9 AI Skills Everyone Must Master in 2026

[00:01] ahead of 99% of people who use artificial intelligence. I wanted to make the first issue of the year as useful as possible, so that I could give you the most valuable information, something you can take and do the most of what you

[00:15] planned in 2026. So this video is about nine AI skills that nine AI skills that , or wants to start working with AI should master. It's important to note that all of these

[00:27] skills I'm going to talk about are n't just plucked out of thin air, but rather based on specific trends and real-world forecasts for 2026, which were made by leading global artificial intelligence from the University of California, Berkeley, and the

[00:41] research company Gther. This is what Andriy Karpatyy and Andrew Ying talk about. There are trends that directly indicate which skills need to be developed. For example, organization, multimodal fluency, or context management. You will find out

[00:54] what these words are in this video. There are also trends that highlight areas where you can get the most out of your investment in the coming years if you get there early. So the plan for this video will be like this. I will name a

[01:07] specific trend or forecast for 2026 and talk about what skill in working with artificial intelligence needs to be developed in order to be one step ahead of 99% of people who use artificial intelligence. Let's go, let's begin. First

[01:21] forecast. In 2026, the demand for verifiability of AI results will increase sharply. Over the past year, many have been waiting for artificial intelligence to become noticeably more accurate, for models to become smarter, for hallucinations to become fewer, and for responses to become

[01:36] more reliable. A lot of work has been done on this, huge teams of developers continue to work on it. But expectations were not met. The AI ​​still lies regularly and still hallucinates regularly. And so far no one has figured out how to

[01:51] completely solve this problem. Therefore, in 2026, to work effectively with AI, to be in demand, you need to learn to reduce the number of hallucinations yourself, to make sure that even the current model makes fewer mistakes. Hence, the first and perhaps

[02:07] even the most important skill, at least for the next year, is the skill of managing context and sources. A little bit of knowledge about why people hallucinate in general. Because in most cases it relies on internal

[02:20] memory. His memory is the result of learning from huge amounts of text from the Internet. Because this array is chaotic, concepts that may be completely different often end up close together in the model's memory. Because of

[02:35] this, especially where data was sparse, AI could mix up facts and produce very strange or inaccurate results while trying to find some kind of average. Furthermore, even when a model uses internet searches herself

[02:49] , we still don't understand how deep she dug and why she chose these particular sources and not others. Therefore, it is much more effective to provide AI with context and sources yourself. In practice it will

[03:05] look like this. Instead of asking a question, tell me about the forecasts for 2026. You upload a PDF, article, or research transcript yourself and ask them to rely solely on that text for their answer. This is already

[03:22] context and source management. A very simple and effective technique is to end instructions like this. You can keep it for yourself. Answer based only on this source. If you are unsure or information is missing, say, "I don't

[03:36] know." Don't try to guess. For each main statement, add a confidence label: high, medium, or low. At the end, list everything you are not sure about or could not find. And a little practical advice:

[03:51] use text expanders for this. I talked about these and other AI techniques in this video, so be sure to watch it after this. Text expanders are programs that insert your ready-made template at your short command

[04:04] . Once you've set it up, it's very easy to write long, repeating blocks of prompts like these. By the way, one of these ways to reduce tools like Google's LM notebook , because in it you can

[04:17] collect your own dataset from your articles, audio, and other materials that you rely on. The AI ​​will then answer questions based solely on your documents and provide references to where it got each statement.

[04:31] first source. This is context management. And if you've already started working with Google's Gemini, you can now connect datasets from your LM notebook directly to the chat. Very convenient. That is,

[04:45] knowledge base there. First, you collect sources in the LM notebook, check them there , supplement them there, and then work with the text in the familiar chat with GN. It's just incredibly convenient, right? That is, you understand everything that you

[04:59] trust, everything that you like. For example, you write letting him come up with what a cool marketing post means, well, I'm talking about it now, yes, you load your notebook into the LM laptop, everything about

[05:14] marketing, for example, or everything about posts, I don't know, everything about YouTube covers, for example. And when you work with GMI, it will rely on this dataset and nothing else. Here's a real example of a dataset. By the way,

