications—the forms, the grids, the validation rules, the security roles—are the Hands. They already know how to safely update a phone number. They already know that "Inventory cannot be negative."

Our Micro-Ontology technology (powered by the built-in Axiom Engine) simply connects the "Brain" (Your LLM of choice) to the "Body" (Your Application).

• The Brain provides the intent: "Update the phone number to 555-0199."
• The Body (Code On Time) executes the action using the HATEOAS API.

It doesn't hallucinate the update logic because it doesn't invent the update logic. It uses the exact same logic your human employees use every day.

The Right Brain for the Job

Because the "Body" handles the safety and execution, you are free to swap the "Brain" based on the user's role.

• For the CEO (Strategy): Give their Digital Co-Worker a high-end Reasoning Model (like GPT-4o or Claude 3.5 Sonnet) and Read-Only Access to all customer orders.
• • The Prompt: "Write a data poem analyzing our Q4 churn rate vs. competitor pricing."
  • The Result: Deep, strategic insight. Expensive compute, but worth it for the 10% of strategic decisions.
• For the Employees (Operations): Give their Digital Co-Worker a fast, efficient Flash Model (like Gemini 1.5 Flash).
• • The Prompt: "Reschedule the Jones appointment to Tuesday."
  • The Result: Instant, error-free execution. Low cost ($0.0004/task), perfect for the 90% of daily grind. Performed via SMS.

You don't have to choose between "Smart" and "Safe." You can have the Genius in the boardroom and the Diligent Worker in the mailroom, both running on the same secure platform.

From "Chatbot" to "Co-Worker"

When you connect a Brain to a Body, you stop getting a "Chatbot" and start getting a Digital Co-Worker.

• A Chatbot writes a poem about your data.
• A Co-Worker fixes your data.
• A Chatbot suggests you email the client.
• A Co-Worker sends the email (after you approve the draft).

Don't settle for a genius on a shelf. Give your AI the hands it needs to get to work.

Ready to unleash Kinetic AI?
Discover how the Digital Co-Worker moves your business