01AI knowledge search evaluation
What should a RAG demo prove?
A fluent demo can hide missing sources or unsupported claims. Use a small, repeatable acceptance pack to test retrieval and answers separately.
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Useful answers for search, AI, and real operations.
Plain-language notes on being found, understood, and trusted in traditional and AI-led search, plus the engineering decisions that make AI useful after the demo.
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OpenAI DevDay 2026
OpenAI DevDay 2026: What shipped and how to use it
DevDay 2026 was less about one new model than about turning AI into a persistent work layer. Here is what shipped, where it fits, and why usage transparency matters as API and Codex products converge.
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Ideas you can use.
Each article starts with a question a buyer, operator, or builder might ask, then makes the answer clear before going deeper.
02AI and spreadsheet workflows
Can AI safely edit spreadsheets?
Let AI prepare a specific row change while the application keeps control of the target, fields, and final write.
Read the note03Document automation
Stop duplicate document records
Prevent a timeout or repeated upload from turning one business document into several records.
Read the note04AI scheduling
Should AI book a meeting?
Choose who owns the reservation before giving an assistant calendar write access.
Read the note05AI customer support
When should a customer AI assistant hand off?
Give customers a clear route to a person, then pass a short reason and useful context to a confirmed destination.
Read the note06AI search visibility
Which AI bots should I allow?
Decide by URL group: public discovery, model use, or private access.
Read the note07AI knowledge systems
When is native AI search enough?
Start with the search tool your team already uses. Build a custom assistant only after you can name a source, validation step, or workflow it cannot provide.
Read the note08AI search visibility
Does llms.txt help AI search?
A team has published a useful service page, and someone proposes an llms.txt file as a prerequisite for appearing in AI answers. Engineering time spent on an unproven signal can postpone fixes to the page itself.
Read the note09AI document processing
Which AI fields need human review?
An extracted value can look plausible and still become a bad record. Set review rules field by field, then keep consequential actions with a person.
Read the note10Production AI automation
When is an AI automation pilot ready for production?
A convincing demonstration is only part of the decision. Before live operations, check whether the whole workflow delivers useful results and whether your team can handle the exceptions.
Read the note11AI knowledge systems
How to tell if your company is ready for an AI knowledge assistant
An internal assistant is useful only when it can find current, trusted information and send uncertain questions to a person. Check the workflow before connecting every document.
Read the note12Editorial systems
How to write content that earns a useful answer
The strongest answer-oriented articles do not sound like a glossary. They start with a real decision, make the recommendation clear, and show the reasoning behind it.
Read the note13Technical SEO
A practical technical SEO checklist for an AI engineering site
Technical SEO is not a separate layer of polish. It is the set of delivery and information choices that lets a useful page be found, loaded, understood, and revisited.
Read the note14AI workflow strategy
Which business workflow should you automate with AI first?
The best first AI workflow is rarely the most impressive one. Start with a repetitive process that matters, can be checked, and has an owner who wants it to improve.
Read the note15AI architecture decisions
Do you need an AI agent?
Your team needs work completed. The design question is how much freedom the software needs to get there. Start by separating interpretation from action.
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