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…
Topic
#cost-optimization
11 篇笔记
Kubernetes GPU Guide 2026: Scheduling, Sharing, Monitoring
Run GPUs on Kubernetes in 2026: install the NVIDIA GPU Operator, share GPUs with MIG or time-slicing, serve LLMs with vLLM, and monitor with DCGM.
How To Use Decision Models for Evals
Co-authored with Antaripa Saha.Decision models have exploded onto the scene recently, starting with TypeSafe’s Jev, followed by Perplexity’s...
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...
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...
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...
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 ...
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
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.
The Agent Harness Should Be Open
Today, we are open sourcing TrueForge, the agent harness we use at TrueFoundry to build and run general-purpose agents. Because once agents ...