Kai-Kristian Kemell

LLM-Generated Microservice Implementations from RESTful API Definitions

A system that uses Large Language Models (LLMs) to automate the API-first development of RESTful microservices and assists in creating OpenAPI specification, generating server code from it, and refining the code through a feedback loop that analyzes execution logs and error messages is presented.

VAPU: System for Autonomous Legacy Code Modernization

An LLM-based multi-agent system is indicated that an LLM-based multi-agent system is a capable solution to update components of a legacy application autonomously.

Distributed Approach to Haskell Based Applications Refactoring with LLMs Based Multi-Agent Systems

A large language models based multi-agent system enables precise task execution and inter-agent collaboration, addressing the challenges of refactoring in functional programming.

Assessing Small Language Models for Code Generation: An Empirical Study with Benchmarks

This study presents a comprehensive empirical evaluation of 20 open-source Small Language Models and reveals that several compact SLMs achieve competitive results while maintaining a balance between performance and efficiency, making them viable for deployment in resource-constrained environments.

Autonomous Legacy Web Application Upgrades Using a Multi-Agent System

An LLM-based multi-agent system that autonomously upgrades legacy web applications to the latest versions and maintains context across tasks and agents, improving solution quality over the base model in some cases is proposed.

Vibe Coding in Practice: Flow, Technical Debt, and Guidelines for Sustainable Use

This article analyzes the flow-debt tradeoffs associated with VC and identifies and explains how current model, platform, and hardware limitations contribute to these issues, and proposes countermeasures to address them, informing research and practice towards more sustainable VC approaches.

A Multi-agent LLM System for Automated Requirements Analysis: A Study on User Story Generation and Prioritization

Generative AI Adoption in an Energy Company: Exploring Challenges and Use Cases

This study investigates how employees in a energy company understand AI adoption and identifies areas where AI and LLMs-based agentic workflows could assist daily activities, including reporting work, forecasting, data handling, maintenance-related tasks, and anomaly detection.

Vibe Coding in Software Development: A Multivocal Literature Review

This is one of the first reviews to integrate peer-reviewed and grey literature on vibe coding under a single documented protocol and is strongest for prototyping and user-interface work and weakest for production, data-intensive, and safety-critical use, and tool visibility does not imply effectiveness.

Identifying and Prioritizing Generative AI Use Cases in an Organization: An Industrial Case Study

This study investigates how employees in a energy company understand AI adoption and identifies areas where AI and LLMs-based agentic workflows could assist daily activities, including reporting work, forecasting, data handling, maintenance-related tasks, and anomaly detection.

Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluation

Five domain-specific RAG applications developed for real-world scenarios across governance, cybersecurity, agriculture, industrial research, and medical diagnostics are presented, highlighting technical, operational, and ethical challenges affecting the reliability and usability of RAG systems in practice.

LLM-based Multi-Agent System for Intelligent Refactoring of Haskell Code

Results highlight the ability of LLM-based multi-agent in managing refactoring tasks targeted toward functional programming paradigms and hint that LLM-based multi-agent systems integration into the refactoring of functional programming languages can enhance maintainability and support automated development workflows.