Agents Are Going Async
Imagine a chief of staff who disappears every time you hand them a big project and only comes back once it's done. You'd probably fire them ...
Topic
#agentic
132 篇笔记
Enterprise Evals 101
Imagine your worst nightmare: your agent passes every demo, then a customer asks something you never tested, and it fails in public.In April...
Designing an Always-On Agent
Chatbots wait for a message. An always-on agent is single-threaded, proactive and situationally aware. Here's how we design them, and what models still lack.
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 ...
ThoughtWorks 技术雷达 Vol.35 摘要
ThoughtWorks 技术雷达第 35 期（2026 年 11 月）中文摘要：四大主题、117 个条目与团队行动建议。
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...
Concurrent agents on one file system
I think there's a lot of confusion out there about what a file system really is. There's lot of places where we can assign blame.People's fa...
Critical thinking when agents do the work
Back in the day, critical thinking was taught as approaching new info with humble curiosity and a healthy dose of skepticism - take in diffe...
The era of personal software
📝 摘要 作者以自己构建的健康数据追踪应用为例，讨论 LLM 时代「个人软件（personal software）」的兴起：当构建成本足够低，软件将逐渐商品化，越来越多人会为自身需求量身定制工具。他完整记录了实现链路——Apple Health 数据经 Health Auto Export 每小时导出 JSON，通过 端点写入 $5 的 PlanetScale Postgres；数据库 sche…
十分钟精读 DSH Super Agent：从 Paper 到 PRD
1. Super-agent作者认为，以 Coding Agent 为代表的单任务 Agent 已逐渐能够独立完成复杂工作，但现有系统仍以单一 Session 为基本单位。用户并行推进多个任务时，需要自行切换会话、管理上下文；文章称一个人通常只能同时跟进 3～5 个活跃 Sess...
Exploring Super-agent Design: Towards a More Autonomous Agent System
The original article is in Chinese. This is a machine translation.This article discusses architectural ideas. It is not an introduction to e...
New context engineering challenges in late 2026
It feels like everyone is converging on the same agent architecture: an LLM, running in a loop, calling tools, running in a sandbox. Claude ...
腾讯 2026 AI Agent 企业解决方案及落地实践手册
腾讯、腾讯云与 WorkBuddy 联合发布的 78 页《2026 AI Agent 企业解决方案及落地实践手册》精读：七类提效场景与 WorkBuddy / ClawPro / Agent Runtime / TokenHub 四件套，三阶段跃迁与三代办公，研发运维、SaaS、内容生产、AI 社交陪伴、游戏 NPC、智能客服与生态共建的方案和案例。
Building an AI-native engineering org
Last week Will Larson (@Lethain) asked how leaders are evaluating engineering managers for AI skills. My reply, a list of questions to think...
Building fine-grained version control for agents with Rust and Durable Objects
How DeltaDB streams every edit from humans and agents into one causal graph.
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…
多 Agent 协作终极解：实测 YC 开源新作 Agent Relay，让 Claude Code 和 Codex 直接对话
这周，美国创业孵化器 Y Combinator 2026 年秋季营（YC Fall 2026）的创业公司 Agent Workforce 发布了开源项目 Agent Relay。公司的两位联合创始人分别是 CEO Will Washburn 和 CTO Khaliq Gant，其...
How I work with Agents
... as of October 2026.Use the latest and greatest models. Everything else is potentially a waste of time. If a model is wrong 10% of the ti...
Agent Compute Engine deep dive | Google Cloud Blog
Traditional compute primitives are not built to run hundreds of millions of these agents at planet scale, which led us to build Agent Compute Engine.
Building agents: When to fold subagents into your main agent loop
When to consider using fewer subagents and how to migrate the into your main loop.
How Uber connects its AI agents to models and tools
In this blog we will see how Uber puts two gateways around its AI agents, and how every call carries the person who asked.
AI Agents Are Having Their Kubernetes Moment
Ten years ago, we saw infrastructure responsibilities moving out of microservices and into Kubernetes, service meshes, and proxies. Applicat...
A deep dive into OpenSEO
Explore OpenSEO's architecture: SEO data APIs, Cloudflare Workers, its audit crawler, MCP tools, AI agents, storage, and self-hosting trade-offs.
