Trust Is Built on What Users Can See, Not Just What Your Agent Gets Right
Accuracy tells you how often an agent is correct. Transparency tells the user *why* they should believe it this time. In the Agentic AI-as-a
J. Okafor · Jun 20, 2026 · 13 min
Reliability
Measuring, testing, and trusting agents in production. · 55 articles
Measuring Hallucination Rates in Agentic Workflows (Without Fooling Yourself)
Most teams report a single hallucination percentage and call it a day. That number is almost always wrong, not because the math is hard, bu
A. Reyes · Jun 19, 2026 · 13 min
Tracing a Multi-Step Agent Run End to End: The Observability Skill That Decides Whether Your GaaS Survives Production
When an autonomous agent fails, the question is never "did it fail?", it's "where, in the forty-three steps it took, did it go wrong, and w
A. Reyes · Jun 13, 2026 · 16 min
Shadow Mode: How to Run AI Agents Silently Before You Let Them Touch a Customer
Shadow mode means running an agent against real, live production traffic while keeping its actions invisible to the user and the downstream
S. Bauer · Jun 13, 2026 · 17 min
Reliability SLAs: What GaaS Vendors Are Actually Promising (and What They're Quietly Not)
Most "reliability SLAs" from Agentic AI-as-a-Service vendors guarantee infrastructure uptime, not whether the agent does its job correctly.
E. Marchetti · Jun 12, 2026 · 12 min
The Observability Data an Enterprise Buyer Demands Before Signing
Enterprise buyers no longer accept "trust us, it works" from agentic AI vendors. Before they sign, procurement and security teams now ask fo
C. Whitlock · Jun 7, 2026 · 14 min
Why Reliability, Not Intelligence, Decides the GaaS Winners
The smartest agent rarely wins the contract. In Agentic AI-as-a-Service, buyers don't pay for raw capability, they pay for an outcome that
R. Devi · Jun 6, 2026 · 15 min
Verification Layers: Checking an Agent's Work With Another Agent
The cheapest way to make an unreliable agent trustworthy isn't a smarter base model. It's a second agent whose only job is to check the firs
T. Brennan · Jun 5, 2026 · 13 min
Golden Datasets for Vertical Agent Evals: The Quiet Work That Decides Whether Your Agent Ships
A golden dataset is the curated set of real tasks, with verified correct outcomes, that you measure your vertical agent against. For agentic
T. Brennan · Jun 3, 2026 · 16 min
Post-Mortem Culture for Agent Failures: How GaaS Teams Learn From What Goes Wrong
When an autonomous agent fails, the temptation is to patch the prompt, ship the fix, and move on. The teams winning in Agentic AI-as-a-Servi
N. Adeyemi · Jun 3, 2026 · 13 min
Multi-Agent Reliability: When One Weak Agent Breaks the Whole Chain
In a multi-agent system, overall reliability is rarely the average of its parts, it's closer to the product of them. Chain three agents tha
S. Bauer · May 30, 2026 · 15 min
The Audit Trail Every Autonomous Agent Should Produce
An autonomous agent that can't tell you *what it did, why, and on whose authority* is a liability, not a product. A proper audit trail captu
T. Brennan · May 29, 2026 · 17 min
Eval-Driven Development for Agent Teams: How to Ship Agents That Actually Work
Eval-driven development (EDD) flips the agent build process: instead of writing the agent first and testing it later, you write the evaluati
S. Bauer · May 27, 2026 · 13 min
The Silent Failure Problem: When AI Agents Confidently Do Nothing Useful
An agent that crashes is easy to catch. An agent that finishes its run, reports success, and quietly produces garbage is the expensive one.
J. Okafor · May 26, 2026 · 14 min
The Eval Tooling Buyer's Guide for Agent Teams: How to Choose Without Getting Burned
Most agent teams buy eval tooling backwards. They shop for dashboards and leaderboard integrations before they've defined what "correct" eve
N. Adeyemi · May 25, 2026 · 14 min
The Benchmark Wars: Which Agent Leaderboards Actually Matter
Most agent leaderboards measure the wrong thing for the wrong reasons, and the gap between a top score and a deployable product is where Gaa
R. Devi · May 11, 2026 · 12 min
The Trust Gap: Why "Capable" AI Agents Still Don't Get Deployed
Most agents that fail to ship don't fail a capability test. They fail a trust test. A vendor demos an agent that books travel, reconciles in
R. Devi · May 10, 2026 · 14 min
Why Every GaaS Company Needs a "Reliability Number" on Its Homepage
Most Agentic AI-as-a-Service homepages lead with capability claims, "autonomous," "10x faster," "human-level." Almost none of them publish
T. Brennan · May 7, 2026 · 15 min
The Reliability Moat: Why It's Harder to Copy Than Capability
In the Agentic AI-as-a-Service market, raw capability has become a commodity that resets every time a frontier lab ships a new model. Reliab
A. Reyes · May 5, 2026 · 13 min
The "Agent Did the Wrong Thing Correctly" Failure Mode, And Why It's the Hardest One to Catch
The scariest agent failures aren't the ones that crash. They're the ones where every step executes cleanly, every tool call returns a 200, e
L. Karlsson · Apr 28, 2026 · 14 min
Why "Escalate to Human" Is the Most Underrated Reliability Feature in Agentic AI
The fastest way to make an autonomous agent more reliable isn't a smarter model or a longer prompt. It's teaching the agent when to stop and
E. Marchetti · Apr 25, 2026 · 13 min
Canary Deployments for Agent Updates: Shipping Agent Changes Without Breaking Production
A canary deployment routes a small slice of live traffic to a new agent version, watches it closely, and promotes it only if it behaves. For
R. Devi · Apr 24, 2026 · 14 min
From QA Engineer to Eval Engineer: The Career Pivot Quietly Reshaping AI Companies
If you've spent years writing test plans, filing bugs, and arguing with developers about what "done" means, you already have most of the ins
M. Hale · Apr 21, 2026 · 13 min
Did the Agent Do What the User *Meant*? How to Actually Measure It
Task success rate tells you whether an agent completed *a* task. It doesn't tell you whether it completed the *right* one. Measuring "did th
R. Devi · Apr 20, 2026 · 12 min