Releasesby GlyphBayes now tracks every Reinforcement Loop fix and catches it when an issue comes back
Monte Carlo updated Bayes to track Reinforcement Loop issue statuses and automatically flag regressed issues if identical problems occur after a fix is marked complete.
Also shipped Nov 11, 2026Monte Carlo in November 2026 →
Web search in apps
Retool added native web search capabilities to the app builder Chat tab and app functions, enabling agent applications to query live web data via a managed Tavily account.
Pages are generally available
Databricks announced the general availability of Pages in Unity Catalog, providing governed definitions of business concepts organized by domain on the Discover page.
graphql-engine 2.51.6
Hasura released graphql-engine 2.51.6, fixing PostgreSQL source-catalog initialization and upgrade issues when logical replication publications include catalog version table updates on PostgreSQL 15.15 and newer.
graphql-engine 2.50.9
Hasura released graphql-engine 2.50.9 to resolve PostgreSQL source-catalog initialization and upgrade issues caused by logical replication publication checks on PostgreSQL 15.15 and higher.
GitHub App support for Enterprise Copilot seat management
GitHub Enterprise Apps can now invoke enterprise-level Copilot seat management APIs using the new Enterprise Copilot license management permission.
More from Monte CarloEvery Monte Carlo release →
See what your end users think of the agents you build in code, on the trace behind each one
Monte Carlo added end-user feedback tracking for code-based AI agents, attaching ratings, categories, and user comments directly to corresponding traces, runs, and conversations.
Eval datasets, curated by Bayes from your agents' real conversations
Monte Carlo introduced automated evaluation dataset generation by Bayes, creating Golden and Improvement datasets from an agent's scored conversations across intent and issue clusters.
Catch agents stuck in a loop with trajectory monitors
Monte Carlo added a repeats condition to trajectory monitors to detect when an AI agent makes consecutive identical tool calls with identical inputs and outputs within a single run.
Agent pages now open on the issues Bayes found
Monte Carlo updated agent pages to display issues found by Bayes in a dedicated view. Users can now access health, monitoring, and activity metrics through side panels without leaving the main interface.
Data products can now include your agents, not just their data
Monte Carlo data products now allow users to include AI agents, providing end-to-end lineage from source tables to the agent. This enables monitoring of both agent health and upstream data health in a single view.
Analytics API (Public preview): report on the health of the data behind your agents, from your AI tool
The Monte Carlo Analytics API is now in public preview, allowing users to query data health, alert status, and cost metrics directly from AI tools via the Monte Carlo MCP server.
Match dbt Cloud runs by warehouse account, host or database
Monte Carlo now allows dbt Cloud integrations to match runs based on warehouse account, host, or database fields. This improves lineage and alert accuracy for environments where multiple connections share the same warehouse.
Monte Carlo's Terraform provider is now on the OpenTofu registry
Monte Carlo has published its Terraform provider and agent modules to the OpenTofu registry, enabling users to manage Monte Carlo infrastructure as code using OpenTofu.