From Coding to Travel: Real-World AI Tools and Workflows You Can Use Today

As artificial intelligence moves from a novel curiosity to a practical utility, professionals across various fields are embedding specific AI tools into their daily workflows. While general-purpose models like ChatGPT and Claude remain staples for brainstorming and answering broad questions, the real productivity gains are found in specialized applications and clever integrations that solve specific problems.

Coding and Development

In the software development world, AI coding assistants have become indispensable. While GitHub Copilot is a common choice for autocompletion and simple refactoring, many are moving to more integrated solutions like Cursor, an AI-first code editor, praised for its powerful workflow. Other tools mentioned include:

Augment Code: A VSCode extension noted for its effective remote and local agent features.
Warp.dev: A terminal with built-in AI for generating shell commands, helping users who can't remember specific command-line syntax.
Local LLMs: Some developers use ollama with models like qwen2.5coder for privacy and offline capability.

Information Management and Research

One of the most powerful applications of AI is processing and querying large volumes of text. Instead of manually searching through dense documents, users are turning to tools that can ingest sources and provide direct answers.

NotebookLM: Repeatedly cited as the most useful tool for embedded work and research, allowing users to load technical manuals and datasheets and ask specific questions, with the AI providing answers and citing the source passages.
Perplexity: Often used as a Google replacement, it excels at research by providing summarized answers with linked sources.
Kagi: The Kagi suite is popular for its Summarizer (used to quickly grasp the essence of an article), Translate, and Assistant features, which can be used for tasks like generating RSS feeds from webpages.

Creative Workflows and Personal Productivity

Beyond professional tasks, people are building ingenious personal systems with AI:

Enhanced Note-Taking: A popular workflow involves using a voice dictation tool like SuperWhisper or ChatGPT's mobile app (noted for its superior speech recognition) to capture thoughts on the go. These raw notes are then processed by a model like Claude, which can run in an Obsidian vault to automatically add tags, create links, and structure the information for later retrieval.
Language Learning: A common hack is to use an LLM like Claude or Gemini to generate short stories in a target language at a specific difficulty level (e.g., A2 German). This text is then fed into a text-to-speech service like ElevenLabs to create a custom listening comprehension exercise.
Travel Companion: ChatGPT's voice mode is being used as a real-time travel assistant for translating menus, explaining cultural nuances (like the difference between two local dishes), and practicing basic phrases in a new language.
Personal Assistant: One user shared their setup of a custom AI bot in a shared Telegram group with their spouse. The bot manages their shared calendar, reminders, and shopping list, all through natural language interaction.

Contrasting Views

Despite the enthusiasm, a notable portion of users remain skeptical, stating they use no generative AI tools on a daily basis. They argue that for many tasks, traditional search is faster, or the output from current AI is not yet reliable enough for critical work. This highlights a key takeaway: the value of AI tools is not universal but depends heavily on the specific use case and the user's willingness to adapt their workflow.