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Check out 8 insights in total

Consulting

When I Ran the Checker, the Checker Was Wrong First

I created a checker to ensure footnote rules were followed and recorded the results. Upon reviewing the manuscript, it turned out the checker was incorrect. This is a record of what automated checks miss.

STAR-T2026-08-19·3 views
#Validation#Limits of Automation#Builder Log
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Consulting

How a Small Team Runs a Company with AI — It Was a Loop, Not a Tool

If adopting AI has added more tasks instead of reducing them, it's not a tool you lack, but a structure. We've anonymized and summarized observations from a team handling multiple tasks with few members.

STAR-T2026-08-17·1 views
#Small Teams#AI Workflows#Validation Cases
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Development & AI

How to Build "Our Team's Own Engine" with a Golden Set Learning Loop

Instead of reviewing AI outputs anew each time, this method involves compiling successful results into a learning loop. It also explains why this loop is highlighted in investment evaluations.

STAR-T2026-08-16·2 views
#Golden Set#AI Operations#Learning Loop
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Development & AI

Five Things to Set Up Before Choosing Tools for Small Team AI Automation

If you've used AI tools a few times but lack a team-wide system, there are five things to decide before selecting tools. We've organized them in the order of creating a loop that continuously learns what works well.

STAR-T2026-08-15·1 views
#AI Automation#Small Teams#Field Guide
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User Research

If You Can't Decide After Verification — The One Line That Separates GO/NO-GO

The reason decisions aren't made even after verification results are out is because the passing criteria are often set after the results are known. Here's a summary of one line to write before verification and four designs that make results unusable.

STAR-T2026-08-10·2 views
#Customer Validation#User Research#Field Guide
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Service Planning

5 Things to Remove Before Launch — MVP is About Subtraction, Not Addition

We included 12 features in our first product. It took six months. Users only used two of them. The time spent on the remaining 10 was completely wasted. The essence of MVP lies in 'minimal', yet we are always obsessed with 'product'.

STAR-T2026-07-27·1 views
#MVP#Service Planning#PMF
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AI Technology

5 Things We Fixed Before Prompts While Building an AI OS

When integrating AI into a business, prompts accumulate first, but verification, status, and records collapse first. Based on model fluctuations shown by Stanford and Berkeley and boundary experiments by Harvard and BCG, we summarize five things we fixed before prompts while building an AI OS. An AI business operation guide for solo entrepreneurs.

STAR-T2026-07-16·3 views
#AI Operations#AI Commercialization#Validation
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