best-practices
Reducing Fab Cycle Time: What MES, Dispatching, Scheduling and APC Each Contribute - Semiconductor Digest
Dispatching, finite-capacity scheduling, MES, APC and simulation each attack a different share of the time wafers spend waiting, and all of them depend on accurate WIP and equipment-state data.
How a team learns to trust a quote it did not build - The Loadstar
Four in five air freight quotes on cargo.one now go out without human review. Here are the six patterns that build forwarder trust in AI quoting.
We have run enough of these deployments to see the same six patterns emerge.
System Design In Depth
Deep system design curriculum — 18 modules, 200 units, 118 architecture diagrams, from-scratch algorithm builds, and curated video walkthroughs for senior engineers.
The most important product decision is what you don’t build
Ask a team what they shipped this year and you’ll get a list. Ask what they killed and the room goes quiet.
https://stratechery.com/2026/write-things-down/
How we configured OpenTelemetry logs in Rails | SixPatterns
We integrated the OpenTelemetry Ruby logs SDK in a Rails app to export logs directly to a vendor, without running a Collector.
Best of New York Times
Click through for our favourite writing from the New York Times
Build Wide, Ship Narrow | Blog
Splitting a finished branch into small PRs used to be the expensive part, so we decided the boundaries before the code existed. That cost collapsed. Now the code can tell you where to cut it.
Skunk Works and the 14 Rules Behind Fast Engineering — Flow Engineering
NASA invented systems engineering. Skunk Works perfected it.
3 NumPy Tricks for Numerical Performance - KDnuggets
In this article, we will cover three essential NumPy tricks to optimize your code: vectorization and broadcasting, in-place operations, and leveraging memory views instead of copies.
To optimize, you must write code using native universal functions (ufuncs) and broadcasting.
When working with very large arrays (e.g. millions of entries), allocating and garbage-collecting these temporary intermediate arrays creates substantial overhead.
Using AI to write better code more slowly
A lot of people seem convinced that the point of AI coding is to write low-quality code as fast as possible. Spew out barely-passable slop, open massive PRs, and merge them unvetted. Ship it! But t…
multica-ai/andrej-karpathy-skills: A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on…
A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls. - multica-ai/andrej-karpathy-skills
LLMs in Production - Christopher Brousseau and Matthew Sharp
Learn how to put Large Language Model-based applications into production safely and efficiently.
5 Must-Know Python Concepts - KDnuggets
In this article, we will explore five fundamental concepts that every Python developer should have in their toolkit.
The 13 software engineering laws
Hyrum's law, Conway’s law, Zawinski's law, and 10 others.
3 constraints before I build anything | Jordan Lord
['Programmer', 'Computer nerd', 'Unix enthusiast'];
Laws of Software Engineering
A collection of principles and patterns that shape software systems, teams, and decisions.
The Git Commands I Run Before Reading Any Code
Five git commands that tell you where a codebase hurts before you open a single file. Churn hotspots, bus factor, bug clusters, and crisis patterns.
The 20 most-changed files in the last year.
Every contributor ranked by commit count.
A college basketball coach made 418 mistakes his first year. He kept track of all of them
Thirteen years ago, Mike Neighbors dreamed up an idea to help others: He started writing down his mistakes.
Scaling a Monolith to 1M LOC: 113 Pragmatic Lessons from Tech Lead to CTO
For context, I work in a Django/React TS/React Native codebase on a 20-person team at MorphMarkethttps://www.morphmarket.com/. I have 17 years experience wit...
Safely Deploying ML Models to Production: Four Controlled Strategies (A/B, Canary, Interleaved, Shadow Testing) - MarkTechPost
Safely Deploying Machine Learning Models to Production: Four Controlled Strategies (A/B, Canary, Interleaved, Shadow Testing)
Note: This bookmark, **[Safely Deploying ML Models to Production: Four Controlled Strategies](#rid:1652757915)**, is an article from MarkTechPost that outlines how to release machine learning models into production while minimizing risk. The article details four key deployment strategies: * **A/B Testing**: Randomly splits a small percentage of total traffic to the new model while the rest stays on the…
Google Has a Secret Reference Desk. Here's How to Use It.
40 Google features to find exactly what you need, the alternative search engines that do things Google won't, and the reference desk framework underneath all of it.
Claude Code told me what tools it needs to work faster. Oh boy I was missing so many things.
My Claude was craving for better tooling.
How I Audit a Legacy Rails Codebase in the First Week
After 50+ engagements, I've learned the first week isn't about reading the code. It's about reading the signals.
Harness Engineering: How to Supervise Code You Can’t Read
AI writes the code now. The skill that matters is controlling what it builds.
Every time you accept that output without checking, you’re running up a tab. Call it trust debt: the accumulated cost of all the assumptions you never audited. Trust debt doesn’t announce itself. It compounds quietly until Future You has to pay it all back at once, usually at the worst possible…
Claude Code Power Tips
Use Claude Code to speed up data science. Master data cleaning, visualization, and model prototyping with Python, pandas, and scikit-learn. Get actionable power tips.
