Software Factory Engineer: Job Description
An emerging engineering role for the transition from AI-assisted development to L4 Autonomous Software Factories.The RoleWe are looking for ...
Topic
#human-in-the-loop
37 篇笔记
Agent State Machines: Building Deterministic Scaffolding for Agents
If you're not using some type of agent state machine, you're completely at the mercy of the nondeterministic nature of models. Are you reall...
コードを読まずにマージするために必要なこと
📝 摘要 本文讨论「no look merge」——开发者完全不读代码就合并 AI 产出的 PR——究竟需要哪些前提。作者认为，仅把质量确认自动化（测试验证行为 + AI 做设计与安全评审、修正后重新验证、存在未执行验证或未解决指摘就不合并）并不足以移除人工审批，真正的障碍在于组织共识：如果漏检后开发负责人仍追究个人责任，那实际上等同于要求人继续读代码。文章引用 2021 年的 Ship / S…
手脑分离与边界治理：企业级 Agent 平台的总体架构设计
在本地终端环境中，开发者早已习惯使用 Claude Code、Cursor 或各类命令行 Agent 进行自主编码与系统运维。模型推理循环与操作系统的 Shell、文件系统和环境变量运行在同一台宿主机上，通过本地进程树与内存字典直接驱动。这种“脑与手同机”的拓扑，在个人开发机上极...
How the Claude Code team does code review
How do you review code at the volume agents produce it? On the Claude Code team, once we had high coverage and deep reviews, we started optimizing for the minimum amount of human review time that doesn't raise reverts or incidents.
How to Cut Your Agent Bill by 90% With Jev Engineering and Kimi K3
How to find the decisions hiding inside your agents, write questions a system one model answers well, route on calibrated confidence and han...
Your Agent Harness Should Repair Itself
Everything you need to understand how an agent harness can learn from production failures and repair itself. It covers procedural memory, tr...
Do you need a software factory?
A software factory is a repeatable loop around software work. If you're building a software factory, code good enough to ship still needs hu...
How we Build Agent Environments & Tasks
TLDR: This is a practical guide on how we create synthetic agent environments and tasks. By the end, we have a two-step pipeline. The first...
Codex as a platform: build on the open agent harness
Build Codex into the products and workflows your users already know.
Designing Agent Context by Scope and Time
When an agent performs poorly, we often blame the model.Then we enlarge the system prompt. When that becomes unwieldy, we add another agent....
How to Design an Agent Harness: six decisions that turn a model into a worker you can leave alone
Your agent says the job is done and the tests never ran. It's sharp for twenty minutes, then forgets a rule you gave it at the start. You re...
Patterns and problems in multiagent systems
We ran experiments on swarms of Claude agents and found coordination failures, collusion, and sabotage. Here, we share what they mean for AI safety.
Practical Loop Engineering
Goals, loops, and the discipline of not delegating your judgment
TDD inside the agent loop - theater or actual value?
Notes from my Thoughtworks colleagues on AI-assisted software delivery
7 rules for self-improving agent loops every AI engineer should know
By @Saboo_Shubham_ and @secchi_eliaWhen coding agents write the code, defining what's good is the real engineering job.Coding agents can now...
The human is the loop
After a few weeks away from AI, I see my usage wasn't always productive or healthy.
How to Build a Shared AI Harness for Your Team
I am going to show you how to turn the models, agents, skills, and automations living across your team's tools and workflows into one coordi...
The company brain has a permissions problem
Every company is connecting Slack, email, docs and meetings into one brain that gives everyone access to everything the company knows.Nobody...
所有想做 FDE 的人，都该读懂 Palantir 这套方法
大模型进入企业以后，最难的一步是把一家公司的数据、规则和权力关系，变成 AI 能够理解并安全执行的系统。2026 年 5 月，OpenAI 成立了一家专门负责企业部署的新公司。它准备投入超过 40 亿美元，并计划通过收购 Tomoro，一次带入约 150 名 Forward De...
Deep Agents vs LangChain vs LangGraph
Deep Agents, LangChain, and LangGraph each offer distinct approaches to building agents. In this post, we cover the key distinctions between...
最佳实践：从Multi-Agent到Agent Team
2w字长文，Agent Team 的最佳实践。
YC 开源 QM：当每个员工都有 Agent，公司需要怎样的协作系统？
未来一家公司里，可能每个员工都有自己的 Agent。它们能读文件、查数据库、写代码、回复邮件，也能在后台持续运行任务。问题随之而来：这些 Agent 应该看到什么？记住什么？使用谁的账号？哪些能力可以共享？危险动作由谁批准？7 月 31 日，Y Combinator 开源的 QM...
Eval Engineering: build the gate that lets your agents merge without you (full 6-step course)
The end state is easy to describe. An agent finishes a change, opens it, and it goes in without a human reading it.Not because anyone decide...
A practical guide to building agents
A comprehensive guide to designing, orchestrating, and deploying AI agents—covering use cases, model selection, tool design, guardrails, and multi-agent patterns.
Codex 进阶指南：作为 Multi-Agent 编排控制平面
大多数人用 Codex 的方式，是开一个会话、交代一件事、等它做完。这种用法只动用了它很小一部分能力。Codex 真正提供的是一组完整的调度原语：发现有哪些项目和会话、创建新会话、从已有会话分叉、给别的会话派活、等它们回来、观察它们的进展、纠正跑偏的那个、把任务搬到另一台机器、最...
The harness is all you need (mostly)
A practical GitHub Copilot workflow for prototyping, planning, implementing, and reviewing software - without chasing every new AI tool.By @...
The Orchestrator's Tax
Use subagents to protect the orchestrator's working memory, not just to save time or run tasks in parallel.
Why Software Factories Fail: Turning the lights back on
This is part two of Why Software Factories FailThe talk version of this post is live on youtube: https://www.youtube.com/watch?v=Ib5GBkD555M...
数据研发Multi-Agent架构的Harness工程实践
📝 摘要 本文基于阿里云数据研发团队的 Multi-Agent 实践，系统阐述了 Harness Engineering（智能体脚手架工程）的核心理念与落地方法。文章指出 AI 工程经历了 Prompt Engineering → Context Engineering → Harness Engineering 三代演进，并提出核心公式 Agent = Model + Harness：模型决定…
Agent 评测：方法论与体系设计
关于评测工程的体系化总结，本文或许能给出一些参考
Getting started with loops
There’s a lot of talk right now about "designing loops" instead of prompting your coding agent. If you spend some time on X trying to pin do...
Towards org-level agent harnesses
Claude Tag has grown rapidly in Anthropic. I want to share some of the reasons for this and the behavioral shifts I’ve seen with this agent ...
15 AI Agent Design Patterns Every Engineer Must Know
Every team building AI agents hits the same wall.You start with one prompt and a few tools.It works. Then requirements grow. More edge cases...
Loop engineering: the 14-step roadmap from prompter to loop designer.
Most developers still prompt their coding agents by hand. They type, they wait, they read the diff, they type again. 9out of 10 builders hav...
How Warp builds self-improving agents on Claude
How Warp devised a simple development pattern that anyone can use to create self-improving agents.
The AI-Native SDLC playbook | Claude by Anthropic
How to transform your software development lifecycle with AI—stage by stage.