monday Service + LangSmith: Building a Code-First Evaluation Strategy from Day 1
Blog post from LangChain
Monday.com has developed an evals-driven development framework for its AI Native Enterprise Service Management platform, designed to automate and resolve inquiries across various service departments. By integrating evaluation as a core component from the outset, the company has significantly accelerated feedback loops, enabling comprehensive testing across numerous examples in minutes rather than hours. The framework employs a dual-layered evaluation approach: offline evaluations act as a safety net, using curated datasets to ensure core logic and specific edge cases are robust, while online evaluations provide continuous quality monitoring in real-time production environments. The evaluations are managed as version-controlled code, using GitOps-style CI/CD deployment, which enhances agent observability and ensures high-quality AI interactions. The platform's architecture allows for parallel and concurrent testing, drastically improving evaluation speed and efficiency. This structured approach to evaluations, with tools like LangSmith and Vitest, reflects a commitment to rigorous testing standards akin to production code management, ensuring the AI service workforce remains reliable and adaptable to various enterprise service management use cases.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 7 | 6,184 | 1,012 | 245 | +27% |
| Agent Evaluations | 3 | 277 | 81 | 30 | +98% |
| Real-time | 3 | 6,860 | 1,508 | 282 | +0% |
| MCP | 2 | 4,921 | 488 | 178 | -5% |
| AI Agents | 1 | 4,753 | 1,020 | 259 | -5% |
| Observability | 1 | 4,175 | 699 | 181 | +22% |
| Platform Engineering | 1 | 654 | 190 | 69 | +42% |
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