Important Dates
Submission Due: 15 December 2025
Expected Publication: Sept/Oct 2026
Agentic engineering is an emerging discipline focused on the design, development, and operation of systems that exhibit goal-directed autonomy, reasoning, and continuous evolution. Foundation models (FMs), such as large language models (LLM), have been accelerating progress in this area across academia and industry.
Agentic systems often involve multiple interacting agents, humans, and tools, requiring rigorous system-level engineering to ensure critical qualities like robustness, safety, and observability. A key design challenge in agentic engineering is the growing capability of FMs/LLMs. Developers must decide whether to rely on the FM/LLM or external tools/systems for the same functionality. These decisions can be made at various stages depending on the problem and context: during design time, development time, or event at runtime from a software engineering perspective, and at pre-training time, post-training time, test/inference time, and post-inference time from an AI perspective. Highly autonomous agentic systems also require continuous monitoring, evaluation, observability, intervention, and oversight after deployment, an emerging discipline referred to as AgentOps. Designing this post-deployment environment is also highly complex, with many interdependent design choices.
This special issue aims to address these challenges by exploring cutting-edge engineering methods, techniques, tools, and practices for agentic systems. It seeks articles that provide with insights into the design, development, and operation of agentic systems, emphasizing practical applications and real-world experiences.
Topics of interests include, but are not limited to:
- Requirements engineering for agentic systems
- Architectural design for agentic systems
- Verification, validation, and testing of agentic systems
- AgentOps – DevOps for agentic systems
- Development processes and lifecycle management for agentic systems
- Evaluation methodologies, tools, and benchmarks for agentic systems
- Responsible AI and AI safety of agentic systems
- Agentic systems for software engineering, including requirements, design, coding, testing, deployment, and operations
- Human-agent interaction, collaboration, and oversight
- Risk and impact assessment (e.g. economic/social impact)
- Real-world case studies and practical experiences in different domain
Submission Instructions:
For author information and guidelines on submission criteria, visit the IEEE Software Author Information page. Please submit papers through the IEEE Author Portal system, and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the IEEE Author Portal. If requested, abstracts should be sent by email to the guest editors directly.
In addition to submitting your paper to IEEE Software, you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE’s data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission.