Can we live dangerously? Sandboxing Claude, and the Claude foreman that runs the rest
How Scout runs a pen full of Claude agents behind one foreman, inside a sandbox with zero blast radius, credentials and all.
How Scout runs a pen full of Claude agents behind one foreman, inside a sandbox with zero blast radius, credentials and all.
The model isn't the only lever, and it's rarely the one you control. What you feed it is. A look at how Claude actually uses prompts, skills, and AGENTS.md, how to write each one well, and how we wire all three into Corral.
AI applications need two layers of monitoring: LLM observability for output quality and token costs, and traditional APM for the application code underneath. A practical guide to what tools cover which layer.
Your AI coding agent can read your codebase but not your production data. MCP changes that. Here is how to connect monitoring to your development workflow.
An honest comparison of the 10 best application monitoring and observability tools in 2026. Covers Scout Monitoring, Datadog, New Relic, Grafana Cloud, Sentry, Elastic Observability, AppSignal, Honeybadger, Honeycomb, and Better Stack with pricing, setup time, and use case guidance.
Sentry is error-first. Datadog is infrastructure-first. An honest comparison for teams choosing between them for error monitoring, with notes on where Scout fits.
Three monitoring tools means three context switches per debugging session. One tool with linked errors, traces, and logs gets you to root cause faster.
The Scout MCP server connects your AI assistant directly to your Scout Monitoring data. Here's how teams are using it, what prompts work well, and what shipped in June.
An honest comparison of the best APM and monitoring tools for small teams (2-20 engineers) without dedicated DevOps or SRE. Covers Scout Monitoring, AppSignal, Honeybadger, Sentry, New Relic, and Datadog.
Comparing the best error monitoring tools for Node.js in 2026. Covers Express and NestJS error handling with honest reviews of Scout Monitoring, Sentry, Bugsnag, Rollbar, and Datadog.
An honest comparison of the best APM tools for Node.js in 2026. Covers Scout Monitoring, Datadog, New Relic, AppSignal, Dynatrace, and PM2 Plus for Express and NestJS teams.
AI makes building faster. It also makes production problems faster. If you ship without monitoring, you are flying blind at 10x speed.
A practical comparison of APM tools for small development teams without dedicated DevOps or SRE. Covers Scout, Sentry, Honeybadger, AppSignal, New Relic, and Datadog.
Looking for a Sentry alternative? A practical comparison of tools that offer more integrated APM, simpler pricing, or better fit for specific languages and team sizes.
How to switch from Datadog to Scout, what to expect, and what BackerKit learned when their 5-person team made the move.
A practical look at APM tools for Elixir and Phoenix applications as of May 2026.
We've shipped API updates, two MCP server options, and a new CLI — all designed to get Scout's performance data to the AI tools you already use.
A look at APM tools for Ruby on Rails as of March 2026.
A comparison of Scout and Datadog, with a look at each platform's strengths and feature coverage.
Scout and Sentry both handle error monitoring and performance, but they started from different places, which shapes what each does well. If you are evaluating both, the origin story is worth understanding because it explains most of the differences you will run into.
A review of the state of APM tools for Python in 2026.
A comparison of how Scout and AppSignal each approach application monitoring.
A relatively deep dive on the new built-in Ruby parser and options for manipulating the AST for fun and observability.
Take a look at the state of error monitoring in 2026 as we review the top error monitoring solutions for fast detection, actionable alerts, integration options, and support for various engineering needs.
Compare Scout and New Relic APM: pricing, framework support, and the case against per-user observability pricing. Unlimited users on every Scout plan.
AI-native monitoring is designed for teams shipping AI-generated code. It brings errors, metrics, and performance data into your LLM, where you already work. Learn how this new approach helps developers tame black-box AI code, cut tool sprawl, and stay in flow — making apps built with AI-generated code easier to debug, scale, and trust.
What happens when issues aren't obvious? Good monitoring can keep you in the know and a step ahead of your users, preventing broken trust and lost revenue.
A side-by-side look at Scout vs. Sentry application monitoring. Which tool is the best fit for your application?
An honest comparison of the best error monitoring tools in 2026, including Scout Monitoring, Sentry, Datadog, New Relic, AppSignal, Honeybadger, Bugsnag, and Rollbar.
A practical look at APM tools for PHP and Laravel applications as of May 2026.
Comparing the best Python error monitoring tools in 2026 for Django, Flask, and FastAPI. Honest reviews of Scout Monitoring, Sentry, Bugsnag, Rollbar, AppSignal, and Datadog.