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A trillion dollars is a terrible thing to waste

OpenAI co-founder Ilya Sutskever just said the quiet part out loud: scaling laws are breaking down. Bigger models aren’t getting better at thinking, they’re getting worse at generalizing and reasoning. Now he’s eyeingneurosymbolic AIandinnate inductive constraints. Yep, the “just make it huge” era m.. read more  

A trillion dollars is a terrible thing to waste
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Practical LLM Security Advice from the NVIDIA AI Red Team

NVIDIA’s AI Red Team nailed three security sinkholes in LLMs:reckless use ofexec/eval,RAG pipelines that grab too much data, andmarkdown that doesn't get cleaned. These cracks open doors to remote code execution, sneaky prompt injection, and link-based data leaks. The fix-it trend:App security’s lea.. read more  

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Roses are red, violets are blue, if you phrase it as poem, any jailbreak will do

A new study just broke the safety game wide open: rhymed prompts slipped past filters in25 major LLMs, including Gemini 2.5 Pro and Deepseek - withup to 100% success. No clever chaining, no jailbreak soup. Just single-shot rhyme. Turns out, poetic language isn’t just for bard-core Twitter. When it c.. read more  

Roses are red, violets are blue, if you phrase it as poem, any jailbreak will do
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Advancing Our Chef Infrastructure: Safety Without Disruption

Slack pulled back the curtain onSlack AI, its LLM-powered assistant built with a fortress mindset. Every customer gets their ownisolated environment. Any data passed tovendor LLMs? It'sephemeral. Gone before it can stick. No fine-tuning. No exporting data outside Slack. And there’s a wholemiddle-lay.. read more  

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Why we're leaving serverless

Every millisecond matters in the critical path of API authentication. After two years of battling serverless limitations, the entire API stack was rebuilt to reduce end-to-end latency. The move from Cloudflare Workers to stateful Go servers resulted in a 6x performance improvement and simplified arc.. read more  

Why we're leaving serverless
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Declarative Action Architecture

The Declarative Action Architecture (DAA) is a scalable E2E testing pattern that separates concerns across three distinct layers. TheTest Layeris 100% declarative, statingwhatis being tested without any procedural logic, making tests read like documentation. The coreAction Layerimplements the execut.. read more  

Declarative Action Architecture
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Failure is inevitable: Learning from a large outage, and building for reliability in depth at

Datadog ditched its “never fail” mindset after a March 2023 meltdown knocked out half its Kubernetes nodes and took major user features down with them. The fix? A full-stack rethink built aroundgraceful degradation. The team addeddisk-based persistence at intake,live-data prioritization,QoS-aware re.. read more  

Failure is inevitable: Learning from a large outage, and building for reliability in depth at
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You’ll never see attrition referenced in an RCA

Lorin Hochstein argues that while high-profile engineer attrition is often speculated to contribute to major outages, it is universally absent from public Root Cause Analyses (RCAs). This exclusion occurs because public RCAs aim to reassure customers by focusing on technical fixes, whereas attrition.. read more  

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Comparing AWS Lambda Arm64 vs x86_64 Performance Across Multiple Runtimes in Late 2025

A new open-source benchmark looked at 183,000 AWS Lambda invocations, andarm64 beats x86_64across the board in both cost and speed. Rust on arm64 with SHA-256 tuned in assembly? It clocks in 4–5× faster than x86 in CPU-heavy tasks. Cold starts are snappy too—5–8× quicker than Node.js and Python... read more  

Comparing AWS Lambda Arm64 vs x86_64 Performance Across Multiple Runtimes in Late 2025
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The story of how we almost got hacked

Team Invictus caught a BEC attempt using WeTransfer to slip in a fake Microsoft 365 login page powered byEvilProxy. Classic Adversary-in-the-Middle move, but dressed up with a slick delivery package. Digging deeper, the team mapped the attacker’s setup and found something bigger: a credential grab c.. read more  

The story of how we almost got hacked
GPT-5.3-Codex is OpenAI’s advanced agentic coding model, designed to go beyond writing code and operate as a general-purpose collaborator on a computer. It builds on GPT-5.2-Codex by combining stronger coding performance with improved reasoning and professional knowledge, while running about 25% faster. The model is optimized for long-running tasks that involve research, tool use, and complex execution, and it performs at the top of industry benchmarks such as SWE-Bench Pro and Terminal-Bench.

Unlike earlier Codex models that focused primarily on code generation and review, GPT-5.3-Codex can reason, plan, and act across the full software lifecycle. It supports activities such as debugging, deploying, monitoring, writing product requirement documents, creating tests, and analyzing metrics. It can also autonomously build and iterate on complex applications and better interpret underspecified prompts, producing more complete and production-ready results by default.

A defining feature of GPT-5.3-Codex is its interactive, agentic workflow. Users can steer the model while it is working, receive progress updates, and adjust direction without losing context, making it feel more like a teammate than a batch automation tool. The model was even used internally to help debug its own training and deployment processes. GPT-5.3-Codex is available through paid ChatGPT plans in the Codex app, CLI, IDE extension, and web, with API access planned for the future.