Startups

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Productizing a Service: From Hours to Licenses

Startups

Updated: July 25, 2026

At some point in most consulting careers, you notice you're doing the same thing over and over for different clients. Some people ignore it. Some people build a product. Here's what that transition actually looks like - the pricing, the awkward middle where you're doing both badly, and the parts that will never productize no matter how hard you try. read on »

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The MVP That Is Not a Product

Startups

Updated: July 11, 2026

You can ship code for weeks and still learn nothing. A real MVP is the smallest thing that creates evidence-about buyers, demand, and what actually works. Here’s how to use AI for scripts, landing pages, concierge ops, and fake doors without turning your "MVP" into a polished demo for a problem you made up. read on »

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Vanity Metrics Look Better When AI Generates Them

Startups

Updated: July 11, 2026

AI can crank out landing pages, emails, and charts all day. It can even crank out signups. The trap is thinking volume means progress. I once worked at a "AI-powered" SaaS where the model was basically spreadsheet column mapping, but the dashboard still looked great. This post is about keeping yourself honest: cohort metrics, boring innovation accounting, and using AI for synthesis-not for the math that decides what’s real. read on »

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Pragmatists Do Not Care That You Built It With Claude

Startups

Updated: July 11, 2026

Model choice doesn’t close deals. Pragmatist buyers want the app to install cleanly, docs that match reality, integrations that survive API changes, and support that answers before their CFO starts yelling. This post breaks down the "whole product" layer most AI startups skip-and how LLMs can help you ship the boring parts without lying to customers. read on »

An orange and yellow cartoon robot with striped accordion arms, wheels for feet, and a control panel on its chest stands centered against a mint green background, surrounded by floating cookies and geometric shapes. Text in the bottom right reads "Small Batches, Large Temptations" in black font.

Small Batches, Large Temptations

Startups

Updated: July 11, 2026

AI makes it weirdly easy to ship a "feature" that’s really ten changes glued together. The diff is huge, the vibes are good, and then you deploy and realize you built a large batch with extra steps. This post is a reminder that small batches are a discipline: one hypothesis, one change, one metric, and a rollback plan. Use AI to shrink the loop from assumption to evidence, not to crank out a feature cannon you can’t validate. read on »

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Ten Pivots, Re-Read for the AI Era

Startups

Updated: July 11, 2026

AI makes pivots feel easy because it can repaint your strategy in an afternoon. New landing page, new deck, new positioning doc, and you’re still wrong-just in three new fonts. This post walks through Eric Ries’ ten pivots with the AI-era failure modes, plus the one ritual that still matters: real evidence, real dissent, and a decision record you can’t wiggle out of later. read on »

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Writing for the Crawlers That Are Crawling for AI

Startups

Updated: July 11, 2026

Perplexity is sending me buyers, but the "SERP" they see is a paragraph with two citations. If your positioning can’t survive being compressed, the assistant will guess what you do - and it’ll guess the boring, generic version. This post is a playbook for writing answer-shaped pages that humans can decide from and assistants can quote without turning you into SaaS mush. read on »

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The Startup Founder Operating System

Startups

Updated: July 11, 2026

Founders aren’t getting replaced by AI. They’re getting buried under it. One day you’re "moving fast," and the next your real product is wedged between Notion, Slack, a shaky CRM, and a Google Sheet nobody will admit they own. This post is about the fix: a boring operating cadence-weekly learning reviews, monthly pivot checks, and real customer calls-so AI supports your startup instead of turning your toolchain into the startup. read on »

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How to Pick the Wrong Customer Slowly

Startups

Updated: July 11, 2026

Founders rarely pick the wrong customer in one clean mistake. They do it slowly, while the ICP deck gets prettier and the pipeline stays empty. This post is about customer selection as the load-bearing decision, the "death flailing" signs that show up when you dodge it, and how to use AI for narrow tasks (scenarios, assumptions, clustering) without letting it turn your research into vibes. Also: keep the raw notes, use boring tools, and ask questions that force real answers. read on »

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Why AI Does Not Save You From Having to Cross the Chasm

Startups

Updated: July 11, 2026

AI helps you ship faster, but it doesn’t make you mainstream-ready. Early adopters will forgive chaos. Pragmatists want integrations, uptime, support, and a plan that won’t blow up their week. Use AI to map segments, tighten messaging, synthesize interviews, and prep objection answers-but don’t confuse a slick demo with reduced risk. The chasm is still there. You just hit it at higher speed. read on »

