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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 ↗842 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.
- Hacker News · Posted on Hacker News · First archived
Ask HN: What brings you back to personal AI agents like Instinct and Muse? ↗
Have you discovered daily routines and use cases that bring you back?
- Hacker News · Posted on Hacker News · First archived
Show HN: AI Agents: Zero to Hero – Learn AI Agents from Scratch in Pure Python ↗
Hacker News discussion.
- GitHub · Repository created · First archived
Elevatormusic/hermes-warm-compaction ↗
Hermes Agent context engine: the main model writes the compaction handoff on its cached prompt prefix
- GitHub · Repository created · First archived
skaragianis/lsty ↗
Terminal lists for Humans and Agents
- Hacker News · Posted on Hacker News · First archived
Schema-guard, stop AI agents from inventing column names in SQL ↗
Hacker News discussion.
- OpenAlex · Published · First archived
Evaluating Safety Embedding Prefiltering for Analyzing Millions of LLM Agent Social Network Messages for Security and Safety Harms ↗
Agentic social networks expose autonomous agents to large volumes of potentially malicious content, including prompt injection, social engineering, and unsafe execution requests. Large Language Model (LLM) judges can detect such content, but applying them at platform scale is expensive. We study the extent to which lightweight embedding-based prefilters can reduce this cost while retaining most of the judge’s unsafe predictions. We annotate 10,000 Moltbook posts and comments with a frontier LLM judge, assigning a binary safety verdict, severity level, malicious intent taxonomy labels, and Open…
- OpenAlex · Published · First archived
Toward AI-agent-driven particle transport simulations: implementation of AI-assisted workflows for PHITS ↗
Monte Carlo particle transport codes are powerful tools, but their use requires substantial knowledge of input preparation, execution, and result analysis. In this study, we present a code-side strategy for applying existing AI assistants and AI agents to PHITS. Two complementary sets of AI-ready resources were prepared from manuals, lecture materials, sample inputs, utility information, and developer-curated cautions: a bundled knowledge base for retrieval-augmented generation (RAG)-based assistants and a compact agent reference for direct use by AI agents. The knowledge base was loaded into…
- OpenAlex · Published · First archived
Plug-and-Play Dramaturge: A Divide-and-Conquer Approach for Iterative Narrative Script Refinement via Collaborative LLM Agents ↗
Although LLMs have been widely adopted for creative content generation, a single-pass process often struggles to produce high-quality long narratives. How to effectively revise and improve long narrative scripts like scriptwriters remains a significant challenge, as it demands a comprehensive understanding of the entire context to identify global structural issues and local detailed flaws, as well as coordinating revisions at multiple granularities and locations. Direct modifications by LLMs typically introduce inconsistencies between local edits and the overall narrative requirements. To addr…
- GitHub · Repository created · First archived
carverauto/agentboard ↗
Self-organized multi-agent orchestration framework with shared context, messaging, job board, and deep CI/git integration
- Hacker News · Posted on Hacker News · First archived
Give Your AI Agent a Domain-Specific Language ↗
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.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.