[05:27] to use the LM laptop, so you can also take a look at it. Naturally, all video are directly related to working with neural networks and AI services, and with different ones at that. And in many countries, unfortunately, they are unavailable, meaning they

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[06:36] delays, and sometimes even faster than without a VPN, as paradoxical as it may sound. This New Year, make sure you and your loved ones have fast and free internet. The link will be in the description. Next forecast. In 2026,

[06:49] people and companies will stop looking for one perfect neural network or one perfect service. It is now becoming clear that there is no single best model. You

[07:01] can't trust benchmarks blindly. One model may be very smart at certain tasks, but completely useless at others. I think you have experienced this yourself. Each neural network is strong in its own way. One is better at

[07:15] reasoning, another at writing texts, and the third is strong in coding. So, instead of searching for the ideal service for you, companies and people began to create their own personal systems, that is, combinations of the strengths of different models. And both at the

[07:30] company level and individually, everyone can use this principle. And this trend immediately reveals several skills that will be in high demand in 2026. And the first skill is creating an AI council. I liked this title.

[07:44] I highlighted it from Andrey Karpatov's project. He created a service where not just one model that thinks about it, but models from different companies think about it simultaneously.

[07:56] Then they each review each other's answers, and then one main model, the chairperson, combines this into a single report, and the answer is already more balanced and accurate. You can use this without this application,

[08:10] because the principle itself is important here. You give the same task not to one model, but to several at once. Then you compare the answers, see where they agree and where they diverge, and choose the best one for yourself. Again, you can

[08:24] ask one model to critique another's answer, or ask one model to compile a final version of the answer, taking into account different points of view. In this scheme, you as a person remain the main one and can choose the outcome in the competitive struggle

[08:37] of models. Your answers will be of much higher quality. the chances of missing something important are much lower. For example, I have now started doing the same. Now I immediately now started doing the same. Now I immediately

[08:51] works really well in conjunction, so I recommend looking into this. The next level and the next skill is orchestration, that is, the ability to connect instruments. This skill and term have already gained popularity in the West, which means that

[09:05] in the new year, in the Russian-speaking segment, you will see advertisements for a whole bunch of online courses where you will be taught orchestration and instrumentation. That 's why I'll tell you everything in advance for free. Please, this is not

[09:18] worth buying the course. No one can tell you which tool is right for you. This is what you need to understand. You must understand this only in practice. So, the main principle of orchestration that you have to learn is

[09:30] that you have to juggle instruments. This is what will speed up your work. The first thing you need to do is simply make a list of the repetitive actions that you do manually. Then break this list down into steps from the

[09:43] start of a specific task to the final result. Then determine which tool can help you with each of these steps. If you do n't know, you can go and experiment. So you've divided

[09:57] all your tasks, you've divided the steps, and now try to solve each step at once, simultaneously, using You will have to repeat this more than once, several times , but eventually you will see some patterns, which model copes better with which task. I will now

[10:10] explain it to you using an example of work, for example, with this video. We had to study forecasts and trends, plus add our personal experience and create a scenario. Then come up with a description, then come up with a title and covers. This is our

[10:23] work process. For primary research, we use GPT chat in different modes. For deep work with already found sources, use the LM laptop. We leave the text

[10:35] to the person. We do SEO optimization of the description through Gemini, and generate covers in NanoBana. And here it’s not really important which specific service you use, because they are designed for different tasks, and no one can

[10:50] tell you this better than you can find out for yourself. What matters here is how you connect them together. This is what orchestration is. Therefore, in 2026, what will be valued will not be a thorough knowledge of any one specific neural network, but

[11:03] specific neural network, but the ability to quickly assemble a working chain for a task. Accordingly, the next skill that follows from this is automation and agents. Because once you've developed and understood the

[11:16] orchestration principle, you can now create automations and AI agents for these steps and tasks, so you don't have to write and explain in the Prompt every time what you need to do. They searched for additional materials, connected services, and you developed your own

