Synthetic vs. Real-World Evals: Getting the Mix Right
Synthetic evals are cheap, fast, and infinitely scalable, but they flatter your agent. Real-world evals are messy, slow, and expensive, an
E. Marchetti · Apr 19, 2026 · 12 min
Reliability
Measuring, testing, and trusting agents in production. · 55 articles
Continuous Evaluation in Production: Why Pre-Launch Testing Is the Easy Part
Most teams shipping Agentic AI-as-a-Service treat evaluation as a gate you pass once before launch. That's backwards. The model underneath s
R. Devi · Apr 19, 2026 · 13 min
Guardrail Testing: How to Red-Team Your Own AI Agents Before They Embarrass You
Guardrail testing means deliberately attacking your own AI agents to find where they break, leak, overspend, or take dangerous actions, bef
S. Bauer · Apr 18, 2026 · 18 min
Drift Detection: How to Catch an AI Agent That's Slowly Getting Worse
Agent drift is the quiet erosion of a deployed agent's quality over time, even when nothing in your code changed. It shows up as a slow slid
J. Okafor · Apr 13, 2026 · 13 min
The Eval-Platform Vendors to Watch (And How to Tell the Real Ones from the Demos)
If you're buying or building agentic AI-as-a-service, the eval platform you choose matters more than the model you run on. The honest list r
C. Whitlock · Apr 13, 2026 · 12 min
The Latency-Reliability Tradeoff in Production Agents: Why Faster Usually Means Wronger
Every production AI agent makes a quiet bet: how much time to spend being sure versus how fast to answer. More verification steps, retries,
L. Karlsson · Apr 12, 2026 · 14 min
Agent Observability Tooling: The Emerging Category Map
Agent observability is splintering into at least five distinct tool categories, tracing, evaluation, monitoring, guardrails, and replay, a
C. Whitlock · Apr 11, 2026 · 13 min
The State of Agent Reliability: An Annual Benchmark Report
Agent reliability in 2026 is improving on paper and stalling in practice. Public benchmark scores keep climbing past 80% on curated tasks, y
C. Whitlock · Apr 6, 2026 · 11 min
Why Public Benchmarks Overstate Real-World Agent Reliability
Public agent leaderboards measure agents under conditions almost nothing like production: clean inputs, generous retry budgets, a single wel
L. Karlsson · Apr 5, 2026 · 11 min
Observability for Agent Memory: What Did It Remember, and Why?
When an autonomous agent makes a baffling decision, the cause is usually not the model and not the prompt you wrote today. It's something th
A. Reyes · Apr 5, 2026 · 13 min
Confidence Scoring: Can Agents Know When They're Wrong?
Short answer: not reliably, not yet, and not the way most buyers assume. Today's AI agents can produce a confidence number, but that number
C. Whitlock · Mar 27, 2026 · 12 min
Eval Benchmarks for Long-Horizon Agentic Tasks: What Actually Measures Whether Your Agent Holds Up
Long-horizon agentic tasks, the ones that span dozens or hundreds of steps, multiple tool calls, and stretches of autonomous work, break the b
E. Marchetti · Mar 27, 2026 · 13 min
Why Traditional APM Doesn't Work for Agents (And What Has to Replace It)
Application Performance Monitoring was built to answer a binary question: did the request succeed, and how fast? AI agents break that model
E. Marchetti · Mar 26, 2026 · 12 min
How to Build a Reliability Report Card for the Top Agent Platforms (Without Fooling Yourself)
Most "best agent platform" rankings measure capability, demos, and funding rounds. None of those predict whether the agent will do your work
L. Karlsson · Mar 25, 2026 · 12 min
The Eval Team: The New Role That GaaS Companies Are Quietly Building First
A new function is forming inside Agentic AI-as-a-Service companies: the eval team. Their job isn't to ship features or close deals, it's to
L. Karlsson · Mar 22, 2026 · 13 min
Human Review Workflows That Scale With Agent Volume (Without Drowning Your Team)
When you ship one agent doing 50 tasks a day, a human can eyeball every output. At 50,000 tasks a day, that math breaks instantly. The fix i
N. Adeyemi · Mar 15, 2026 · 14 min
The Cost of a False Positive vs. a False Negative, by Vertical: How Error Asymmetry Decides Where Agents Get Deployed
In agentic AI-as-a-service, the headline accuracy number tells you almost nothing about whether an agent is safe to ship. What matters is wh
M. Hale · Mar 15, 2026 · 14 min
Your Agent Didn't Change. The Model Underneath It Did. Now What?
When a model provider ships a new version, your agent's behavior can shift overnight even though you didn't touch a single line of code. Tra
M. Hale · Mar 13, 2026 · 14 min
The Reproducibility Problem: Why the Same Prompt Gives You a Different Answer Every Time
Run the identical prompt through the identical agent twice and you can get two different outcomes. This isn't a bug you can patch away, it'
N. Adeyemi · Mar 11, 2026 · 14 min
Standardizing Incident Severity for Agent Failures: A Practical Framework for GaaS Teams
Most teams running agentic AI-as-a-service inherited their incident severity scale from a traditional software playbook, and it quietly brea
J. Okafor · Mar 10, 2026 · 15 min
The Trust Dashboard Customers Actually Want From GaaS Vendors
Buyers of Agentic AI-as-a-Service have stopped being impressed by demos. What they want before signing is a live trust dashboard: task succe
M. Hale · Mar 8, 2026 · 13 min
Building an Eval Suite for an Autonomous Agent (Without Fooling Yourself)
An eval suite is the only thing standing between a demo that wows a buyer and an agent that quietly burns money in production. The hard part
L. Karlsson · Mar 5, 2026 · 13 min
Monitoring Agents Across Model-Provider Outages: A Survival Guide for GaaS Teams
When OpenAI, Anthropic, or Google has a bad day, your agents do too, but they fail in stranger ways than a website does. An agent doesn't j
N. Adeyemi · Mar 4, 2026 · 14 min
The Famous Agent Failures of 2025-2026, Dissected
The headline agent disasters of this cycle weren't caused by dumb models. They were caused by capable agents doing exactly what they were to
C. Whitlock · Feb 25, 2026 · 13 min