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Reading Your Own Data Honestly

Startups

Updated: July 11, 2026

Learn how to analyze your personal logs and data with honesty and objectivity to gain meaningful insights, identify patterns, and make better decisions based on your actual behavior rather than perceived habits. read on »

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The Augmented Founder

Startups

Updated: July 11, 2026

AI can crank out landing pages, dashboards, and "market research" before lunch. None of that answers the only question that matters: will someone pay for this. Use models for drafts, compression, and internal glue work, but don’t let autocomplete-with-confidence replace judgment, taste, and five uncomfortable conversations with real buyers. read on »

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Vibe Coding Hangover: What Happens After the MVP Ships

Startups

Updated: March 03, 2026

You shipped a vibe-coded MVP in a weekend. Then a user pasted a cursed CSV and your app fell over. This post is a quick hangover cure: the common failure modes (no tests, leaky errors, hardcoded secrets, zero validation, AI-shaped architecture) and a simple triage plan-secure the money paths, add visibility, test the core flows, document the basics, then decide whether to patch or rewrite. read on »

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Decoding Tech Entrepreneurship: Startup Myths vs. Realities

Startups

Updated: March 03, 2026

Startups aren't "small businesses, but faster." They run on different incentives: growth, fundraising, and exits-not stability. That's why low cash + "equity will hit" can quietly turn into unpaid risk, and why funding can mean "good story," not "good business." This post lays out the warning signs-death flailing, transparency theater, and pitch-first building-and the blunt questions to ask before you bet your time, money, and sanity. read on »

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When Your AI Startup Isn't Actually an AI Startup

Startups

Updated: March 03, 2026

"AI startup" is a spectrum: real ML teams with real evals on one end, and "proprietary AI" that's mostly spreadsheets and humans on the other. This post lays out three buckets (genuine ML, honest API wrappers, and outright fraud), plus the technical and social tells that separate them. If you're interviewing or investing, you'll leave with specific questions that force reality to show up. read on »

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The 6-Month Rule: The Difference Between Startups and 'Expensive Hobbies'

Startups

Updated: March 03, 2026

If nobody pays after 6 months, you probably don't have a startup-you have an expensive hobby. This post lays out a blunt checkpoint: ship a "just enough" MVP, ask strangers to pay, and treat revenue (not vibes, press, or polite VC nods) as the only real signal. If the answer is still no, do a real pivot based on customer pull-or shut it down before you waste more time, money, and pride. -Sethers read on »

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The Technical Co-Founder Matching Problem

Startups

Updated: January 25, 2026

Finding a technical co-founder isn't a scavenger hunt for "an engineer." It's a high-stakes match of risk tolerance, work style, and shared reality. In this post, I break down why most founder pairings implode (hint: "just build the app" is not a plan), how the MVP fight usually starts, and the four questions I make co-founders answer before anyone starts arguing about equity at 11pm. -Sethers read on »

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It's Not about Crushing Success, It's about Recovering from Catastrophic Failure

Startups

Updated: January 26, 2026

Most teams can handle a normal rush. The real test is when everything is already on fire and then the lunch crowd shows up anyway. In restaurants, the pros don't panic or rewrite the process mid-service-they fix the next thing and keep the line moving. Startups are the same: "crushing it" is mostly a myth, but recovery is a skill you can build. This post is about designing teams and systems that can take a hit, get up fast, and keep shipping. read on »

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Startup Red Flags: A Checklist for Job Seekers and Early Employees

Startups

Updated: January 26, 2026

Startups don't usually fail because founders are dumb. They fail because everyone is moving fast, running on hope, and nobody wants to ask the "are we about to explode?" question. This post is a practical checklist of red flags to watch for in interviews-financials, leadership, culture, product, and compensation-plus the exact questions to ask so you can figure out what kind of mess you're walking into (and whether it's the kind you can live with). read on »

A UFO looking at a star saying, "laaaame!". The image has the caption, "Turns out our 'north star' was actually a ball of burning hydrogen!"

Best Practices, Antipatterns, and Why Nothing Seems to Work

Startups

Updated: June 29, 2026

My career has given me the privilege of witnessing some pretty spectacular failures and successes. I know for myself, experience is the best teacher (we’ll blame my ancestors and my upbringing read on »

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