[11:31] , you understood which tool would be suitable for what, and you simply created an specific task. I will tell you the most important platforms for creating important platforms for creating AI agents or automation. We have

[11:44] you can create automations. More simple for beginners, for non-cores. Then we have N8N. It is more complex, but it is more AI agents. Then we have constructors like Minnichat. In it you

[11:59] can create bots for social networks. Well, you can search for something similar ManiChat, you can find some other platform for yourself. These are the three most basic platforms to study, simply because that's where you'll

[12:13] build automation, automate all the steps you've programs that cover these tools in detail. I periodically post training videos on YouTube. Watch them to get a deeper understanding of

[12:26] automation is and what agents are. But if you want to delve deeper into this and acquire a real skill, and not just create or repeat some template, then you can study our training. We create precisely

[12:39] professional training. These are multi-month programs where you master a particular skill from scratch to pro level . We currently have training for AI agents and AI stentors. We have training on automation and

[12:52] bots. You can read more in the bot. Well, in general, the ability to create automated processes with artificial intelligence is an absolute trend. And everyone will do this , even non-techies. I am a person

[13:04] delegate all of this later. I still needed to figure it out, become a pro at it, do it myself, so that I could then manage and give precise instructions on needed to be created. And if you master this skill, you will be head and shoulders

[13:19] above any of your competitors in almost any profession. You understand, right? you will immediately automate, you understand? Immediately create a digital employee, automate, and simply work more efficiently. That's the

[13:34] whole point. Our next prediction is that text will finally cease to be the primary language of communication with artificial intelligence. Until recently, text was our primary way of interacting with AI. Large language

[13:48] models, they read text and produced text. We have adapted to all of this over the past two years, and we have gotten used to it. But in the last year, we have added other formats, such as voice, image, and even video. Now we have

[14:03] generative interfaces, where II doesn't just respond to your request with text, but rather II doesn't just respond to your request with text, but rather it assembles the interface of an application that solves your problem. For example, like we have with Gemini 3. Therefore, in

[14:15] 2026, to work effectively with EI, you will need to be able to use all of these formats. I call this skill more like multimodal fluency. And it will consist of two parts, two directions. The first is the ability to

[14:28] provide information correctly. And here you need to understand which format is more advantageous to use for your task: text, image, audio or video. Let me explain now. For example, Gemini can now accept video and audio input.

[14:45] transcribes them well and analyzes videos frame by frame. Therefore, if you need, for example, to work with visuals, space, for example, it is much easier to simply write down a short room tour than to describe it all in long text. That

[15:00] is, you directly film the room on video and ask the GI to draw up, for example, a detailed plan of the room, and she will do this by looking at the video frame by frame. And then you can use nanoban to make a model of this room and add something to it.

[15:15] Then, in other tasks, on the contrary, it is easier to convey the idea in audio. There are a lot of subtleties, I think you have this too , that only come to light when you're talking about an idea or a task. I use this very often. For me,

[15:29] awakens when I speak, so I can just throw my five-minute thoughts into the chat, and it works with it. That is, I understand in what situations it is better for me to write in text, and in what situations it is better for me to speak.

[15:43] So, multimodal fluency is precisely about understanding which format will give you the best results and save you time. The second part of this skill is the ability to correctly deliver the result in the required format. This is the downside

[15:58] of multimodality. We've been living in a content reformatting mode for a long time now, but in 2026, this will become the basic norm. An audio message, for example, can now be much more effectively converted into a short text summary for colleagues. A

[16:11] complex idea can now be turned into an infographic, a diagram, or an AI podcast. This will make it easier for you, for example, to convey

[16:24] important to understand one thing: sometimes text is the worst format, even if the idea is very good. AI allows you to quickly translate meanings between formats. And those who know how to use this will work more clearly, quickly, and

[16:39] we have a really interesting idea, we make a podcast out of it, not [music] lyrics, and listen to how cool it will be perceived by the audience. When I need to explain to the editor how I want the graphics to look, I don't

