By skyforbes Imagine waking up to a short, sharp briefing that tells you only what you should know — not every headline, not every viral rumor, but the three-to-five items that will affect your day, your team, or your thinking. That’s the point of a personalized news brief: to turn noise into signal. In a world where 10 news alerts can blow up your phone before breakfast, teaching ChatGPT (or any capable LLM) to surface and synthesize the right stories is like hiring a tiny, relentlessly efficient research assistant.
This guide is both practical and humane. I’ll show you a step-by-step recipe you can copy, an example walkthrough, and simple benchmarks you can use to measure whether your brief is getting better — or just louder. I’m keeping it honest: you’ll need to invest a little time up front, and you’ll need to tune the system as your priorities change. But the payoff — minutes reclaimed each morning, better context for conversations, fewer surprises — is real.
Why train an LLM to brief you?
There are three big benefits:
- Prioritization. News volume grows every year; you don’t. A trained brief filters for the things that match your goals: industry moves, competitor signals, policy changes, or — if you want — important culture pieces.