How to be more ambitious: A tutorial for humans with models
I work on Claude. It's an interesting experience: Every day I learn about yet another feat accomplished with or by Claude that I hadn't considered, didn&
Redesigning source control at Anthropic
As our merges per day grew more than tenfold, source control became our biggest development bottleneck. Here, we share how we migrated to an in-house version control system in five months.
为什么我们需要 Agent 评测
Agent 评测已经成为了当前 Agent应用的基石。如果说年初大家都在关注 Harness，那目前的热点和深水区，一定是 Agent评测和 Agent Infra。我所了解到的是，基本每个做 Agent 产品的组都很看重评测的方法论以及效果。因此我专门开了一个系列，给大家详细介...
「万字总结」- 我偷来了一份成为 Agent 工程师的学习线路
我之前面试了一家做 AI + web3 业内比较厉害的公司，但是没有通过吧，面试之后面试官给我了一份《Agent工程师入门指南》。我把它整理了一下，分享出来给大家提供参考，这是一份很详细很详细的、关于如何成为 Agent 工程师的文档，并且补充上我自己的学习心得当时给我的答复是 ...
来自 every 的自我批评，不应该让每个员工一个 Agent
Every 是一家做 AI 应用和内容的公司，最近把自己用了半年的企业 Agent 公开，同时批评自己之前的做法：受 OpenClaw 的影响，Every 为员工每人一个 agent，但在实践过程中，发现了在「维护」层面产生了诸多的问题，导致这种方法不可持续。它的联合创始人兼 C...
入职大厂两个月，我的 AI 开发心得
背景起因是和组里老板进行了几次 one-on-one。他对我目前使用 AI 工具、搭建个人 Harness，以及 AI Coding 的工作流很感兴趣。主要也是因为，我现在的需求做得又快又好，已经是一些项目的主 O 了。因此，我也借这个机会，整理了一下自己的日常 AI 工作流。目...
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...
The 5 levels of AI agents. From a single prompt to a production agent (Complete course)
There are five words people throw around about agents right now. Context engineering, loop engineering, Jev engineering, harness engineering...
The Evaporation of Software Engineering (and the Rise of the Agentic Builder)
If you’re like me, you likely thought software engineering was a safe and secure job …In fact, I never thought I’d have to worry about a job...
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...
An Accidental Blackboard
Notes from my Thoughtworks colleagues on AI-assisted software delivery
Building the missing layer between AI spend and ROI
Author: René SultanAI telemetry tells us which models our agents use and what they cost, but not what we are paying them to do. We built a s...
From rg to zg: Local Search Beyond Keywords
Summary: The information humans and agents need is often scattered across large numbers of local files, making it difficult to locate accura...
Your Inference Server is Secretly a Learner: Open-Sourcing Reef for Continual Self-Improving Agents
1. Before all the “RSI” hype becomes realBefore today's excitement around RSI is fully realized, we want to open-source Reef, an infrastruct...
Agentic Kernels in Production
TL;DR: We’ve built an agentic kernel development framework that identifies model-level optimization opportunities, generates improved kernel...
Running a Software Factory Efficiently at Uber Scale
Post author: @udaykiranIntroductionAI tools are now embedded in every phase of software development at Uber. More than 70% of pull requests ...
AI Agent 沙箱怎么选？我们把 runc、vArmor 和 Kata 跑了 30 轮
在 104 线程 Linux 物理机上实测 runc、runc + vArmor 与 Kata QEMU：Kata 用近一倍启动时间和数百 MiB 内存换独立内核，vArmor 则以接近 runc 的成本收紧行为边界。
AI agents meant to replace Meta workers made “large-scale, disruptive actions”
Report shows Meta's challenges replacing people with AI agents.
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...
Evaluating OpenWiki with WikiBench
OpenWiki is our open source agent for generating and maintaining codebase documentation. As we improve OpenWiki, we’ve needed to measure two...
Agent 的 Sandbox 到底是怎么实现的？
从 Codex、Claude Code、Gemini CLI 到 OpenHands很多人讨论 AI Agent 安全时，关注的是：“模型会不会执行危险命令？”但真正重要的问题其实是：即使 Agent 决定执行危险命令，底层系统是否允许它成功？这就是 Sandbox（沙箱）存在的...
