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AI Agent Discussion -- From Where to Go to Towards the Universe

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Series Article Catalog

A total of six articles

Catalogue

AI Agent Discussion -- Core Elements of Local Agents

AI Agent Discussion -- From Where to Go to Towards the Universe

AI Agent Discussion -- Let Politics Be a Stable Cornerstone (To be continued)

AI Agent Discussion -- Irreplaceable Art Creation (To be continued)

AI Agent Discussion -- Labor Market Transformation Self-Help (To be continued)

AI Agent Discussion -- How to Realize Gundam Haro (To be continued)

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Tips: AI Agent, Kardashev Scale, Structural shift, Future, Civilization

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Foreword

Today, I want to talk about a super cool topic: how AI is truly exploding our productivity! In the past, if you wanted to develop a product, you had to manually write the code, debug it, and test it all yourself, right? But now, AI can help us write code. While we still need to verify it much of the time, and sometimes it gives us "off-topic" code, just by reducing the time we spend learning new things and optimizing code, it significantly shortens the entire development cycle! This is truly amazing!

What about the future? I don't even have to think about it; one person might be able to handle everything that currently requires many. So, many people will start to worry, "Oh no, will 90% of people lose their jobs?"

However, from our perspective as developers, that's not really the case! We have many choices. As the saying goes: "When God closes a door, he will open another window for you!"

This is the main point I want to share with everyone in this!

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Tip: The following is the main content of this article, and the following cases can be used for reference

What Stage is Earth Civilization Currently In?

First, let's broaden our perspective a bit. Looking at the long river of cosmic civilization history, what stage do you think our Earth civilization is roughly in right now? This way, we can more clearly know where we need to go next, right?

The most famous classification of cosmic civilization levels is the Kardashev Scale! This scale was proposed by the Russian astrophysicist Nikolai Kardashev in 1964. Simply put, it measures how advanced a civilization is by its ability to utilize energy.

As of 2025, our Earth civilization, according to the Kardashev Scale, falls approximately between:

🌍 Type 0.73 to 0.8 Civilization (roughly around Type 0.73)

This number is estimated based on the total amount of energy we can currently utilize. Although it's a theoretical model, it gives us a clear reference point. So you see, we are still very, very far from a complete "Type 1 Civilization"!

What is a "Type 1 Civilization"?

So, what conditions must be met to achieve "Type 1 Civilization"? Let's find out together:

• First, it needs to be able to fully control and utilize all energy on the planet! This includes geothermal energy, tidal energy, and fully developed solar and wind energy.
• Secondly, it must be able to precisely plan and control the global climate and environment.
• Moreover, on this planet, it can freely regulate the ecological environment and avoid climate crises.

However, as of today in 2025, humanity is still very, very far from a "Type 1 Civilization"!

Without the assistance of AI Agent technology, it would be absolutely impossible for humans to become a "Type 1 Civilization."

Why Do We Need Agent Technology?

Let's talk in depth about why we can't reach Type 1 Civilization without Agent technology.

• First, to precisely control global climate and environment, we must build a super sensitive, real-time responsive system. Because the environment has a "butterfly effect," even small changes can trigger big problems. So, we not only need a large number of distributed sensors to monitor tiny environmental changes in real-time, but also actuators that can quickly make subtle and precise adjustments based on these monitoring results.
  To achieve this kind of "real-time sensing - chain micro-control," we need to find the "butterflies of the weather," which are those very small but critical variables. How do we find them? One method is to use Machine Learning Modeling (ML Modeling), allowing the model to automatically identify key variables from massive sensor data, and even discover potential causal relationships.
  Once we build a causal inference model (Causal Graph) for climate chain effects based on this data, we can develop Agents specifically for chain micro-control: these weather micro-control Agents no longer just provide data; they can, based on real-time perception, judge possible chain reactions, and then autonomously take subtle, localized, continuous regulatory actions to achieve precise control and stable maintenance of the overall environment. It's like a smart housekeeper that can perceive, judge, and execute on its own, instead of just following instructions. Sounds like science fiction, but this is what we need to do in the future!

