AI Once a Day

Ivy at AI Once a Day

One useful AI insight, every single day. No hype, no doom — just things that actually work. Hosted by Ivy.

  1. 15h ago

    Day 105: Use AI to organize your digital photo collection effortlessly.

    Hey, Ivy here. Today, we're diving into how you can use AI to organize your digital photo collection effortlessly. If you're like many people, your photos might be scattered across various devices and cloud storage, making it a challenge to keep track of all those precious memories. But don't worry, AI tools are here to help you sort, tag, and categorize them, making it a breeze to find your favorite moments whenever you need them. Imagine being able to search for a specific photo just by typing in a keyword or a date, and having it pop up instantly. That's the power of AI at work. These tools can recognize faces, locations, and even events, which means they can automatically group photos of the same person or from the same vacation, for instance. This not only saves you time but also makes your digital photo collection much more enjoyable to browse through. We'll also cover some handy tips for maintaining your collection, ensuring that your photos are always easy to access and beautifully organized. Whether you're a professional photographer or someone who just loves snapping pics on your phone, these AI tools can make a big difference. And don't worry if you're not tech-savvy. Many of these AI-powered photo management tools are designed to be user-friendly, with simple interfaces that anyone can navigate. You'll be amazed at how quickly you can get your photo collection in order. So, if you're ready to take control of your digital photos and make sure those special moments are always at your fingertips, stay tuned. And don't miss tomorrow's episode, where we'll explore how AI can enhance your cooking skills. Whether you're a seasoned chef or just starting out in the kitchen, AI has some incredible tools to offer. Stay tuned!

  2. 3d ago

    Day 102: Design the workflow before automating it.

    Hey, Ivy here. Today, resist the urge to start with an automation tool. A tool can execute a workflow, but it cannot rescue a rule nobody agreed on, find an owner who was never assigned, or guarantee that a failed notification reaches someone another way. First, make the work visible. Use this exercise exactly: "Map this workflow before suggesting any automation. Use these headings: Trigger, Inputs, Rules, Actions, Exceptions, Human approvals. Under each heading, record what happens, who owns it, and what information is required. Then write test cases for a duplicate request, a missing owner, and a notification failure. For each test, give the expected behavior, the human fallback, and the evidence we should log. Do not recommend tools until the map and tests are complete." The six headings describe the normal path and the places where judgment enters. The test cases make you design what happens when the normal path breaks. For a duplicate, decide whether the system blocks, merges, or flags it. For a missing owner, decide who receives the exception. For a notification failure, define the retry, alternate channel, or manual queue, plus the evidence that shows what happened. Take the completed map to the people who do the work. Replace vague ownership with named roles, keep meaningful approvals with people, and run the tests with sample data. Only then should you compare tools or connect a live system. The result is a set of requirements and recovery steps that your team can inspect before automation repeats the process at scale. Tomorrow, we will use AI to discover new music that matches your mood.

  3. 4d ago

    Day 101: Question a document before you file it.

    Hey, Ivy here. Today, pause before you drop a document into a folder. A polished summary is not enough if it misses a payment date, an account reference, or the sentence that asks someone to act. The safer move is to ask for a traceable extraction while the document is still open. Attach the document to an image-capable AI assistant, if your privacy rules allow it, and paste this prompt exactly: "Read the attached document before I file it. Extract every visible date, amount, reference number, requested action, and deadline. For each item, quote the exact visible text that supports it and note the page or section if available. Do not infer missing details. Mark anything unclear, conflicting, incomplete, or hard to read as UNCERTAIN, explain why, and list the questions I should resolve before filing." The quotes matter because they give you a fast route back to the page. The UNCERTAIN label matters because unclear text should stay unclear until a person checks it. AI can misread scans, skip small print, merge nearby fields, or supply a plausible detail that is not present, so compare every item with the original document. Once you have checked the output, use it to choose a useful file name, add the right reference, route the document, or record the follow-up. Keep the source file as the authority, and do not upload sensitive material to a tool that is not approved for it. Tomorrow, we will map a workflow before choosing anything to automate.

  4. 5d ago

    Day 100: Find the story hiding in a small spreadsheet.

    Hey, Ivy here. Day 100 is about reading a small spreadsheet without rushing past the boring checks that make the story trustworthy. A tidy-looking table can still contain blank cells, duplicated records, mixed formats, or numbers stored as text. Any one of those can distort a total or make a normal row look unusual. Attach a non-sensitive CSV or spreadsheet and paste this prompt: "Inspect this spreadsheet before drawing conclusions; list every column and its apparent type; count missing values by column; identify duplicate rows and the columns used to define a duplicate; flag inconsistent dates, numbers, currencies, categories, and text formats; then report patterns and anomalies with exact row numbers and calculations; use two sections titled Observations and Interpretations; put only verifiable spreadsheet facts in Observations, show the calculation behind each claim, and put possible explanations in Interpretations with uncertainty clearly labeled; do not invent missing context, and ask me questions when a field is ambiguous." Read the response in order. First compare the column list and apparent types with the sheet. Confirm the missing-value counts, then inspect the exact rows labeled as duplicates or format problems. For each reported pattern or anomaly, open the cited rows and redo at least one calculation in the spreadsheet or a calculator. If the AI cannot identify row numbers, give the table a stable row ID and ask it to run the inspection again. The final separation matters. Observations are things the cells and calculations support. Interpretations are possible reasons those facts occurred, and they may be wrong without more context. Keep both sections, because that record lets another person verify the finding without inheriting the AI's guess. Tomorrow, we will question a document before filing it so dates, references, and actions do not disappear.

  5. 6d ago

    Day 99: Build a decision matrix you can challenge.

    Hey, Ivy here. A decision matrix can help when several options look reasonable for different reasons. The catch is that a polished total can feel more objective than it really is. Today's exercise keeps your judgment visible and gives you a way to challenge the result. Paste this prompt into your AI assistant: "I am choosing among [OPTIONS]. First, ask me for the criteria and a weight for each criterion, with weights totaling 100%; then ask me to score every option from 1 to 10 on each criterion; build a weighted decision matrix; show the arithmetic for every weighted score and total; identify the criterion driving the result most; rerun a sensitivity test with that criterion's weight reduced by 50%, redistributing the difference proportionally across the other criteria; compare the rankings, state what changed, and flag any assumptions or missing information; do not make the decision for me." Start by replacing the bracketed options with the real choices. Answer the questions about criteria, weights, and scores, and make sure the weights total 100%. When the matrix appears, check one or two weighted scores yourself by multiplying the score by the weight. Then read the sensitivity rerun closely. If cutting the result-driving weight by 50% changes the ranking, you have learned that the choice depends on that preference. If the ranking stays put, the comparison is more stable under that specific test, though it is still not proof that the top option is right. The outcome is a decision record you can inspect, explain, and revise instead of a recommendation you have to trust. Tomorrow, I will show you how to find the story hiding in a small spreadsheet.

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One useful AI insight, every single day. No hype, no doom — just things that actually work. Hosted by Ivy.