u/Bitman321

I’ve been tinkering with an idea called Bellwether. You describe a future event in plain English (“tell me when this policy changes”, “notify me if this price threshold is crossed”), and it watches the web for credible evidence that it actually happened. If it did, you get notified. If not, silence.

Most alert tools are keyword matchers, so guides, forums, and old coverage all spam you. This tries to judge the event instead.

Still early / just an idea I’m building out, but the judgment layer is the part I think is interesting for this sub.

How the models fit in:

It doesn’t use an LLM as a chatbot. Open instruct models do the judgment steps:

* Vagueness check - reject topic-only inputs like “interest rates” and suggest clearer watch sentences
* Compile - turn a clear sentence into structured JSON: triggers, non-triggers, search queries, authoritative domains
* Detect / decide - given a candidate page, decide whether the event actually occurred
* Outputs are JSON-only, low temp, validated with Zod. Watches are timestamped at creation so only post-watch evidence can fire them.

Inference is Hugging Face open models (HF_MODEL to swap). Default is Llama 3.3 70B right now; the same pipeline is set up to run smaller ones too - Llama 3.1 8B, Qwen2.5 7B, Mistral 7B - and there’s an eval harness to compare them on historical fixtures.

Rough demo: https://bellweather-alerts.vercel.app/

Source code: https://github.com/JamesANZ/bellweather-alerts

I’ve been tinkering with an idea called Bellwether. You describe a future event in plain English (“tell me when this policy changes”, “notify me if this price threshold is crossed”), and it watches the web for credible evidence that it actually happened. If it did, you get notified. If not, silence.

Most alert tools are keyword matchers, so guides, forums, and old coverage all spam you. This tries to judge the event instead.

Still early / just an idea I’m building out, but the judgment layer is the part I think is interesting for this sub.

How the models fit in:

It doesn’t use an LLM as a chatbot. Open instruct models do the judgment steps:

• Vagueness check - reject topic-only inputs like “interest rates” and suggest clearer watch sentences
• Compile - turn a clear sentence into structured JSON: triggers, non-triggers, search queries, authoritative domains
• Detect / decide - given a candidate page, decide whether the event actually occurred
• Outputs are JSON-only, low temp, validated with Zod. Watches are timestamped at creation so only post-watch evidence can fire them.

Inference is Hugging Face open models (HF_MODEL to swap). Default is Llama 3.3 70B right now; the same pipeline is set up to run smaller ones too - Llama 3.1 8B, Qwen2.5 7B, Mistral 7B - and there’s an eval harness to compare them on historical fixtures.

Rough demo: https://bellweather-alerts.vercel.app/

Source code: https://github.com/JamesANZ/bellweather-alerts

In exchange for some of the highest taxes in the developed world, we still:

• Pay out of pocket to see a GP
• Pay heavily for childcare
• Pay for university
• Pay tolls just to use major roads
• Get hit with payroll tax, GST, super taxes, CGT, alcohol excise, tobacco excise, and stamp duty
• Get slugged with the Medicare Levy Surcharge once income creeps a bit over $100k
• Don’t get family based taxation or income splitting
• Sit on enormous mineral wealth and somehow still get told there’s never enough revenue

And now the one broad protection ordinary Australians had against already high tax rates: the CGT discount, is apparently on the chopping block, dressed up as “intergenerational fairness.”

If the government wants to argue for higher capital gains tax, then at least be honest about it: this is a revenue grab.

If they want to talk seriously about fairness, start with:

• lower income tax rates and index them to inflation
• better spending discipline
• meaningful productivity reform
• better use of the country’s resource wealth

I thought they were targeting housing only? How can we talk them out of it? I think taxes are too high as is, with the top bracket strongly discouraging work.