• Next is the utilization of renewable energy. Currently, our conversion efficiency is still very poor, and we still heavily rely on fossil fuels and nuclear energy.
  Regarding energy utilization, there are actually a myriad of research directions! For example, for wind power generation, environmental parameters like wind speed, direction, and vortex change every second. Is it possible for us to use ML models to predict wind field behavior, and then automatically adjust blade direction to capture maximum energy? A practical example is Google's research on using reinforcement learning to optimize wind farm operations, which resulted in a 20% increase in wind power generation efficiency!
  What about solar energy? In addition to researching how to make solar panels "track the light," we can also improve traditional MPPT (Maximum Power Point Tracking) technology through algorithms. Most current MPPT algorithms mainly determine whether the point of highest power generation efficiency has been reached by calculating the rate of change of voltage and current (what you call differentiation).
  However, just looking at changes in voltage and current can sometimes hit bottlenecks, especially when environmental conditions change rapidly. Why? Because to achieve the highest energy conversion efficiency for a solar panel, theoretically, it's when the solar panel's output "impedance" perfectly matches the "impedance" of the load connected to it (like the input end of an inverter). Imagine it like two water pipes; the water flows most smoothly when they have the same diameter.
  And this optimal "impedance matching point" is actually affected by many factors! Not just voltage (V) and current (I), but also temperature (T), light intensity (G), the aging or contamination level of each cell in the solar panel, and even the inverter's input/output status (Load Status). These parameters constantly change, causing the optimal operating point to dynamically adjust.
  Therefore, if we only use traditional voltage and current differentiation methods, we might not always find that most perfect point. At this time, building an adaptive algorithm through machine learning that can consider all these complex parameters, allowing it to automatically find the correlation between these parameters and the optimal impedance matching from vast amounts of data, is definitely a tool worth in-depth study! This way, we can track the maximum power point more accurately, convert every bit of sunlight into electricity, and significantly improve conversion efficiency.
  So, only when we truly understand the underlying variable relationships can we truly control the flow of energy, instead of just "relying on nature"!

• Finally, and most crucially, we all still live on Earth! Space travel is still a dream; we haven't reached the point of colonizing other planets.

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Where Should Humanity Go in the Future?

From the Kardashev Scale, we are still far from a Type 1 Civilization, and there are many technologies waiting to be breakthroughs! To upgrade civilization and break through Earth's limitations, AI Agents are absolutely key.

Humanity, lacking new "purposes" and "stages," is very likely to fall into "internal friction." What is internal friction? It's when everyone, in the limited space of Earth, constantly competes with each other, leading to "involution"! Think about it: when AI massively boosts productivity, excess capacity may in turn squeeze limited job opportunities, concentrating technological value, ultimately leading to vicious competition across all industries.

This forces us to consider a deeper question: "Is the purpose of life simply survival, or is it about living fully?"

With powerful tools like AI Agents, there's an opportunity for technological leaps, which could open up entirely new markets and directions!

If we are just fighting for limited jobs within the existing framework, that would be a great pity! It's time to set our sights further and wider. Therefore, from nations to each one of us, we must establish a "worldview" oriented towards the universe. Only in this way can society's goals "expand" and find greater meaning and a grander stage!

We must tell ourselves that we are not here to find an existing job, but to become designers of new stages! This new stage has long transcended Earth; it is the entire solar system! I hope that on our journey to becoming a genuine Type 1 Civilization, this path will be smooth and full of hope!

Evolution of Civilization Eras

The journey to Type 1 Civilization can be roughly divided into five eras: the Agricultural Era, the Industrial Era, the Information Era, the Agent Era, and the Solar System Era. When we reach the Solar System Era, we can truly be considered a Type 1 Civilization.

