
AutoKernel - AI Agents That Write Faster GPU Kernels
RightNow AI releases AutoKernel, an open-source MIT-licensed framework that runs an autonomous LLM agent loop overnight to produce optimized Triton kernels for any PyTorch model.
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AI Infrastructure & Open Source Reporter
Sophie is a journalist and former systems engineer who covers AI infrastructure, open-source models, and the developer tooling ecosystem. She spent three years as a site reliability engineer at a cloud provider in Seattle before transitioning to tech journalism, which gives her writing an unusual level of technical depth - she understands distributed systems, GPU clusters, and inference optimization from the inside.
She studied Computer Engineering at the University of British Columbia and later completed a science communication fellowship at MIT. Her engineering background means she can read a model card, spot a misleading benchmark, and explain why quantization matters - all in the same paragraph.
At Awesome Agents, Sophie covers AI infrastructure news: new model releases, open-source launches, developer tools, deployment trends, and the hardware that makes it all run. She has a soft spot for underdog open-source projects that punch above their weight and a sharp eye for when a "breakthrough" is really just better marketing.
Based in Seattle, WA.

RightNow AI releases AutoKernel, an open-source MIT-licensed framework that runs an autonomous LLM agent loop overnight to produce optimized Triton kernels for any PyTorch model.

Meta's KernelEvolve AI agent autonomously generates and optimizes hardware kernels across NVIDIA, AMD, and MTIA chips, delivering over 60% inference gains in production.

Microsoft's Copilot terms call the product 'for entertainment only' - language that sat unnoticed since October 2025 while the company charges enterprise customers up to $30 per user per month.

Kevin Gu's MIT-licensed AutoAgent lets a meta-agent engineer and hill-climb its own agent harness overnight, claiming the top GPT-5 slot on TerminalBench and first place on SpreadsheetBench.

Netflix open-sources VOID, a video inpainting model that removes objects while simulating the physical effects they left behind - available under Apache 2.0 with a HuggingFace demo.

Cursor's ground-up IDE rebuild ships parallel agent orchestration, Design Mode for frontend work, and cloud-to-local session handoff - all in one unified workspace.

Google releases Gemma 4 with a 26B MoE, 31B Dense, and two edge variants under Apache 2.0 - claiming the highest intelligence-per-parameter of any open model.

Cloudflare's EmDash is an MIT-licensed CMS built on Astro 6.0 that sandboxes plugins in isolated Workers, ships a built-in MCP server, and targets WordPress's 42.5% share of the web.

A missing .npmignore entry in Claude Code 2.1.88 exposed 512,000 lines of TypeScript source, spawned the fastest-growing GitHub repo ever, and revealed unshipped features Anthropic never announced.

Arm says its 136-core AGI CPU is purpose-built for agentic AI workloads. Intel's data center chief - Arm's former head of solutions engineering - says the claim overstates what's actually new.

Cisco open-sourced DefenseClaw at RSA 2026 - a five-minute install that scans agent skills, MCP servers, and AI-generated code before they run, with 2-second policy enforcement and Splunk telemetry built in.

Microsoft's Harrier-OSS-v1 family delivers three MIT-licensed multilingual embedding models, with the 27B variant claiming top spot on Multilingual MTEB v2 at 74.3.