E2B

Gemma 4 Deep Dive — Cassidy Hardin, Researcher, Google DeepMind

Apr 27, 2026 · 19:03

Cassidy Hardin, a researcher at Google DeepMind, details the Gemma 4 family of open-source models, claiming they set a new precedent for small-scale performance. The family includes two on-device effective models (E2B and E4B) with Per Layer Embeddings (PLE) stored in flash memory, and two larger models: a 26B mixture-of-experts (MoE) with 128 total experts (8 active) and a 31B dense model that ranked #3 on the LM arena leaderboard, outperforming models 20x its size. Architectural innovations include interleaved local/global attention (5:1 ratio, sliding windows of 512/1024 tokens), grouped query attention (8 queries per key-value in global layers), and native multimodal support with variable aspect ratios and resolutions for vision encoders (550M params for large, 150M for small) plus a 305M parameter conformer for audio. All models are released under Apache 2.0 license, available for self-hosting on Hugging Face and Ollama, or cloud deployment on Vertex AI.

Paperclip: Open Source Human Control Plane for AI Labor — Dotta Bippa

Apr 15, 2026 · 24:34

Dotta Bippa introduces Paperclip, an open-source human control plane for AI labor that lets you manage an org chart of agents to run a zero-human company. The tool enables you to hire employees, set goals, automate jobs, and bring your own agent (e.g., Gemini, Claude, Codex) with skills and instructions. Paperclip supports reliable workflows like QA reviews and approvers, and routines for recurring tasks such as summarizing PRs or writing changelogs. Dotta demonstrates creating a Remotion video celebrating Paperclip's 40,000 GitHub stars (now 50,000) by instructing the CEO agent to hire a video writer and apply brand guidelines—something that would have taken a week becomes an afterthought. Paperclip is not just for coding; it handles marketing, sales, and finance. Upcoming features include CEO chat, maximizer mode, multi-user support, cloud deployments, and a desktop app, all aimed at giving humans control over AI labor.

How we hacked YC Spring 2025 batch’s AI agents — Rene Brandel, Casco

Jul 30, 2025 · 17:33

Rene Brandel, CEO of Casco, explains how his team hacked seven of sixteen YC Spring 2025 batch AI agents within 30 minutes each, revealing three critical security flaws: cross-user data access via IDOR, arbitrary code execution through code tools, and server-side request forgery (SSRF) from tool endpoints. They extracted personal data by exploiting missing authorization checks, overwrote security controls by writing malicious files into code sandboxes, and stole Git credentials by manipulating a database-schema tool. Brandel emphasizes that agent security extends beyond LLM prompt injection, advises treating agents as users with proper authentication and authorization, and warns against rolling custom code sandboxes, recommending out-of-the-box solutions like E2B. The talk concludes with a Q&A on extracting system prompts and the dangers of local coding agents.