Here, I will analyze the main challenges of different eras:

🌱 Agricultural Era: To Do

• Humanity's most basic drive comes from "survival" and "labor."
• Emphasis on "what can be done," "what can be produced."
• Everything revolves around "food" and "labor."

🏭 Industrial Era: To Build

• The key is no longer just "doing," but "building scalable systems."
• Emphasis on processes, efficiency, standardization, mass replication.
• Factories, cities, national systems, and corporate management were born during this time.

🖥️ Information Era: To Know How

• Knowledge becomes the most important resource.
• Education, science, and technology become core values.
• Whoever knows how to do it has the upper hand.

🤖 Agent Era: To Decide

• Information is readily available, but "which choice to make" becomes a scarce ability.
• Judgment, selection, and combination will be the value of humans in this era.
• Everyone needs to be like a director; AI can quickly provide many possibilities for people to make judgments.

🌌 Solar System Era (Planetary Civilization): To Be

• The question is no longer just "what to do," but "who are we?"
• When "survival" is no longer the main problem, and science and technology are just basic conditions.
• Then "self-awareness and the choice of civilization" become key.

Currently, we are at the critical turning point from the "Information Era (To Know How)" to the "Agent Era (To Decide)."

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The Future Isn't About Job Loss, but a "Fundamental Shift in Work Patterns"

According to the "Future of Jobs Report 2025" published by the World Economic Forum (WEF) in January 2025, the global labor market is undergoing an unprecedented transformation. This report surveyed 55 economies, 22 industries, and over 1,000 companies (covering 14 million employees), predicting that by 2030, 92 million jobs will be displaced globally, but at the same time, 170 million new jobs will be created, a net increase of 78 million job opportunities.

If you want to read the full report, you can click here: 《Future of Jobs Report 2025》

📉 Jobs to be Displaced (Estimated 92 Million Reductions)

So, which jobs might be displaced? These declining positions actually share several obvious common characteristics: they are usually highly repetitive, standardizable, and have fixed processes. In short, they are jobs that are particularly easy for machines or automation technologies to learn. What kind of jobs are these?

• Data entry clerks and administrative assistants are very typical examples. As various automation tools become more widespread, the demand for these positions will certainly decrease significantly. Next are accountants and bookkeepers. Current AI and automated software handle financial data with much higher efficiency and fewer errors than manual labor.
• Also, cashiers and counter service staff that we encounter in daily life. Everyone has probably noticed, right? With the increasing number of self-checkout machines and mobile payments, these positions face very significant challenges.
• This, of course, also includes warehouse and logistics operators. If you imagine those incredibly advanced automated warehousing and distribution systems, once implemented, the reliance on human labor naturally decreases.
• Even cleaning and maintenance personnel are included. Look at how smart robot vacuum cleaners already are; in the future, as robotic cleaning equipment develops, it will likely replace some of the human labor demand.

📈 Jobs to be Added (Estimated 170 Million New Jobs)

So, what kind of new job opportunities will be created? You'll find that these future emerging positions are actually very diverse! They are not only related to the commonly heard fields of technology, data analytics, and artificial intelligence, but also heavily appear in areas that require unique human creativity, complex problem-solving abilities, deep emotional connections, and the ability to collaborate with AI. Simply put, these are jobs that are difficult for robots or AI to completely replace, truly requiring high-level human intelligence and various 'soft skills'. What are they specifically? Let's take a look:

