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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 ↗861 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.
- GitHub · Repository created · First archived
kydlikebtc/awesome-jev ↗
1207 public resources for Jev, TypeSafe AI's System One decision model, indexed by decision pattern. Source citations, dated link checks and scheduled call-site text checks; runtime and performance are not independently tested here. EN/中文, JSON schema and platform compatibility.
- GitHub · Repository created · First archived
hlan98/JobHunterCat ↗
一只真正替你找工作的 AI 桌宠：它会找岗位、判断匹配度、帮你投递、盯 HR 回复，并根据你的求职结果不断调整策略
- OpenAlex · Published · First archived
Bounded Autonomy and Verifiable Safety for Agentic AI Enabled Automation ↗
Agentic AI-enabled automation cannot be safely deployed in high-stakes environments on probabilistic reasoning alone. A recurring risk is epistemic drift: as reasoning deepens, system behavior may move away from subject-matter-expert constraints for safe operation. This paper presents BRaVeS, a bounded reasoning and safety-governance framework termed the Defensible Next-Gen Reasoning System (DNRS). BRaVeS encodes SME-defined constraints as invariant anchors, proposes MoDA-Style (Mixture of Depths Attention) depth-aware access as a candidate mechanism for keeping these anchors visible during in…
- GitHub · Repository created · First archived
menma4ever/agentic-team-mcp ↗
Autonomous hierarchical multi-agent team (CEO -> Manager -> Workers) for Model Context Protocol (MCP). Mix Claude Code, Antigravity, Codex & Direct API with persistent SQLite queues and a real-time web UI.
- GitHub · Repository created · First archived
hazelpe/ComptyAI ↗
Turn token activity into compute. A compute-access protocol designed for Robinhood Chain: protocol fees fund GPU capacity for token holders.
- GitHub · Repository created · First archived
electric-capital/quest ↗
An open source, self-hosted, safety-focused AI workbench
- GitHub · Repository created · First archived
malevrigns/agent-jev ↗
AgentJev-0.6B - a fast 'System One' decision model for AI Agents: feed it any unstructured state (diffs, traces, logs) and structured questions, get calibrated probability distributions back in one ~50ms forward pass. Zero output-token decoding.
- GitHub · Repository created · First archived
emircan-sahin/gitviber ↗
Vibe code from one app: run agents in parallel worktrees, watch their diffs live, browse, test and commit. A 14 MB git client with a file explorer and terminal built in.
- GitHub · Repository created · First archived
chenrui333/jev-docs ↗
Community-maintained history of Jev / TypeSafe System One APIs, SDKs, agent guidance, and engineering best practices.
- GitHub · Repository created · First archived
F0Rextasy/omp-laya-judge ↗
Local Laya System-1 judge MCP server + skill for oh-my-pi: typed decisions in milliseconds, zero LLM tokens
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 ↗
Related threads
Explore related regions
These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.