How to Build a Company Brain That Gets Smarter Every Week
I am going to show you how to turn every correction, decision, and useful workflow your team gives AI into one company brain that makes ever...
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...
Moats in the age of floods
As the labs break revenue records and absorb more capabilities, there's a growing narrative that the great flood of intelligence they bring ...
SemiAnalysis 发布 AgentX InferenceXv3 研报，Mooncake 成为关键基础设施
SemiAnalysis 发布 AgentX InferenceXv3，用大规模真实 Agentic workload 重新审视推理系统性能。随着长上下文、多轮交互和 KV Cache 复用成为常态，Agentic Inference 正从“拼算力”走向系统级优化，而 Mooncake 也正在其中扮演越来越重要的基础设施角色。
How to Cut Agent Tokens by 2.7x (using an open harness)
Everything you need to understand where your agent's tokens actually go and what to do about it. It covers what a production harness owns be...
Agent 终章（Harness 成本篇）：一次百炼账单降低 88% 实战
关于优化 token，本文或许能够提供一些经验和参考
Computers Compared
Agents get computers now, and definitions vary. A Fly.io Sprite gives each agent its own hardware-isolated Linux machine that keeps its filesystem, stays reachable, and sleeps when there is nothing to do.
Recursive Self-Improvement
Agents can already edit their tools, skills, and harness. Recursive self-improvement still needs a system that can raise the verifier without capturing it.
Codex as a platform: build on the open agent harness
Build Codex into the products and workflows your users already know.
Domain-Driven Design matters more when AI writes your code
The domain model and Ubiquitous Language matter more than ever when an AI agent writes your code.
What is a Harness?
An agent harness is a piece of software that provides an environment for an AI model to operate within.
An open source rival to Claude Managed Agents just launched
TrueFoundry's open source TrueForge challenges Claude Managed Agents with vendor-neutral model choice, claiming 50% lower agent costs and no lock-in.
Fragments: August 18
fragments 18 Aug 2026
From context to dreams: architecting memory for AI agents
Have you ever felt that every conversation you have with an LLM across sessions feels like starting over from scratch? LLMs have a problem: ...
Cursor Origin review: An engineer’s perspective
A detailed review of Cursor Origin, covering Git hosting, GitHub sync, cloud agents, current limitations, and whether it’s worth switching.
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....
Optimizing for cost and intelligence
Balance cost and intelligence on the Claude Platform, with measured results for prompt caching, effort, model choice, budgets, and multi-model strategies.
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.
The AI Engineering Skills Map
I am delighted to present The AI Engineering Skills Map. AI allows us to build software very differently today than in 2022, and everyone wi...
Why model routing must be in the harness
Inference spend is rising as agents are deployed more widely, take on more complex tasks, and run longer autonomously. Enterprises are start...
"Issue tracking is dead"; How the pull request became the last chokepoint in the SDLC bottleneck
CodeRabbit's new Agentic Change Management layer reimagines code review as AI agents outpace human teams' ability to plan and prioritize work.
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.
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...
Your Agent Remembers Everything and Understands Nothing
Agent memory is where analytics was for years, returning what you asked for and nothing more. Then analytics started surfacing which number ...
DeepSeek 刚支持了 OpenAI Responses API，但你可能还不知道它是什么
2026 年 7 月 31 日，DeepSeek 悄悄发布了 V4-Flash-0731，附带一行更新日志：原生支持 OpenAI Responses API。消息不大，但背后藏着一条值得认真讲的故事线。一套 API 格式，是怎么从聊天框时代的产物，一步一步演化成今天 agent...
Five AI rivals just backed a shared plugin standard. Here's why it matters for developers.
OpenAI, AWS, Cursor, GitHub and Microsoft back Vercel's new Agent Plugins standard for packaging AI skills and MCP servers. Here's what it means for developers.
Why managed agents are the next big thing in agent building
Today we’re launching Managed Deep Agents - the easiest way to build, run and deploy production agents. We have a full release blog and docs...
Why managed agents are the next big thing in agent building
Today we’re launching Managed Deep Agents - the easiest way to build, run and deploy production agents. We have a full release blog and docs...
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...
Efficient Decode Context Parallelism with vLLM for Long Context Workloads
Decode Context Parallelism (DCP) in vLLM shards KV cache across GPUs by sequence dimension, enabling 3× higher throughput on long-context agentic workloads comp
Why Agents Started Dreaming (And What is Dreaming)?
