Human‑AI Engineering Framework for Legacy Software Modernization

At A31 we are implementing software delivery practices tailored for legacy systems modernization, combining top-notch engineering expertise and modern AI tools to speed up software development process, streamline data migration process — without compromising security and further maintenance.
What is A31?
Who we are?
What is AI-Driven Engineering?
Why now is the right time?
How we can help?

What is A31?

A31 is a software development agency specializing in modernizing legacy software through senior engineering teams, enhanced with AI-driven software delivery process. Our adapted SDLC framework combines human architectural leadership with AI-driven tools, balancing our engineers expertise, experience and supervision with the routine tasks efficiently managed by AI coding agents.

Hybrid Human + Agentic Teams

At A31, experienced principal engineers and architects prepare and optimize your existing infrastructure for seamless AI integration. We strategically restructure your codebase into manageable repositories, allowing AI coding agents to operate within clearly defined contexts, accelerating development without sacrificing control or quality.

Who we are?

Olga Kyivska, Delivery Director: Olga is a Delivery Manager / Product Manager with 12+ years' experience and a track record of launching products with oversight for all phases from concept to delivery

Dmytro Evseev, Engineering Advisor: Dmytro is a crucial part of our Technical Advisory team. He has over 20 years of experience as a software engineer and tech lead helping organization and startups with go to market product implementation.

Ross Dzikovskyi, Executive Director: Ross leads our research and policy work. Ross has over 16 years of experience in building software development agencies, and leading software modernization and replatforming projects with teams up to 100 people.

Alex Bondarenko, Head of Engineering: Alex leads our development and research teams. He has over 12 years expertise in software development and helped design our SDLC framework for Human-AI development. He has extensive knowledge in multiple programming languages, software architecture and infrastructure.

What is AI-Driven Engineering?

AI-Driven Engineering at A31 represents an evolved Software Development Lifecycle (SDLC), meticulously designed to integrate generative AI effectively. Our approach harnesses AI to support every critical stage of software development, from initial architecture through testing and documentation. By strategically embedding AI tools, we enhance development agility, accuracy, and efficiency.

AI-Driven Engineering involves:

Generative AI Integration

Implementing advanced generative AI models to automate code generation, testing, and documentation.

Contextual AI Management

Creating structured, manageable contexts within repositories for AI-agents to accurately interpret and execute tasks.

AI-Agent Architecture

Deploying AI-architect agents equipped with Retrieval-Augmented Generation (RAG) memory for deep contextual understanding of project documentation and codebases.

Evaluations (Evals)

Defining rigorous benchmarks to consistently measure and improve the performance of AI-driven processes.

Secure Human Oversight

Ensuring AI agents are supervised by human lead engineers who manage architectural integrity, system security, and sensitive tasks, balancing automation with expert human judgment.

Our Hybrid SDLC Implementation:

Infrastructure Preparation

Principal engineers restructure codebases into smaller, AI-manageable repositories.

AI Evaluation Framework (Evals)

Rigorous assessment methods to ensure AI agent reliability and output quality.

Automated Testing & Documentation

Leveraging LLMs to automatically generate comprehensive tests and API documentation.

Human-Led Supervision

Our human lead engineers supervise AI agent-architects, reviewing prompts, supervising tasks, and managing sensitive components.

Why now is the right time?

The integration of AI into software development is no longer optional—it's essential. Leading technology companies are already seeing major benefits, rapidly redefining productivity and innovation standards:
Microsoft / AI now contributes to 20–30% of code in projects, predicting 95% AI-generated code within five years (source).
Google / Over 30% of new code is AI-generated, up from 25% in late 2024, reflecting quick and widespread AI adoption (source).
Salesforce / Achieved a 30% productivity increase through AI, reshaping hiring strategies (source).
GitHub Copilot / Proven to reduce developer workload by up to 50% in code documentation and by 30–40% in repetitive coding tasks (source).
The complexity of tasks AI can manage doubles roughly every seven months, meaning by 2032, AI could automate tasks equivalent to a month’s worth of manual development (source).

Companies that adopt AI-driven engineering now will gain crucial competitive advantages, positioning themselves for sustained innovation and accelerated growth.

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