Operations Articles
21 articles · Page 1 of 2
How to Run the Agent Development Lifecycle (ADLC) in Production
Shipping an AI agent is easy. Keeping it reliable after launch is hard. The ADLC walks you through Intent, Build, Evaluate, Deploy, Observe, then back around.
Your Agent Re-reads Its Own Manual on Every Call
Datadog's 2026 State of AI Engineering report found that 69% of input tokens go to system prompts, yet only 28% of LLM calls use prompt caching. Here's how to diagnose the problem and fix it without rewriting your agent.
Shadow Mode: Deploy AI Agent Updates Without Risk
Shadow mode runs your new agent version in parallel with production, comparing behavior before customers ever see it. Here's how to build the full deployment pipeline from shadow to canary to 100%.
How to Build a Cart Recovery Agent (and When to Send Nothing)
Most cart-recovery flows are three discount emails. A real recovery agent decides why the customer left, picks the right channel, caps the discount to protect margin, and sometimes sends nothing at all. Here is how to build it.
Build a Returns Voice Agent That Can't Refund Itself Broke
Returns are 60% of peak ecommerce contact volume. Most voice agents will refund $4,000 on a prompt injection. Here's how to build one that physically can't.
Build a Nurture Agent That Decides Not to Send
Most nurture sequences are 14 emails on a calendar. The fix is an event-triggered agent whose most valuable action is wait. Here's the worker.
How to Build a Real Estate Showing Voice Agent (MLS, Lockboxes, TCPA)
Build a real estate voice agent that pulls live MLS data, parses showing instructions, books tours, and sends lockbox codes at the right time.
Reasoning Tokens Are Showing Up on the Bill
GPT-5 and Claude thinking tokens bill as output and stay invisible. A 200-token reply can hide 8,000 billable ones. How to measure, cap, and budget.
74% of Production Agents Still Rely on Human Evaluation
A survey of 306 practitioners reveals most production agents are far simpler than expected. The eval gap isn't a tooling problem. It's a trust problem.
What to Trace When Your AI Agent Hits Production
OpenTelemetry GenAI conventions are the production standard for agent tracing. What to instrument, what to skip, and what breaks — from a 2 AM debugging war story.
The AI Agent Dashboard of 2026: What Teams Actually Need to See
Traditional dashboards tell you what went wrong yesterday. The AI agent dashboards teams actually need deliver feedback in the moment, during the call, not after it. Here's what that looks like in practice.
Stop Reacting to Bad Calls. Catch Problems Before Customers Do
By the time a customer complains, you've already lost. Real-time analytics lets AI agent teams catch failing conversations mid-flight, not in the post-mortem. Here's how to build a proactive monitoring stack that prevents pain instead of documenting it.
The Signal Briefing
One email a week. How leading CS, revenue, and AI teams are turning conversations into decisions. Benchmarks, playbooks, and what's working in production.
