PAgE 2026

AI-powered agents now run in production: they plan, call tools, and act on live services and data. Yet the formal methods foundations required to make these systems safe and reliable remain underdeveloped. Ensuring their correctness and reliability demands a new discipline we term agentic engineering that combines principles from programming languages, formal verification, and neuro-symbolic reasoning to analyze, test, and repair agents at scale. This workshop aims to address key questions surrounding agentic engineering and to foster a community of researchers engaged in this area. There is a clear opportunity across the PL, software engineering, and machine learning communities to build agentic systems with precise specifications, verifiable behaviors, and runtime checks that hold up in production.

Call for Papers

This workshop aims to bring formal methods and AI communities together to advance the principles of safe agentic engineering. It will feature peer-reviewed papers and invited talks from experts in the field. We welcome artifacts, datasets, case studies, and experience reports. Topics include (but are not limited to):

• Specifications and type-safe interfaces for tool use

• Memory and state management for agents

• Reliability & groundedness in planning and tool use

• Static & dynamic analysis and verification of agentic plans

• Safe integration with software engineering workflows

• Runtimes, compilers and virtual machines for agentic programs

• Evaluation methods and benchmarks for trustworthy agents (safety, reliability, cost/latency)

• Safety, security, and privacy of multi-agent systems

• Testing and debugging agentic workflows