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Recently, I used Cursor and AI Studio in conjunction with GPT and Gemini to build an enterprise-level crypto intelligence monitoring and semi-automated publishing system from scratch.
The core logic is actually not complicated—24/7 nonstop scanning of the entire internet for cryptocurrency news via RSS, Grok, and various large models, then the system automatically performs information cleaning, quality scoring, content generation, and finally decides the timing and channels for publishing based on traffic algorithms. From raw data input to publication, the entire process requires almost no manual intervention.
This setup is quite practical for teams engaged in intelligence aggregation and market monitoring. Automatic scanning combined with intelligent scoring helps you quickly identify truly valuable information, much more efficient than manual filtering. Especially in the explosive information environment of the crypto market, the ability to automatically capture key data changes and public opinion trends greatly supports decision-making.
Now that AI programming tools are so mature, and with the reasoning capabilities of large models, many workflows that previously required manual work can now be automated. This system is a good example of practical implementation.
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With such a high level of automation, does the labor cost get cut in half?
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Is this really reliable? Can the quality score be trusted, or is it all just spam?
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Isn't this the ultimate form of information arbitrage? Whoever masters it makes money.
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Is the Cursor and Gemini combo so powerful now? I need to try it.
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The question is, whose RSS feed source is of good quality? Input garbage, output is also garbage.
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With the crypto market information flow so fast, being even a few seconds late with automation could get you caught out. Is it reliable?
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I'm a bit worried that using this thing too much will make market information sources even more competitive.
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Suddenly, I feel that the jobs of intelligence analysts might not be secure anymore.
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After large models become faster at reasoning, engineers will definitely need to learn how to tune parameters. It’s definitely the trend.
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No, can this thing judge which information is valuable on its own? I feel like it might just be a bunch of trash.
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Did Cursor come up with Gemini? Alright, this efficiency really outperforms manual work by a mile.
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The key is how the traffic algorithm is set up; it seems easy to be manipulated.
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Damn, if this can truly automatically scan public opinion, what do analysts even do? Just fire them all.
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This idea has actually been tried during the PUBG era, but now with large models, the feasibility has definitely increased.
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Damn, if that's true, can those information brokers still survive?
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Is it semi-automatic or fully automatic? The headline sounds a bit exaggerated.
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Just want to ask, how much does this system cost in electricity to run for a month?
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Talking lightly, but are there going to be many pitfalls during actual deployment?
How to prevent false positives in the automatic scoring system? I'm worried it might frequently give high scores to spam.
Does this setup really run stably? Feels like the hallucinations of large models might cause issues.
Is the Cursor and Gemini combo reliable? I'm still using Claude.
Honestly, this is just the beginning of information warfare. Whoever controls public opinion controls the market.
Is the quality scoring algorithm open source? I want to study it.
Really, just integrating Grok+GPT+Gemini isn't simple, right? That must cost a lot...
Individual investors like us are really getting squeezed. While their system automatically monitors, I'm still browsing news on my phone.
Wait, if this system can truly publish automatically, does that mean many of the crypto news I see might be generated by AI? Feeling a bit uneasy.
Is Cursor this awesome now? Feels like I'm still writing code by hand.
But speaking of which, how do you avoid false data in the information quality scoring...
If this thing can truly operate 24/7 automatically, how much manpower would it save?
The combination of Cursor and Gemini is now accessible to everyone, but the key is still the reliability of the data sources.
I'm curious about how you deal with FUD information...
This kind of automated system sounds awesome, but there must be quite a few pitfalls when actually running it.
Efficiency is indeed high, but since the crypto market information is mixed with true and false data, I still have some reservations about purely AI-based scoring.