A long-running agent gets really worse at remembering facts over time.As the context window fills up during the conversation, and especially...
Cloudflare OS: an open platform for agents, apps, and work
Cloudflare OS is an open-source platform that lets everyone in your company build apps, automate work, and safely access internal systems, shaped around what your organization knows and how it operates.
The Agent Development Lifecycle has arrived on Cloudflare
Agents can write code faster than teams can review, deploy, and maintain it. Today we’re introducing the Agent Development Lifecycle and the Cloudflare primitives that underpin it.
最佳实践：从Multi-Agent到Agent Team
2w字长文，Agent Team 的最佳实践。
Behind the scenes: How we build, test, and scale Google Agent Skills
AI agents are only as good as the instructions and context you give them. When we launched Google Agent Skills, our goal was simple: encode ...
How Stripe Built Kai on Deep Agents in 1 Week
Learn how Stripe built Kai, a company-wide AI agent on LangChain, LangGraph, and Deep Agents, reaching 5,000 users in roughly 4 weeks.
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...
Evaluating code review agents with ReviewBench
There are more code review agents now, and we’ve been building one internally. Code review is hard to evaluate. There aren’t many benchmarks...
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.
Agency: Secure, scalable sandboxes for agents
This is part of our series on how we're AI-pilling Sierra.In our last few posts, we talked about what happens when every employee has a sing...
Why Kubernetes is the wrong tool for agentic workloads
At some point, everyone building ai infra wonders whether they should use Kubernetes. There’s no straight answer for it because it depends o...
多模型路由进入 Agent 会话之后
模型路由在单轮问答中可以按难度分配成本，但进入 Agent 多轮会话后，还要处理上下文、工具状态、缓存和隐式状态。本文拆解会话级路由的智能与工程瓶颈，以及固定强模型、隔离子任务和有状态路由三条现实路线。
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 @...
Kimi K3 Is Here: Efficient Day-0 Support on vLLM
vLLM delivers day-0 Kimi K3 serving with hybrid KDA prefix caching, DSpark speculative decoding, production-scale disaggregation, and optimized kernels across N
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...
Towards Automating Eval Engineering
Today we’re releasing our Eval Engineering Skill, a skill that helps coding agents build evals using context from a repository and agent tra...
The State of Agent Wikis
In April 2026, Andrej Karpathy published a GitHub Gist describing a pattern he called the LLM Wiki.In the months since, four different teams...
State machines in 2 minutes
First it was loops. Now it's graphs. Next month it'll be something else.Here's the thing: we're constantly rediscovering decades-old softwar...
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
How to Build the Loops That Just Replaced Entire Prompt Engineering
For two years, getting more out of an AI agent meant writing a better prompt.That era is quietly ending. The best engineers in the world sto...
DSLs Enable Reliable Use of LLMs
Why Domain-Specific Languages and good abstractions make LLM code generation reliable and reviewable.
A Taxonomy of Self-evolving Agents
Self-evolving agents are becoming popular. [Hermes Agent](https://hermes-agent.nousresearch.com/docs/user-guide/features/skills) enables aut...
Your KV Caching Is Broken
A practitioner's guide to KV cache management. How a modern caching architecture cuts input token costs by 90% and speeds up LLM inference b...
Career advice in the age of AI
AI models get better at anything you can write a loss function for, and school is mostly loss functions: well-defined problems graded agains...
Trust Doesn't Live in Code Review
The gate you becameAgents write code faster than anyone can read it. This is not a forecast; it is the baseline now. A single agent, in an a...
Reshaping the economics of software: Building a future-ready core with Al/works™
Shift from AI experimentation to execution. Discover how Thoughtworks AI/works™ reshapes the economics of software delivery.
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 ...
30 Core Agentic Engineering Concepts Every Developer Should Know
There are 8 billion people on the planet.Only a fraction of developers understand how AI agents actually work.Not the demos. Not the hype.Th...
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...
Qwen Studio
Qwen Studio offers comprehensive functionality spanning chatbot, image and video understanding, image generation, document processing, web search integration, tool utilization, and artifacts.
