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Earlier sources: AI agents
AI agents use models to choose actions, call tools, and work toward a goal. This thread follows agent frameworks, memory, orchestration, evaluation, and safeguards; autonomy and reliability vary between systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗830 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
SkillScaffold: Scaffolding Agentic Reinforcement Learning with Policy-Adaptive Skill Credit Assignment and Selective Injection ↗
Agentic reinforcement learning (RL) enables large language models (LLMs) to learn from multi-turn interactions with verifiable outcomes. Textual skills can improve exploration by distilling prior interactions into reusable guidance. However, existing skill-based RL approaches often either assume skill injection is beneficial or rely on indirect feedback or rollout-intensive evaluation to assess its utility. Our pilot studies show that rollout-based utility estimation for skill credit assignment is costly and unstable under limited sampling, while skill benefits vary across candidates and depen…
- GitHub · Repository created · First archived
pycodebr/heditor ↗
Creative vertical video editing skill for AI agents (Claude Code, Codex, OpenCode, Cursor, Hermes): named styles, creative mode, HyperFrames + voice-first mix.
- GitHub · Repository created · First archived
JonathanQUANLEE/JobKoi-AI ↗
JobKoi-AI (求职锦鲤) · 全智能求职锦鲤助手 ｜ 基于 AI 智能管家驱动的 BOSS直聘/猎聘/51Job 全流程拟人化自动化投递与求职提效神器
- Hacker News · Posted on Hacker News · First archived
Show HN: Mac Markdown reader for your AI agents ↗
Hi HN, I'm Kirill. A dozen coding agents running in parallel, producing walls of suggestions, comments and ideas, all at once, all crammed into 88 columns of terminal scrollback, all gone the moment you run the next command. Does this sound familiar? FolderMd ( https://foldermd.com ) might be for you. It's free, and it's fast, and your agents can use it. I made it because I just couldn't handle it anymore. It's a small Mac app that gives those do…
- Hacker News · Posted on Hacker News · First archived
Agentic AI for network incident response ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Agor, multiplayer AI – stop running agents alone ↗
Hacker News discussion.
- arXiv · Published · First archived
Towards Safe Autonomy for Computer Use ↗
The safety of LLM-based agents currently rests on alignment training and safety classifiers, neither of which can rule out that a sophisticated indirect prompt injection (IPI) goes through and causes significant harm. Recent work therefore builds agents with information-flow guarantees that rely on structured tool interfaces to interact with the environment. Computer Use Agents (CUAs) act visually on the computer screen, which does not provide a boundary between trusted first-party interfaces and untrusted, potentially attacker-authored content. Actions are equally ambiguous: a click may land…
- Hacker News · Posted on Hacker News · First archived
Mobile Tunnel: Giving AI agents control of Android to drive drones and IoT ↗
Hacker News discussion.
- arXiv · Published · First archived
ReTerm: Recovery Training for Self-Improving Terminal Agents ↗
Terminal agents have shown strong abilities in complex coding tasks. However, they often struggle to recover from errors during long-running execution (e.g., command errors, faulty implementations), eventually leading to task failures. To this end, we present ReTerm, a self-improving terminal agent trained by learning how to recover from its own failed terminal tasks. To support its training, we construct a customized data pipeline and produce ReTerm-10K, a high-quality dataset that provides effective recovery demonstrations for SFT cold start. Furthermore, we propose ReTerm-GRPO, an online RL…
- Hacker News · Posted on Hacker News · First archived
Anthropic offers £145k for London personal assistant amid AI agent boom ↗
Hacker News discussion.
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about AI agents
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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