Blog
Scale Without Chaos
Practical frameworks, real lessons, and operational playbooks from 14+ years of building and scaling distributed teams.
Redefining Leave When Your Team Works With AI
Days off and weekly hours measure input, not output. A three-state availability model for software teams: Working, Light and Off, with a protected floor.
A Salary Formula for Small Startups Where Every Developer Uses AI
A transparent salary formula for 5 to 10 person startups: market anchor, geography tiers, a score-set band position, capped raises, a merit pool and a simulation.
Scoring Developers When Everyone Uses AI
A per-person scorecard for small startups where every developer uses AI: cost, time, quality and simplicity as ratios, not token counts or lines of code.
We Audited an AI-Built Startup App. Here Is What We Found.
A technical audit of an AI-built app, walked through step by step: what the founder believed he had, what the first hour found, and the order we fixed it in.
Eight Management Mistakes We Watched Kill Startups in Their First Year
First-year startup failure is rarely the idea. After a decade-plus leading engineering teams, here are eight ordinary management decisions that quietly end companies.
The Three-Person Startup That Ran Like a 200-Person Company
Three people were running sprint planning, retros, and OKRs built for two hundred. Here is the one-page operating model that replaced it, and why it worked better.
The Hidden Monthly Bill of Vibe Coding: Tokens and Cloud Costs
A worked cost model for AI-built products: what platform credits, per-request AI calls, and default infrastructure actually cost as users grow.
Spend Your First $50k on Product, Not Infrastructure Mistakes
The two ways to waste a first budget are opposite: building for scale you don't have, or locking into a platform you can't leave. Here's the boring stack.
The Technical Due Diligence Questions Investors Will Ask
Seed investors increasingly bring in a technical advisor before wiring money. Here is what they check, the answers that end the conversation, and how to prepare.
When Your Technical Co-Founder Cannot Scale With the Company
The engineer who built version one is not always the person who can lead version three. Here is how to handle that shift with respect, not a firing.
What "Senior Oversight" Means When AI Writes the Code
Reviewing AI-generated code is not reading it line by line. Here are the twelve questions a senior engineer asks that the model never does, and what it costs.
The AI-Assisted Engineering Workflow That Works for a Three-Person Team
Speed with AI coding tools comes from the loop, not the model. Here is the five-step workflow small teams use to ship fast without breaking things.
Rewrite or Keep? A Decision Framework for Vibe-Coded Products
Most vibe-coded products should not be rewritten, and most should not be kept as-is. A seven-question scorecard tells you which path actually fits.
Leading Engineers When You Cannot Read Their Code
You do not need to read code to lead engineers well. Here are the signals to watch, how to define done, and the weekly cadence that makes it work.
The Non-Technical Founder's Guide to Not Being Fooled by an AI Demo
AI made demos look finished even when they are not. Here are eight questions that tell you whether your builder shipped a product or a convincing shell.
Your AI-Built App Has a Security Hole. Find It This Weekend.
A non-technical founder can find the most dangerous security holes in an AI-built app in one weekend, with a browser and this checklist, no code required.
You Just Raised. Do Not Hire Five Engineers.
Most seed-stage hiring plans call for five engineers by month six. Here is the 12-month sequence we use instead, and why it protects your runway.
Why Your First Engineering Hire Quit After Four Months
First engineering hires rarely quit over pay. We've watched the real reason play out at several startups, and it is fixable before the offer goes out.
Technical Co-Founder or Fractional CTO? What a Seed Startup Actually Needs
A technical co-founder is a decade-long commitment. A fractional CTO is a reversible one. Here is how to tell which your seed-stage startup needs right now.
The 7 Ways AI-Built MVPs Fail in Production (And What Each Costs to Fix)
AI-built MVPs tend to break in the same seven places. Here is how to spot each one in minutes and roughly what it takes, in hours, to fix it properly.
MVP Cost in 2026: Agency, Freelancer, AI, or AI With Oversight
Four ways to build an MVP in 2026, agency, freelancer, pure AI, and AI with senior oversight, compared on build cost, fix cost, run cost, and time to market.
The Founder Who Reviewed Every Pull Request (Until Shipping Stopped)
We were the only approval gate for every pull request at a startup we advised. Here is what that cost the team, and the system that replaced us.
Vibe Coding Is Great for Demos. It Is How Startups Lose Their First Round.
A weekend build can win a term sheet, but it is not the same as software ready for real users. Here is what breaks between demo day and week three.
Automating Manual Work: Where to Start
Every startup has processes that run on spreadsheets, emails, and human memory. Here's a practical framework for identifying what to automate first, and what to build vs. buy.
Why Your Smart People Aren't Productive (And How to Fix It)
You hired great people. The work is still slow. The problem isn't the people. It's the system they're working inside. Here's how to diagnose it and fix it fast.
Scaling from 10 to 30 People Without Losing Your Mind
The jump from 10 to 30 people is where most startups break. Here's what actually happens, and the playbook we use to help founders navigate it without losing their best people.
Work-Life Balance for Software Engineers: Five Strategies That Actually Work
Software engineering is one of the easiest careers to let consume everything. Here are five concrete strategies for maintaining balance without sacrificing quality.
When to Leave a Sinking Ship: A Scientific and Social Perspective
How do you know when it's time to leave a declining company? Drawing on our team's experience, here's a practical guide to recognizing the signs and moving wisely.
AI vs Coders: The Speed Battle
AI can produce code very quickly, but the evidence that it makes developers faster is mixed. Are coders obsolete? Not quite, but it does change how we work.
Long Live JavaScript: An Ecosystem to Rule
JavaScript has been declared dead more times than any language in history. It keeps thriving. Here's why the ecosystem is stronger than ever, and worth betting on.
The Absurdity of Unrealistic Tech Job Descriptions
Internships that demand full-stack expertise. Junior roles that require 5 years of experience. Single engineers expected to master 15 unrelated technologies. Something has gone wrong with how tech companies hire.
Remote Work: One Size Fits None
Remote work works brilliantly for some people and poorly for others. The best managers recognize the difference and build flexibility into their approach.
Hire Professionals, Not Amateurs: The Real Cost of Cutting Corners
Hiring amateurs to save money is one of the most expensive decisions a business can make. Here's why the math almost never works out.
Stop Asking for Cover Letters
Cover letters consume time on both sides of the hiring process and reveal almost nothing useful. There's a better way.
The Probation Period Is Your Best Hiring Tool
Technical interviews and take-home assignments are imperfect proxies for real performance. The probation period gives you something far more reliable: actual work in actual conditions.
Why Projects Fail: The 10 Root Causes
Most failed projects weren't killed by bad luck or lack of funding. They were killed by predictable, avoidable mistakes. Here are the ten most common ones.
The Impact of Emotional Intelligence on Your Career
IQ gets you in the room. Emotional intelligence determines how far you go once you're there. In our experience, it matters far more than most career advice admits.
The Secrets Behind Project Success: Leading People
Resource management gets all the attention. People leadership is what actually determines whether projects succeed or fail.