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1016 postsGLM 5.2 and the Open-Source Shakeup of AI Profit Margins
Zhipu AI's open-source GLM 5.2 rivals GPT-4o performance via MoE architecture while slashing inference costs, reshaping AI's profit margin economics.
FOMO-Driven AI Coding: Speed Illusion, Hidden Review Debt
GitHub's 55% speedup versus METR's 19% slowdown finding reveals how FOMO-driven AI coding adoption hides the real cost of review and verification in mature codebases.
Fixing JavaScript Observability Without Monkey-Patching
Sentry engineers are pushing Node's TracingChannel API into pg, mysql2, and redis to replace fragile JavaScript APM monkey-patching.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comCodeCrucible: A Reusable Blueprint for LLM-Driven SAST
Block's CodeCrucible offers a reusable design blueprint for LLM-driven SAST, using whole-repo analysis instead of snippet-anchored vulnerability scanning.
AI-Built Phishing Kits Are Industrializing Business Email Compromise
Two AI-built Phishing-as-a-Service kits automate Microsoft 365 takeover and invoice fraud, industrializing business email compromise at scale.
How Anthropic bakes security into its Claude-driven dev lifecycle
A look at how Anthropic embeds AI-driven security checks across coding, CI review, and deployment in its Claude-based dev lifecycle.
Static Scanner Finds 30 Unguarded Destructive Actions in AI Agent Frameworks
An open-source scanner analyzed 25 AI agent frameworks and confirmed 30 cases where models can delete data, deploy, or send webhooks unauthorized.
Agent-Native Software Engineering: Why Specs Alone Aren't Enough
Coding agents fail less at writing code than at holding architectural context. A look at spec-driven development's limits and what comes next.
Are AI Labs Gaming the Pelican-on-a-Bicycle Benchmark?
A statistical study generates 1,008 SVGs across 7 LLMs to test whether AI labs are secretly optimizing for the famous pelican-on-a-bicycle benchmark.
Emem: A Signed Memory Layer for Multi-Agent AI Systems
Emem gives AI agents a signed, verifiable memory layer for physical-world facts that survives context compaction across models and vendors.