𝗖𝗹𝗮𝘂𝗱𝗲 𝗦𝗸𝗶𝗹𝗹𝘀 𝗶𝘀 𝗽𝗿𝗼𝗯𝗮𝗯𝗹𝘆 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝘂𝗻𝗱𝗲𝗿𝗿𝗮𝘁𝗲𝗱 𝗳𝗲𝗮𝘁𝘂𝗿𝗲 𝗖𝗹𝗮𝘂𝗱𝗲 𝗵𝗮𝘀 𝗯𝘂𝗶𝗹𝘁. If you’re still writing the same prompts in Claude every day… |…
𝗖𝗹𝗮𝘂𝗱𝗲 𝗦𝗸𝗶𝗹𝗹𝘀 𝗶𝘀 𝗽𝗿𝗼𝗯𝗮𝗯𝗹𝘆 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝘂𝗻𝗱𝗲𝗿𝗿𝗮𝘁𝗲𝗱 𝗳𝗲𝗮𝘁𝘂𝗿𝗲 𝗖𝗹𝗮𝘂𝗱𝗲 𝗵𝗮𝘀 𝗯𝘂𝗶𝗹𝘁. If you’re still writing the same prompts in Claude every day, you’re doing extra work. Skills fix that. They package your best instructions once, then you reuse them on demand. Result: less repetition, more…
21 Lessons From 14 Years at Google
Lessons learned from 14 years of engineering at Google, focusing on what truly matters beyond just writing great code.
Has Von Maur Figured Out How Department Stores Should Work?
Von Maur has made a different play than several other retailers. Is it working?
36 Ways to Revive an Ecommerce Business
Here's how to overcome entrepreneurial doldrums, when a business is seemingly stuck in no growth or worse.
Why your Amazon Ads aren't delivering: 6 critical issues to fix
Many Amazon ad delivery issues have little to do with bids. Find out what really stops ads from running – and how to prevent it.
the problem is rarely ad copy or targeting
tightly tied to your listings, inventory, and account health.
Onboarding Success: Learn the Cold Start Algorithm
Master the art of onboarding with proactive strategies. Discover how to quickly adapt and make an impact in your new tech role.
The Complete LLM Tech Stack
In this article, I'll take you through the complete LLM tech stack you should know to develop & deploy real-world LLM applications.
I’m Switching to Python and Actually Liking It
I’ve started writing more Python code lately (because of… AI, you know). In this post, I share the tools, libraries, configs, and other integrations I use for building production-grade Python applications following a frontend-backend architecture.
The Founder’s Guide to Building a V1 of Customer Success
A CS leader who has built the function from the ground up shares where founders should start — from how to hire to the most important metrics to track.
Merchandising Lessons from Top Marketplaces
We analyze the home pages of 10 marketplaces to spot common merchandising traits.
Python Patterns for Intermediate Data Scientists
Learn to leverage Python patterns like a professional.
How to Build and Scale Onboarding
Superhuman became known for its unique approach to onboarding: a highly-personalized, white-glove, human-led experience. Superhuman's Gaurav Vohra, startup advisor and growth leader, gives us a detailed look at how he built and scaled the program.
How to do a code review
Google’s Engineering Practices documentation
humanlayer/12-factor-agents
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - humanlayer/12-factor-agents
12-factor-agents: Principles to build LLM-powered software good enough to put in the hands of production customers
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How I Spent 17,784 Hours in 5 Years as a Startup Founder
Levels founder & CEO Sam Corcos shares his detailed time-tracking data across 5 years of startup growth
Mise en Place: The Chef’s Secret to a More Productive and Organized Life
People have different styles when they cook. Some people are neat and tidy. After taking out and using an ingredient they don’t need anymore, they return it to the fridge or cabinet. After chopping up vegetables, they clean up the scraps left behind. When a dish has been…
A short introduction to Interval Tree Clocks
A short introduction to Interval Tree Clocks, a causality tracking mechanism, based on a lightening talk I gave at dotScale 2017.
Goodhart's Law Isn't as Useful as You Might Think
Goodhart's Law is useless. It tells you about a phenomenon, but it doesn't tell you how to solve it. We look at how organisations actually prevent Goodhart's Law, and illustrate this with Amazon's Weekly Business Review as an example.
The Amazon Weekly Business Review
The authoritative guide on how Amazon does WBRs (from former exec Colin Bryar): how it works, how to do it, and how Amazon uses it to win.
Becoming Data Driven, From First Principles
People often say things like "become data driven" without explaining what that means or how to do it. This is everything you need to know to actually become data driven, from scratch, using the same first principles that Amazon, Koch, and Toyota used back in their day.
Run Charts - Improvement | theCompleteMedic
Create your first run chart and start interpreting your data using just four rules. Your go-to QI resource.