The slop cannons in your engineering org - by Jake Handy

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The slop cannons in your engineering org<br>A field guide to the engineers and designers firing AI agents at every problem in sight

Jake Handy<br>May 07, 2026

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Getting this out of the way first: I’m writing this as someone who loves Cursor and Claude Code. I once spent a Sunday evening having Claude Code build scripts for automated social media video counting while I was simultaneously playing Diablo IV, and it was, for the record, a great Sunday night. You won’t find a bigger believer in agent-driven dev on Substack.<br>Which makes what I’m about to say more credible, not less. There is a specific, identifiable type of person inside modern SaaS organizations who has weaponized these tools against their own team. They run agents like a slot machine. They generate output the way a lawn sprinkler generates water. They confuse volume for value, velocity for progress, and tokens spent for problems solved.<br>The term I’ve heard that best describes the phenomenon: slop cannons.<br>@yrechtman Slop Cannon is in the OpenAI vocab","username":"Jack_Raines","name":"Jack Raines","profile_image_url":"https://pbs.substack.com/profile_images/2020253173034954752/l7B6KGok_normal.jpg","date":"2026-05-05T23:11:37.000Z","photos":[],"quoted_tweet":{"full_text":"@signulll CEO + a few slop cannons","username":"ryanbrewer","name":"Ryan Brewer","profile_image_url":"https://pbs.substack.com/profile_images/1930678973832273921/nW8TIqv9_normal.jpg"},"reply_count":1,"retweet_count":2,"like_count":10,"impression_count":4181,"expanded_url":null,"video_url":null,"belowTheFold":false}" class="pencraft pc-display-flex pc-flexDirection-column pc-gap-12 pc-padding-16 pc-reset bg-primary-zk6FDl outline-detail-vcQLyr pc-borderRadius-md sizing-border-box-DggLA4 pressable-lg-kV7yq8 font-text-qe4AeH tweet-fWkQfo twitter-embed">

Jack Raines@Jack_Raines

Congrats @yrechtman Slop Cannon is in the OpenAI vocab

Ryan Brewer @ryanbrewer

@signulll CEO + a few slop cannons

11:11 PM · May 5, 2026 · 4.18K Views

1 Reply · 2 Reposts · 10 Likes

What’s a slop cannon?

A slop cannon is often an engineer or designer (or one of those “designer-engineer” hybrids with weird LinkedIn bios) who has converted their workflow into a high-throughput AI artifact firehose. They have a recognizable shape:<br>They run more than three AI agents in parallel as a default setting, not an exception, often launching a slew of them from their phones in the morning to check on a few hours later.

Their PRs are large, fast, and confident, and the median one needs a follow-up patch within two weeks.

They post terminal screenshots in Slack with rocket emojis.

They cannot explain their own diff.

They distrust other people’s code reviews more than the model’s.

They incessantly use the phrases like “the agent figured it out” and “Claude can handle that.”

Slop cannons are not inherently bad developers. They are, in many cases, very good developers, and that’s what makes this pattern dangerous. They have enough taste to ship something desirable and enough velocity to ship a lot of it.<br>What the slop cannon produces

In March 2026, AI agents generated roughly 17 million pull requests per month on GitHub, up from 4 million in September 2025. That is a 325% increase in six months. Voiceflow’s head of cloud infrastructure, Xavier Portilla Edo, put the legitimacy rate at “1 out of 10,” meaning 90% of those agent-authored PRs are noise the maintainer has to sort.<br>Reported AI-agent PR volume on GitHub rose from roughly 4 million per month in September 2025 to 17 million this March. Separately, GitHub COO Kyle Daigle said platform activity had reached 275 million commits per week and 2.1 billion GitHub Actions minutes per week. Third-party analysis estimated Claude Code at about 4.5% of public GitHub commits in March 2026.<br>Claude Code alone now accounts for 4.5% of all public GitHub commits. Weekly commits across the platform hit 275 million in early 2026, a 14x year-over-year increase. GitHub Actions usage crossed 2.1 billion minutes per week. None of that scaled because humans got 14x more productive. It scaled because the cannons are firing.<br>The platform is feeling it. In early April, GitHub had five outages inside 48 hours: a 2.7-hour Copilot backend exhaustion, an 8.7-hour code search blackout, an audit-log incident, four hours of Copilot Cloud Agent degradation, and a coding-agent job-startup failure. Five outages. Two days.<br>Handy AI is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

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At the artifact level the picture is uglier. CodeRabbit's December 2025 analysis of 470 open-source pull requests found AI-coauthored PRs contained 1.7x more issues than human-only ones, with 1.4 to 1.7x more critical and major findings, and logic and correctness errors 75% more common. Veracode's 2025 GenAI Code Security Report tested over 100 LLMs...