ai
AI features and customer data: what to decide first
The decisions to make before customer data reaches a language model: what goes in, which account tier, how long it is kept, and what customers are told.
Insights / AI-native building
AI-native building desk
Build and operate a product that depends on a model, with the risks stated.
AI-native building means putting a language model inside a product and running it with the risks stated.
One article reads the OWASP list of risks for model applications. Another applies the NIST AI Risk Management Framework to a small team. Another sets out the questions to ask a model provider. Another shows how to evaluate a feature before launch. Another explains retrieval and where it breaks. Another covers metering and budgeting usage. Another covers decisions about customer data. Another places a person in the loop. The last lists questions to bring to counsel about AI regulation.
Each article cites the document it describes and says what it cannot tell you.
- Dream 7 articles
- Build 11 articles
- Grow 6 articles
- Fundable 8 articles
- Starting out 14 articles
- Funding and capital 13 articles
- Legal and company basics 8 articles
- Team and hiring 9 articles
- AI-native building 9 articles
- Go-to-market 10 articles
- Pathways 12 articles
- Business models 8 articles
- Sectors 8 articles
- Operations and wellbeing 11 articles
Show the figures as a table
| Desk | Articles |
|---|---|
| Dream | 7 |
| Build | 11 |
| Grow | 6 |
| Fundable | 8 |
| Starting out | 14 |
| Funding and capital | 13 |
| Legal and company basics | 8 |
| Team and hiring | 9 |
| AI-native building | 9 |
| Go-to-market | 10 |
| Pathways | 12 |
| Business models | 8 |
| Sectors | 8 |
| Operations and wellbeing | 11 |
Illustration: World Enterprise Group Incorporated, drawn at build time from the articles published on this site.
AI-native building
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Each dot is one article; the amber mark is the desk’s median.
Show the figures as a table
| Group | Article | Reading time |
|---|---|---|
| AI-native building | AI features and customer data: what to decide first | 7 min |
| AI-native building | AI regulation for a small SaaS company: what to ask counsel about the EU AI Act and the Texas AI statute | 7 min |
| AI-native building | Choosing a model provider: the questions that matter | 6 min |
| AI-native building | Evaluating an LLM feature before you ship it | 6 min |
| AI-native building | Human review in an AI feature: where to keep a person in the loop | 6 min |
| AI-native building | Metering and budgeting model usage | 6 min |
| AI-native building | Prompt injection and the OWASP Top 10 for LLM applications | 8 min |
| AI-native building | Retrieval-augmented generation: what it is and where it breaks | 6 min |
| AI-native building | The NIST AI Risk Management Framework for a small team | 5 min |
Chart: World Enterprise Group Incorporated, counted at build time from the articles on this desk.
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ai
AI regulation for a small SaaS company: what to ask counsel about the EU AI Act and the Texas AI statute
Questions a small SaaS company can bring to counsel about the EU AI Act and the Texas AI statute, with dated facts from each primary source.
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ai
Choosing a model provider: the questions that matter
Questions to put to any language model provider before you build on it, drawn from vendor documentation on data use, retirement notice, limits and terms.
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ai
Evaluating an LLM feature before you ship it
A method for testing a language model feature before launch: written success criteria, a test set with edge cases, grading choices and re-runs after changes.
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ai
Human review in an AI feature: where to keep a person in the loop
Where a person should review an AI feature's output, how review fails when it becomes a rubber stamp, and what standards and laws say about oversight.
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ai
Metering and budgeting model usage
How to measure language model usage per feature and per customer, set limits before a bill surprises you, and handle the errors that limits produce.
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ai
Prompt injection and the OWASP Top 10 for LLM applications
What prompt injection is, how the OWASP Top 10 for LLM applications describes it, and the design questions the list raises for a small SaaS team.
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ai
Retrieval-augmented generation: what it is and where it breaks
What retrieval-augmented generation is, where it commonly fails in a product, and how to test retrieval and answers separately before launch.
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ai
The NIST AI Risk Management Framework for a small team
What the NIST AI Risk Management Framework contains, how its four functions read at the scale of a small team, and what the framework does not say.
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