Our research

Precision Data Generation (PDG)

Traditional AI development scrambles to find adequate datasets. Precision Data Generation (PDG) takes a different approach: generate the exact data you need, when you need it.

Our research applies contract-based frameworks to dataset creation, enabling AI systems to produce high-quality, task-specific data on demand. By defining precise requirements upfront—schema, quality standards, edge cases—organizations gain consistent, reproducible datasets that align perfectly with their applications.

PDG transforms data from a scavenging problem into an engineering discipline: scalable, auditable, and built for production AI.

Precision Code Generation (PCG)

AI can write code fast, but is it code you can trust? Precision Code Generation (PCG) ensures the answer is yes.

Our research applies contract-based frameworks to AI code generation, transforming unpredictable outputs into consistent, production-ready code. By defining precise requirements upfront—architecture patterns, testing standards, security constraints—development teams gain code that meets enterprise criteria without endless iteration.

PCG transforms AI coding assistance from a review burden into an engineering multiplier: predictable, auditable, and built for production systems.

AI Oriented Solution Design (AIOSD)

Traditional software design patterns break when AI enters the picture. AI Oriented Solution Design (AIOSD) provides the missing framework.

Our research establishes design principles for AI-native systems—architectures that account for AI's probabilistic nature, evolving capabilities, and non-deterministic behavior from the ground up. Rather than retrofitting AI into conventional patterns, AIOSD defines how to design solutions where AI is a governed, observable, first-class component.

AIOSD transforms AI integration from architectural afterthought into intentional design: predictable, governable, and built for production reality.

Contract-Driven Generative Architecture (CDGA) is to AI what Object-Oriented Programming was to software engineering—a fundamental paradigm shift.

In CDGA, you don't write code. You write contracts using the Precision Prompting Protocol (P^3) that specify exactly what the system must do. The LLM writes and executes the implementation. Your role shifts from coder to architect of specifications—defining requirements, constraints, and governance while AI handles generation.

CDGA is both programming paradigm and language: AI-Oriented Programming for the generative era. It's how software gets built when AI is the execution engine.

Contract-Driven Generative Architecture (CDGA)

AI Capability Enhancing Tools (AICET)

In Contract-Driven Generative Architecture (CDGA), programmers write contracts in P^3, and LLMs execute implementations. AI Capability Enhancing Tools (AICET) provides the complete infrastructure that makes this paradigm practical.

For AI execution: Runtime tools that enable LLMs to compute, retrieve data, integrate systems, and maintain state—the capabilities contracts require for real-world implementation.

For human development: Professional tooling for contract creation—prompt generators that scaffold P^3 contracts, prompt managers for versioning and governance, validation frameworks for contract testing, and debugging tools for execution analysis.

AICET is the complete development stack for CDGA programming—runtime and tooling layers working together.

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