When I read about AI, cloud services, and security, I use several kinds of sources. Papers explain new methods, release notes describe product changes, and engineering posts describe what people tried. I look for different things in each source. One combined list can make it hard to decide what to read more closely.
I use eight information-gathering routines with scheduled actions in Gemini. For papers, I ask what is new and how it might help my development work. For cloud updates, I ask whether the change could affect my systems. I treat the schedule and the questions I want a summary to answer as separate choices. Here is how I set up those requests.
These are my settings as of October 13, 2026. All times are Japan Standard Time. The schedules below describe the configured frequency, rather than a log confirming every run.
Find papers and practical engineering advice
1 Select ten papers and take a closer look at one
I schedule the paper request for 7–8 a.m. every day. I ask for ten papers, preprints, or technical reports from research institutions and company research teams. Preprints are papers shared before formal journal publication. For each item, I ask what is new and how the proposed method or system works.
To help choose relevant papers, I provide context from my public GitHub work and my professional interests in AI, security, and cloud services. I then ask for a closer look at one especially relevant item, including ideas for using it in development. The aim is to help me choose which paper to read in full.
2 See what developers in overseas communities are discussing
Every day at 7:30 a.m., I ask Gemini to check Hacker News, a site for technology discussions, and the Reddit communities r/programming, r/MachineLearning, and r/devops. The request focuses on new open-source software, technical debates, and opinions about different technologies. Open-source software makes its source code available for use and modification under its license.
I ask for a short explanation of each topic, why it is getting attention, and what people like or criticize about it. I also ask for links to the original posts so I can read the discussions myself.
3 Collect lessons from real development work
At 8 a.m. every day, I ask for ten practical articles or resources about AI, cloud services, and security. Sources include Japanese and international engineering blogs, knowledge-sharing sites, and conference presentations. I look for accounts of using a technology, fixing problems, and designing systems.
Alongside the official documentation, I want to know what went wrong for people who used the technology and how they solved it. When selecting papers, I focus on new methods. For practical articles, I ask what to watch out for when using a technology.
4 Check how cloud updates could affect my systems
I have a separate request to check official release information and blogs for AWS, Azure, and Google Cloud in the morning or periodically. It covers new features and previews, which let users try features before their full release. It also covers features that are no longer recommended and changes that could stop existing setups from working.
I ask for both a summary of the update and its possible effect on my infrastructure: the servers and cloud services I use together. I want to find features worth trying and updates that may need a closer check, such as a possible configuration change.
Choose a schedule that fits the information
5 Follow updates on a specific topic
I also have a request to follow a topic over time. One example is reporting about a possible OpenAI stock market listing, or IPO, along with partnerships and changes in how the company is run. I ask it to check financial media and official sources periodically and alert me to changes. The IPO is a topic I follow, not a confirmed event.
6 Read short news summaries in the morning and evening
My general and technology news request is scheduled twice a day, in the morning and evening. I ask for short summaries of current affairs, economic news, and technology from major news outlets. This helps me follow broader news alongside my specialist interests.
7 Find technical videos with explanations and demonstrations
I ask for technical video recommendations every day from YouTube and similar sources. Topics include testing AI models, ways of organizing development work, and security. These give me options when I want to learn by watching an explanation or demonstration.
8 Choose books on the first day of each month
On the first day of each month, I ask for technical books, including new releases, that match my interests and recent technology trends. I use a different schedule for books that take time to study than for news I want to check each day.
Use the information in development work
Choose sources and a schedule → Ask for details that fit the purpose → Read the original sources → Check test conditions and my environment → Choose what to read or try next
I ask for different details in each of the eight routines. For papers, I want a candidate for deeper reading and possible uses. For community discussions, I want to understand the interest and disagreement. For practical articles, I want things to watch out for during implementation. For cloud updates, I want the possible effect on my setup. I request these details to help me decide what to read or try next.
For example, suppose I wanted to improve an app that searches documents and uses them to answer questions. A paper might suggest a new method. An engineering post might explain problems to watch out for when using it. A cloud update might introduce a useful feature. This is only an example of how the information could fit together. It does not describe a change I made or an improvement I measured.
Before using an idea, I would still need to read the original paper or official documentation. I would check how it was tested, which versions it supports, and whether it fits my environment. A popular technology may be worth a look, but those details matter when deciding whether to use it.
An example request you can adapt
The example below was written for this article using the routines described above. It is an example you can adapt, not the original prompt from my setup.
“My interests are AI, cloud services, and security. Use the public GitHub context I share to select ten relevant papers, preprints, or technical reports from research institutions and company research teams. For each item, explain what is new and how the method or system works. Choose one especially relevant item and explain it in more detail. Suggest possible uses in development and list what I should check before trying it. Include links to the sources. Separate what you verified from what you inferred. Say if you could not read the full text of a source.”
I added the instructions about source links and what the AI could verify as suggestions for readers writing their own requests. A detailed prompt does not guarantee a correct answer. Before sharing project information, check whether it is appropriate to share that information with the AI service.
Start with one topic you want to follow
The eight routines serve different purposes. Some give a quick news overview, some track changes, and one takes a closer look at a paper. I adjust the schedule and the requested details to match what I want to learn.
To try this approach, choose one topic you care about. Decide where to look, how often to check, and what decisions the information should help you make. I use the summaries as a starting point for choosing which sources to read more closely.
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