Agent-based coding introduces new quality risks to teams that rely primarily on traditional testing approaches. Because agents default to ""best guesses"" when provided insufficient or underspecific context, these gaps—if left unchecked—can result in production issues related to performance, stability, or unexpected edge cases. However, when teams provide clear invariants and non-functional requirements coupled with review cycles that ensure they're met, agents can produce significantly higher quality code, reducing downstream maintenance costs.
This talk presents an invariant-driven framework for deciding what to verify and where those checks belong in your pipeline. We'll introduce a simple invariant taxonomy that delivers immediate benefits through verification. The taxonomy is based on scope (universal across any repo, system/architecture-specific, or feature-level) and type of check (data contract, business logic, or performance/SLA), coupled with the target remediation (advisory only, block merge, or rewrite).
We'll conclude with a before-and-after demo leveraging Tessl's Specification Registry that demonstrates the benefits of incorporating invariants into your agentic coding workflows. Attendees will leave with a practical checklist they can apply immediately.
While most people idly ponder whether the glass is half full or half empty, Jennifer Sand goes right to the source, asking where is the waiter?, what is the problem?, and how can I get the waiter's attention, thereby solving this problem as efficiently as possible? That same enterprising attitude motivated Jennifer to leave West Virginia to study at Wellesley College in Massachusetts. Jennifer has spent decades in Series A startups to public companies, honing her tech skills. At Everbridge, she drove growth from $5M to $75M ARR. At CloudLock, she helped build a solution through its $293M acquisition by Cisco. As Co-Founder and CEO of Codential, Jennifer is solving a problem she's witnessed throughout her career: even the best teams spend significant time chasing preventable quality issues.
Brandy Pielech is a seasoned technology executive and Co-Founder & CTO of Codential.ai, bringing deep technical expertise in constraint solvers, cybersecurity, distributed systems, and streaming processing. Throughout her career, she has led engineering organizations across companies at every stage, from Series A startups to public enterprises, including leadership roles at Toast, Cisco, CloudLock, and BAE Systems. Brandy holds both BS and MS degrees in Computer Science from WPI and is passionate about building high-performing engineering teams that deliver customer value while improving operational efficiency. She lives in the Boston suburbs with her spouse and two kids and when not doing all things AI, she enjoys gardening, gaming, and watching NASCAR races from start to finish.
