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speedscale

Flamegraphs Find It. Replay Proves It.

Aug 11, 2026 By Matt LeRay In Speedscale
I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU. This walkthrough gives the agent two independent witnesses: Together, they turn AI code verification into an experiment with two independent checks.
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cortex

DRIVE vs SPACE: What each framework measures and when to use them

Aug 11, 2026 By Ganesh Datta In Cortex
When Nicole Forsgren, Margaret-Anne Storey, and their coauthors published "The SPACE of Developer Productivity" in 2021, they settled an argument the industry had been losing for years. Productivity is not one number, and it is not a proxy like commits or story points. It is multidimensional, and any attempt to flatten it into a single metric will mislead you. Most of what came after in developer productivity measurement builds on SPACE. SPACE and DRIVE were built for different jobs.
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gitkraken

An 80% AI Adoption Rate Is Like an 80% Gym Membership Rate. It Doesn't Prove Anyone Got Stronger.

Aug 11, 2026 By Jade Nangah In GitKraken
Leadership has stopped asking whether your team is using AI. They’re asking what you’re delivering with it. That’s a harder question, because most of the numbers teams have been reporting, adoption rate, seats activated, prompts run, don’t actually answer it.
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Asset Infinity

Cooler Management Software: How Beverage Companies Track, Maintain and Optimize Coolers in the Field

Aug 11, 2026 By Himanish Ganguly In Asset Infinity
For beverage companies, deploying a cooler at a retailer, restaurant, supermarket, or distributor is only the beginning of the asset lifecycle. Once coolers move outside company facilities, maintaining visibility becomes far more difficult. Operations teams need to know where each cooler is located, who is responsible for it, whether it has been transferred, if maintenance is required, and whether the equipment is being used effectively.
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AI SRE Agent Debugs a Lambda Timeout with the AWS MCP Server: AURA

Aug 11, 2026 By Mezmo In Mezmo
A scheduled Lambda quietly stops completing and nothing pages you. AURA finds the function, reads its logs, and comes back with a three-second timeout. The usual path is opening the console, tracking down the right log group, and reading CloudWatch by hand. Here AURA connects to AWS through the MCP proxy AWS publishes, run locally with uvx against an AWS CLI that is already configured, so there are no new credentials to issue.
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upsun

Don't build the autonomous AI factory first

Aug 11, 2026 By Upsun In Upsun
Here's a scene playing out in engineering teams right now. An engineer spends the weekend running four or five coding agents in parallel. Monday morning, a teammate opens their laptop to 53 changed files with 2000+ diffs and a message that says, more or less, "should be good to merge." Nobody asked for this much output. Nobody has time to review it properly. The team doesn't feel faster. It feels ambushed.
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elmahio

Solving bugs with elmah.io and Claude Code - a real-life example

Aug 11, 2026 By Thomas Ardal In elmah.io
I spend most of my day in Claude Code these days. Most of my development processes changed after having access to my own personal assistant. In this post, I'll show you a real-life example of how bug fixes are often done on elmah.io now. I hope it will inspire someone to optimize their workflow and get even more out of their elmah.io subscription.
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