Original Summary

I have been thinking that the current Agentic Loop design of LLM Call -> Tool Call -> ... has been outdated. The arrival of Jev and other System One models provided us a primitive we desperately needed. We need an agent that can natively think fast and slow . Not have workflows or multi-agent architectures that mimics it. The agent should be able to do its hard reasoning using the power of modern LLMs, capture an execution graph filled with steps and fast intuitive decisions executed with the new system one models, and prevent it from making LLM calls for just to "follow through the plan". This way, it can "do metaprogramming over its own execution" Jive is an open-source terminal coding agent that replaces tool calls with graph calls where each graph is a DAG of tool and jev calls. What Jive does well: repo investigation, bulk classification, multi-step profiling, repetitive edits. What it does not do: replace Codex or Claude Code for everything. But I think it will. Some numbers from the tasks I benchmarked (same task, all models at medium effort; time / output tokens): conversation_eval: Jive 3m 26s / 11.1k · Codex 29m 33s / 20.5k · Claude Code 16m 48s / 47.9k error_handling_audit: Jive 3m 10s / 10.7k · Codex 19m 29s / 25.8k · Claude Code 5m 08s / 42.5k product_matching: Jive 3m 03s / 8.9k · Codex 22m 00s / 19.7k · Claude Code 32m 02s / 19.3k search_latency: Jive 2m 00s / 9.6k · Codex 9m 00s / 12.8k · Claude Code 7m 18s / 51.4k sembench_movie: Jive 1m 47s / 6.1k · Codex 19m 58s / 10.3k · Claude Code 8m 51s / 15.7k slow_trace_search: Jive 1m 41s / 5.7k · Codex 6m 00s / 8.1k · Claude Code 3m 04s / 19.3k See README for more information: https://github.com/merijjeyn/jive . Also for available tasks, and how to run one yourself. Happy to take any comments and answer questions.   submitted by   /u/merijjeyn [link]   [comments]

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  • 发布时间：2026/9/22 04:53:13