Back to CatalogPerma-Beta is how teams avoid accountability: never set a quality bar, never build an eval harness, and let the “beta” label absorb all complaints.
Agentic AI
Anti-Patterns
Perma-Beta
Keeping the agent in "beta" forever — so quality regressions stay someone else's problem.
Intent & Description
🎯 Intent
Shipping to real users under a beta label indefinitely — without the evaluation tooling needed to actually measure or gate quality across releases.
📋 Context
The agent launches in beta. Months pass. It’’s still beta — partly because quality hasn’’t been measured, partly because removing the label would commit to a bar nobody can defend. The label quietly shifts from “actively iterating” to “not our fault.”
💡 Solution
Build the eval harness and exit beta deliberately. Set a measurable quality bar and gate releases on it. See eval-harness, llm-as-judge, shadow-canary.
Real-world Use Case
- Never use this; treat indefinite beta as a process failure and exit it deliberately.
- Build an eval harness so quality regressions are visible before they reach users.
- Pair eval-harness with llm-as-judge and shadow-canary to gate releases.
Source
📌 TL;DR
Build an eval harness, set a quality bar, and exit beta — or “beta” becomes permanent liability cover.
Disadvantages
- User trust erodes with no SLA to point to when things go wrong
- Quality stagnates because there’’s nothing to improve against
- No defensible response when something fails in production