LifeHubber
LifeHubber helps you use AI seriously without handing your whole workflow to one model, app, or company.
Start with practical guides, resources with original links, access routes, and context that keep your judgment, files, prompts, and habits useful as tools change.
New on LifeHubber
A recently added Resource, the newest Guide, and the latest Radar story.
Recent Resource
A native-PyTorch learning project for training tiny language models from scratch, with public data and checkpoints, tokenizer, pretraining and alignment stages, LoRA, tool-use and agentic-RL examples, plus local inference paths.
Newest Guide
Use practice material, inspect the current controls, test one familiar task, and decide what role a new AI tool has earned in your work.
Latest Radar
OpenAI says it intends to stop supplying models to Cursor after the coding tool joined SpaceX, with a proposed November 12 cutoff.
Reader paths
Choose a path based on the AI question you are actually facing.
Choosing tools
The question is not which chatbot is best; it is which one fits the job, risk, and account or data boundaries.
Prompting
Prompting is less magic wording and more a clean handoff: task, context, constraints, and how you will judge the answer.
Reviewing output
When an AI answer sounds finished, use a checking habit before it becomes a work note, public claim, or decision.
Testing models
Before signing up or sending real data, compare access routes, limits, privacy posture, and related projects.
Agents
Agents get interesting when tools, accounts, memory, and permissions enter the room. Start with the guide, then inspect related resources and Radar signals.