The 7 Types of Agent Memory: A Technical Guide for AI Engineers
Agent memory explained: the 7 types — working, semantic, episodic, procedural, retrieval, parametric, prospective — and when to build each.
AI 101: What is Recursive Self-Improvement?
How AI systems are beginning to automate coding, experiments, evaluation, and research workflows ‒ and why Anthropic, Recursive, and Sakana ...
The Agent Loop Architecture
Everyone's asking "WTF is a loop?" Here's the question nobody's asking: what runs the loop?The AI discourse has converged on loops as a core...
You don't need ten agents. You need two tracks.
Spend enough time on the internet, and you'll see someone showing off a terminal with ten coding agents running in parallel. The implied pro...
Loop Driven Development, in practice
In Loop Driven Development I made an argument: when coding agents do the implementation, the engineering that matters moves to the feedback ...
MiniMax M3 & Kimi K2.7-Code: 两款中国开源前沿编程模型深度调研
MiniMax M3 & Kimi K2.7-Code: 两款中国开源前沿编程模型深度调研 2026 年 6 月第一周至第二周，MiniMax 和 Moonshot AI 先后发布了各自最新的编码/Agent 模型。两者均以开源（Open-Weight）形式发布，在编程和 Agent 能力上对标 GPT-5.5、Claude Opus 4.x 等闭源前沿模型，同时在价格上具有压倒性优势。 ----…
SkyPilot Sandboxes: Run Agent Code on Your Own Kubernetes, at Scale
SkyPilot runs untrusted, LLM-generated code in sandboxes on the Kubernetes clusters you already own. A single cluster sustains 50,000+ sandboxes, with multi-cluster support to go further. Individual launches in less than a second. All at up to one-tenth the cost of hosted alternatives, with your code and data never leaving your cloud.
Every Company's First AI Strategy Should Be a Skill Library
Watch your best people work long enough and you notice something. They have patterns.A great salesperson approaches an important call with a...
Economy of Minds: Multi-Agent Prompt Optimization explained
Wake up babe there's a new paper from Harvard: Economy of Minds (EOM). They've made a decentralized multi-agent system where agents coordin...
A harness for every task: dynamic workflows in Claude Code
Last week, we released dynamic workflows in Claude Code. Claude can now write its own harness on the fly, custom-built for the task at hand....
Session-Aware Agentic Routing: Continuity-Aware Model Selection for Long-Horizon LLM Agents
How Session-Aware Agentic Routing in vLLM Semantic Router preserves long-horizon agent continuity with session memory, safe model-switch boundaries, prefix-cach
Setting Up and Using the Pi Coding Agent
My experience of setting up the Pi coding agent with DeepSeek, installing packages, and using it for side projects and experiments.
From "Reasoning" Thinking to "Agentic" Thinking
The last two years reshaped how we evaluate models and what we expect from them. OpenAI's o1 showed that "thinking" could be a first-class capability, something you train for and expose to users. Deep…
Harness design for long-running application development
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Harness Engineering 深度解读：AI Agent 时代的工程范式革命
\> 基于六篇核心文献的综合分析：OpenAI (Ryan Lopopolo)、Anthropic (Justin Young)、Martin Fowler (Birgitta Böckeler)、LangChain、Latent Space、Cassie Kozyrkov 一、什么是 Harness Engineering？ Harness Engineering 是 2025-2026 年 A…
智能体工程的 8 个等级【译】
作者：Bassim Eledath 原文：The 8 Levels of Agentic Engineering — Bassim Eledath AI 的编程能力正在超越我们驾驭它的能力。这就是为什么所有那些拼命刷 SWE-bench 分数的努力，并没有与工程领导层真正关心的生产力指标同步。Anthropic 团队用 10 天就上线了 Cowork，而另一个团队用着同样的模型却连一个 POC（概…
The Anatomy of an Agent Harness
TLDR: Agent = Model + Harness. Harness engineering is how we build systems around models to turn them into work engines. The model contains the intelligence and the harness makes that intelligence use…
How to design Experiments to evaluate your Agentic Systems
Our forefathers and foremothers laid down the script for improving any system: (1) Build, (2) Evaluate, (3) Refine. Step 1 is trivial now thanks to coding agents. Step 3 is also simple too once you fi…
Harness engineering: leveraging Codex in an agent-first world
By Ryan Lopopolo, Member of the Technical Staff
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