GGML

GGML AI

GGML AI

GGML AI

GGML AI

GGML AI

GGML AI

GGML AI

GGML AI

GGML AI

GGML AI

Research-Driven Agents: What Happens When Your Agent Reads Before It Codes

Coding agents working from code alone generate shallow hypotheses. Adding a research phase ( arxiv papers, competing forks, other backends) produced 5 kernel fusions that made https://github.com/ggml-org/llama.cpp CPU inference 15% faster. submitted by /u/Southern-Papaya [link] [comments]

Layman: Agentic Insight and Oversight (same same but different)

What's the most common duplicate project on r/ClaudeAI? Usage trackers. What's the second most common? AI Monitors. Does Layman do those things? Yes, of course. So what makes it different? Layman's Dashboard, Flowchart, and Logs view (with Layman's Terms and Analysis examples) Like many similar tools, Layman runs as a web service in a container on your local machine. It installs hooks and accesses harness logs to "look over your shoulder," then leverages a secondary AI instance to help keep your multiple sessions, sub-agents, and alternate harnesses in line. So, short answer: Drift Monitoring. Repeatedly named as one of the most frustrating issues for heavy Claude Code users, Layman takes into account all user prompts issued to CC as well as current project and global CLAUDE.md instructions, and at configurable intervals scores the current degree of "drift" occurring from your goals and the rules you have established. You can optionally receive warning notifications or place a block when different thresholds are reached. Risk Analysis. Layman will classify all tool calls and operations with a "risk" level based on simple, consistent criteria (such as read-only, writing, modifying, network access, deletion, etc.) and can automatically analyze the AI agent's current intended action, the overall goal or purpose behind that intention, and summarize the safety and security implications at stake. Layman's Terms. The eponymous origin of the tool, offering a plain-language (and if possible non-technical) explanation of the purpose of any given tool call. It can summarize what was performed at the session level as well, helpful for later recall and understanding after some time has passed. Vibe coders aside, should a professional developer already have knowledge of what their tools are doing before they grant permission? Yes, of course, but when you are operating at scale and (say) that TypeScript project you are polishing needs to look up some JSON value and your AI agent writes a one-off Python script to parse it out, it can be helpful to have an "extra pair of eyes" taking a look before you effectively begin yet-another code review. Meanwhile, typical features you might come to expect are included, from Session Recording (opt-in is required first for data tracking and there is no telemetry to worry about), Bookmarking, and Search, PII filtering (including PATs and API keys), File and URL access tracking, and a handy Setup Wizard for helping get those hooks installed in the first place and walking you through configuration of core capabilities. Did I mention besides Claude Code it supports Codex, OpenCode, Mistral Vibe, and Cline (with more to come)? Whether using these for local agents or as an alternative when hitting session limits, Layman can monitor and track them all at once. But wait, doesn't a "secondary AI instance" just end up wasting tokens? My Precious? (erm...) Our precious, precious tokens? When session limits already hit so hard? It turns out these algorithms do not require nearly the level of "intelligence" you might desire for your planning and coding sessions themselves. Personally I keep an instance of Qwen3-Coder-Next running locally via llama.cpp server on my system's GPU to field those calls, with no discernible impact on system performance. And when a local LLM is not available, Haiku does the job excellently (now you have a reason to use it). You absolutely do not need to use anything more resource-intensive to get the job done. Now you have a complete picture. GitHub repository: https://github.com/castellotti/layman License: MIT submitted by /u/jigsaw-studio [link] [comments]