AI-Assisted PDF to Word: Review the Converter and Its Checks
Inspect an open-source PyQt PDF-to-Word converter, its heading heuristics, and why a zero suspicious-character score does not prove conversion fidelity.
Read moreAI Models & Basics
Model comparisons, prompt technique, and hallucination control — the fundamentals, in plain language and without the hype.
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AI Hallucinations in Code: Check APIs, Versions, and Evidence
Catch invented APIs and unsupported claims with version-specific documentation, compilation, runtime checks, and explicit uncertainty.
Read moreClaude Projects Tutorial: Organize Sources and Instructions
Set up a focused Claude project, separate reference material from instructions, and test whether answers preserve sources and uncertainty.
Read moreClaude vs ChatGPT: A Reproducible Evaluation Worksheet
Compare Claude and ChatGPT using identical writing, Java review, and document tasks. Record tools, sources, corrections, and time before choosing a plan.
Read moreChoosing AI Tools for a Java Development Workflow
Choose an assistant around a concrete Java task: code review, a bounded repository change, or documentation. Includes a reusable evaluation worksheet.
Read morePrompt Engineering: Define Inputs, Constraints, and Checks
Write prompts that preserve facts and expose missing context. Use examples, output contracts, and verification instead of unsupported performance promises.
Read moreChatGPT for Beginners: Ask, Check, and Refine Your First Task
Start with a concrete ChatGPT task, provide the needed context, check factual claims, and review privacy and plan settings without relying on old model tables.
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