• AI and machine learning specialists will certainly continue to experience explosive growth! Think about it, AI technology is being applied more and more widely, and in the future, the demand for professionals in this area will only increase.
• Next are data analysts and scientists. Businesses generate massive amounts of data every day. How to extract valuable insights from this data to help bosses make smarter decisions requires highly skilled professionals.
• And cybersecurity experts. As our digitalization increases, cybersecurity naturally becomes super important. Every company now prioritizes information security.
• Don't forget renewable energy engineers! The world is vigorously promoting green energy, so the demand for related technical talent is also rising, making it a very promising field.
• You might find it strange, but the demand for nursing and care professionals will also significantly increase! Why? Because global population aging is a major trend, and the demand for medical and care services will only increase, not decrease. These jobs require a great deal of empathy, delicate interpersonal interaction, and the ability to handle non-standardized situations, which are currently very difficult for AI to replace.
• Educators too! The education sector is also undergoing digital transformation, so there will naturally be a need for more teachers with new skills to educate the next generation on how to adapt to this rapidly changing world and how to cultivate future-ready skills. This type of work emphasizes guidance, inspiration, and character building, which AI also finds very challenging.
• Additionally, some jobs requiring high creativity, such as content creators (YouTubers, Podcasters), artists, designers, etc., while AI can assist in content generation, the ultimate style, philosophy, emotional connection, and storytelling ability still rely on humans.
• Also, community managers or interpersonal communication experts. In an information-saturated era, how to effectively build trust, manage communities, handle complex interpersonal relationships, and negotiate are all jobs highly dependent on human emotion and judgment.

You'll find that the new positions actually cover a broader range than we imagined, from hard skills to soft skills, from innovation to human care.

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Although the "Future of Jobs Report" shows a net increase of "12 million job vacancies" overall, this doesn't mean "everyone will have a stable job." This is because the structural disruption is massive—these new jobs are completely different from the old ones and require very different skill sets.

Imagine: you used to be a data entry clerk, but that job was completely replaced by AI. However, the new vacancies are "AI model trainers" or "data ethics consultants"—these are completely different skill sets! So the problem isn't that jobs are disappearing, but whether you can keep up with this transformation.

The future of work will be several times more diverse than it is now. Because with the assistance of AI Agents, the same position no longer needs as many people, but each person can do more things. In other words:

• Work more efficiently
• No longer limited to a single function
• But also need to better understand "what to choose, what to decide"

AI won't strip away our value; instead, it will amplify the truly valuable aspects of you—like judgment, creativity, and empathy.

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The Challenge of Moving Towards a Solar System Civilization

After the AI era, humanity will enter a larger phase: the exploration period of a solar system civilization. At this time, the world may be very unstable, many people will lose their way, desires will intensify, changes will accelerate, and politics and commerce will become more intense. As the saying goes: "Man's ambition rises higher than heaven, and he brings good and ill fortune upon himself."

If humanity only engages in internal struggles and involution, without looking at the bigger world (space exploration, establishing off-Earth civilizations), it may eventually lead to destruction.

Why is the transition from the "Information Age" to the "Agent Age" so crucial? Because the Information Age (To Know How) teaches skills; the Agent Age (To Decide) requires making choices and taking responsibility.

This is a turning point for civilization. Do we want to master the future? Do we want to break out of involution, anxiety, and internal friction to think about the overall direction of humanity? This is a multiple-choice question history has given us.

I recall learning software engineering in college and feeling a great sense of accomplishment writing code. But in the workplace, I found that most of the time was spent cleaning up messes: fixing bugs, technical debt, clearing messy data, handling compatibility, tuning parameters, adding tests, interfacing with SDKs/APIs... These trivial tasks were once engineers' daily routine. But in the future, these are precisely what AI Agents are best at! They can help us automate these tedious tasks, giving us more time to think and create.

Now is the critical moment for humanity to enter the "Agent Era." We need to ask ourselves a fundamental question again: What do humans live for?

If the answer is merely "for survival," then we should consider—do we want to be trapped in competition, overtime, and stress our entire lives? Or do we want to actively design our future stage? This stage should never be limited to Earth. We have the opportunity to truly embark on a journey to the solar system, moving towards a "Type 1 Civilization." And this path can only be traversed by using AI Agents as tools and guided by human subjectivity.

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Conclusion

"Don't be a slave to tools; be an architect designing civilization. Our stage is the entire universe." What do you think?