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How to Avoid Fake References When Using AI to Write Academic Papers: 5 Steps from Searching and Verification to Citation Integration
ByShark 2026年 11月 4日

Author’s note: This article walks through a five-step verification process for addressing a common problem in AI-assisted academic writing: references that don’t appear in databases. It covers finding sources, opening the original texts, checking bibliographic details, comparing citations with the sources, and confirming them manually. Many people encounter the same problem when they first use…

Read More How to Avoid Fake References When Using AI to Write Academic Papers: 5 Steps from Searching and Verification to Citation Integration
AI Memberships | APIYI Tips & Tricks | OpenAI API

Using GPT for Coding and Organizing Information: ChatGPT Plus or Pay-as-You-Go API? 5 Factors to Help You Choose
ByShark 2026年 11月 4日

Author’s note: When the free tier isn’t enough, should you subscribe to ChatGPT Plus or pay as you go with the GPT API? This article helps you decide by comparing five factors: how you use them, how billing works, which tools they support, payment and invoicing, and estimated costs. Many developers rely on GPT models…

Read More Using GPT for Coding and Organizing Information: ChatGPT Plus or Pay-as-You-Go API? 5 Factors to Help You Choose
AI Model Troubleshooting | AI Tidbits

DeepSeek Servers Busy? 5 Steps for Everyday Users to Identify the Cause and 4 Temporary Workarounds
ByShark 2026年 11月 4日

Author’s note: This article is for everyday DeepSeek users. It explains how to find the source of a “server busy” error and what temporary alternatives are available. On the afternoon of November 3, 2026, several users posted in quick succession on the tech community V2EX. Their titles were blunt: “DeepSeek is down” and “Is DeepSeek…

Read More DeepSeek Servers Busy? 5 Steps for Everyday Users to Identify the Cause and 4 Temporary Workarounds
AI Agents | AI Tools | Video AI API

Code-Generated Video vs. Pixel-Generated Video: 4 Questions to Decide When AI Should Write the Code
ByShark 2026年 11月 4日

Author’s note: Starting with the f(t) rendering principle and the SenseNova 6.8 Code2Video case, this article uses four questions to help you choose between code-based and pixel-based video generation. If you create science explainers, formula walkthroughs, or data animations, you’ve probably run into the same problem: the visuals look good, but the text is wrong…

Read More Code-Generated Video vs. Pixel-Generated Video: 4 Questions to Decide When AI Should Write the Code
AI Tools | API Code Examples | API Use Cases

Get Agents to Generate Interactive Charts: Flint-interactive’s Semantic Event Approach and 3 Integration Paths
ByShark 2026年 11月 4日

Author’s note: This article breaks down how Flint-interactive uses “semantic events + update operations” to reduce the cost and error rate of agent-generated interactive charts, and explores three integration paths. If you’re building an AI agent for data analysis or reporting, you’ve probably run into this: an agent can quickly create a static chart, but…

Read More Get Agents to Generate Interactive Charts: Flint-interactive’s Semantic Event Approach and 3 Integration Paths
AI Memberships | AI Model Pricing

Understanding and Verifying Large Language Model API Bills: 5 Types of Charges and a 4-Step Reconciliation Method
ByShark 2026年 11月 4日

Author’s note: This article breaks down input, output, cache, and reasoning tokens, along with multimodal billing, in Large Language Model API bills. It also covers practical ways to reconcile usage against request logs, investigate sudden cost changes, and respond to pricing updates. You open your bill at the end of the month and notice that…

Read More Understanding and Verifying Large Language Model API Bills: 5 Types of Charges and a 4-Step Reconciliation Method
API Best Practices | APIYI Tips & Tricks

LLM Findings Become Outdated After 15.7 Months on Average: Why You Should Retest Each Model Version (5-Step Retesting Checklist)
ByShark 2026年 11月 4日

Author’s note: Stanford researchers found that 44% of widely cited LLM findings are outdated. Among findings with an estimated expiration date, the average lifespan was just 15.7 months. This article turns the research into a model-selection retesting checklist development teams can use. “This model can’t count the r’s in strawberry.” “Information in the middle of…

Read More LLM Findings Become Outdated After 15.7 Months on Average: Why You Should Retest Each Model Version (5-Step Retesting Checklist)
API Best Practices | APIYI Tips & Tricks

How to Troubleshoot Model API Call Errors: 6 Steps to Identify Whether the Problem Is on Your End, the Gateway, or the Upstream Model
ByShark 2026年 11月 4日

Author’s note: A troubleshooting guide for developers working with model APIs in production. Using a three-layer framework—your own request, the gateway platform, and the upstream model—it explains how to pinpoint failures with error codes, logs, and a minimal curl reproduction, and what information to include in a support request. An alert goes off in the…

Read More How to Troubleshoot Model API Call Errors: 6 Steps to Identify Whether the Problem Is on Your End, the Gateway, or the Upstream Model
API Best Practices | APIYI Tips & Tricks

Lower Model Pricing Doesn’t Mean a Lower Bill: A 5-Step Method for Estimating Real Costs Using Token Consumption and Caching
ByShark 2026年 11月 4日

Author’s note: When comparing model costs, looking only at the price per million tokens can lead you to the wrong choice. This article explains how to calculate cost using “unit price × actual token consumption” and walks you through testing models on a small sample of your own tasks. When choosing a model, many teams…

Read More Lower Model Pricing Doesn’t Mean a Lower Bill: A 5-Step Method for Estimating Real Costs Using Token Consumption and Caching
AI Tools | APIYI Tips & Tricks

Non-Developers Building Data Processing Workflows with Codex: 5 Principles for Dividing Responsibilities to Preserve Methodological Ownership and Human Verification
ByShark 2026年 11月 4日

Author’s note: Using Heimstaden’s environmental risk assessment project as an example, this article breaks down how non-developers can work with Codex on data discovery, cleaning, and workflow building—and why ownership of the methodology and human validation must remain with domain experts. Many business analysts know their industry but don’t write code. When a project involves…

Read More Non-Developers Building Data Processing Workflows with Codex: 5 Principles for Dividing Responsibilities to Preserve Methodological Ownership and Human Verification