Business Logic Agents

GenAI, Plus The Missing Ingredient: Business Logic Automation

Full Systems: DB, App, API, Logic

Not just Screens or Functions

Running Multi-Table Systems - Including Business Logic

Full Control: Human In the Loop

Validate Logic in Your IDE, With Logging and Debugging

Maintainable: Models, Not FrankenCode

Customize with Your IDE, Dev Tools

Works with GenAI Coding Tools

GenAI Alone Falls Short

Requirements

The requirements for a Business Logic Agent:

- Full System: App, API, Database, and Business Logic
- Validate-able: "Human in the Loop" is a requirement... but how?
- Maintainable: the created system must be maintainable and extensible, and able to leverage the latest AI-based coding tools.

GenAI Alone is Not Enough

Generative AI is transforming software development, creating full stack systems with screens and database access. But there’s a problem.

What's missing is the business logic - the rules and policies that drive the business. And that’s nearly half the effort.

Attempts to use GenAI (alone) for such business logic creates code that is dangerously incorrect, and non-performant. For more information, see this study.

That’s where Business Logic Automation comes in.

Let's explore it, and how it creates full systems - with logic - that are verifiable and maintainable.

GenAI Alone Fails to Address Logic, or Produces FrankenCode

GenAI With Business Logic Automation is Required

The GenAI + Business Logic Automation Approach

1. Full System Creation From Natural Language Prompt

The basic process is shown here:

Submit your business idea as a prompt into your browser. The system creates a running system:
- Full Multi-table Systems: DB, App, API.

Not just a single screen.

- Declarative Business Logic

Not just "your code here".

Remarkable automation - these 5 rules would have otherwise required 200 lines of code.

- Governable Agentic GenAI

No hallucinations, rules are deterministic. Details here.

Full System GenAI is exciting, but presents new challenges: how can you validate the created projects, and maintain / customize them? These are suggested by items (2) and (3) in the diagram here, and further discussed below.

Prompts can be provided in WebGenAI via the Browser, or the CLI.

GenAI occurs during project creation., only.

Resultant project logic is deterministic.

2. Full Control: Human in the Loop

Logic is Deterministic

GenAI occurs during project creation, only.

Resultant project logic is business rules - fully deterministic.

Validating Logic with Your IDE

Created systems are fully transparent. They are backed by standard projects you can download into your favorite IDE, as shown at right.

This enables you to validate the logic created by GenAI, with:

logging (see each rule that fires) and
running it in the debugger (stop in a rule and see state)

This is a level of transparency you don't even get with a spreadsheet.

You can use this to respond to audit and compliance requests: "what is the chain of logic that lead to this result?"

3. Models Make it Extensible and Maintainable

In some cases, you may find that Full System GenAI prompts provide all you need. See the Time Tracking example.

If you need more, projects are designed for customization: create custom UIs, custom endpoints, logic extensions.

You can not only validate your project - you can maintain and customize it as described below.

Your IDE and Tools

Use your favorite IDE - the debugger, and code completion to create rules. Use all the Python libraries. Create containers, and deploy anywhere.

Works with GenAI Coding Tools

You can also use the new generation of GenAI coding tools. These are completely synergistic with Full System GenAI. For example, use CoPilot, Claude or AllHands (etc.) to create custom UIs, custom services, or business logic.

Models, Not FrankenCode

GenAI technology can lead to an explosion of code generation. Past experience has shown that such code is difficult to understand and debug... FrankenCode.

Full System GenAI therefore creates models - high level abstractions of what, not how. For example, the Natural Language Business Logic translation is shown in the diagram:

the constraint (lines 37 - 40)
and the sum derivation (lines 42-43)

As shown here, Models apply to the UI, API, and Logic. Models are made executable by underlying engines, provided by the API Logic Server runtime system.

Business Logic Automation is Critical

In conventional development, business logic is nearly half the effort. To achieve their promise, Business Logic Agents require Business Logic Automation.

Hence the name, GenAI-Logic.

GenAI Business Logic Automation is the process of extending GenAI to:

🔹 Create full, working systems from natural language prompts

🔹 Expressing business logic as declarative models — not enormous amounts of imperative code — that can be directly executed by runtime engines

🔹 Enabling human-in-the-loop validation, debugging, and extensibility using standard developer tools

It builds on GenAI to create maintainable, transparent, and adaptable Business Logic Agents — ready to evolve with your business.

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