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
An Apache-2.0 Python framework that turns existing Transformers or vLLM-served language models into bounded choice, yes-or-no, and score decisions, with levels for zero-label bias correction, calibration, and question-specific decision heads.
Newest Guide
Decide whether local AI needs new hardware, understand RAM and VRAM, and check compatibility before spending on an upgrade.
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.
Running AI locally
Start with the model and app, then compare computers, memory, storage, and graphics by the work they need to support.