[16:54] use text or audio anymore, but I simply use Nanabanana to draw him infographics. I draw him a diagram of how the editing of a particular frame should look . And that's how it works. Next forecast. Wipe coding will become widespread, and

[17:09] it will become even easier and more understandable for a mass audience. This means that people with ideas will have even more opportunities to implement these ideas on their own, without programmers, without teams and without long development. Of course, I'm

[17:23] not talking about large AI products, like entire applications or social networks. I'm talking about more Microsoft. These are forms, trackers, bots, mini-services, and internal tools for a specific task. Even these mini-tasks

[17:37] previously required only developers, only people with a technical education. And now you can put it together in an evening with artificial intelligence, sometimes even in one prompt. For those who have n't delved into this yet,

[17:50] n't delved into this yet, vibe is the process of creating digital tools, or products, through dialogue with E. In other words, you literally describe to AI what you want to create, and AI helps turn it into a working

[18:02] Try it if you haven't done it, for example with Gemini 3, for example, I made a card generator for social networks. Or earlier we did marркеетй with agents . Wipe coding isn't my specialty, but it's

[18:16] gradually becoming part of my tasks and helping me out. And this skill, guys, is worth developing. And this can be done in stages. That is, first start with the simplest possible environment, where you simply formulate an idea, and the service builds a prototype for you, for example,

[18:30] Lovable. This service received an AI Award for being the most accessible and awards ceremony. I think you will definitely find many useful services for yourself . So, then you can move on to more flexible tools with

[18:45] greater functionality. For example, you can then go to Google AI Studio, a free platform, and directly through a dialogue with GMI, assemble, for example, a tool for your task: a tracker of some kind, a counter, or

[18:58] any task or mini-task that I need to show or do, I go there and create mini-applications like these. But then, after this, you can move on to more advanced tools like the cursor, like

[19:12] Cl. Here you will each have your own track and your own depth of immersion. Some of you will be satisfied with simple prototypes, some will go deeper, and some programming in general after this. But, you know, if you want to move forward, you're going to need to

[19:27] learn this skill, wipecoding. And you don't have to buy study this on your own, because vibecoding courses, in my opinion, are not universal courses. That is, they will still teach you something specific in the wipe code

[19:40] . Wycoding is essentially just describing to the AI ​​what you need. All. So you're literally writing: "Create me a landing page in blue," with a task tracker in the middle where I 'll enter my task. As soon as I do it

[19:56] , it will be able to move away, and I won’t know, confetti will be pouring out there . Vibecoding is literally describing to a neural network the entire functionality of a particular application, what you want to create. Because of you, no one will be able to write

[20:08] this text correctly. The logic is simply to learn to present your thoughts in a artificial intelligence. Now one more forecast. There will be so much content and any other

[20:20] forecast. There will be so much content and any other results of AI work that human taste will become decisive . In 2026, there will be radically more content. AI will generate texts, visuals, and videos with virtually no

[20:37] limitations, quickly, cheaply, and in huge volumes. But at the same time, the gap between good and bad AI-generated content will become much wider. There will be more bad things, and more average things too. But truly strong results will

[20:54] stand out especially sharply. And what will be valuable will not be the ability to generate something, because everyone will be able to do that, but the ability to understand what from this generated information is truly worth paying attention to. AI doesn't have a sense of taste, it doesn't

[21:10] sense proportion, it doesn't understand why one idea catches on and another doesn't. He doesn't know how to evaluate results the way we humans do. So the key

[21:22] skill in this will be evaluating and criticizing the result. This is a skill about the ability to choose and make decisions. Because in a world where everyone can create,

[21:34] value will shift to those who know how to select, who know how to cut and enhance, on the contrary, the result using their own taste, their own critical thinking and their instinct and, perhaps, even intuition. And it is precisely

[21:49] human taste, a sense of quality, appropriateness, and meaning that in 2026 will become something that AI cannot yet replace. And in general, in fact, I think that it will not replace it, well, not at all. Simply because a person needs a person. In

[22:05] this regard, it is, of course, very difficult to give you any specific tools and techniques, but the only thing I can say for sure that each of us needs to improve is our visual acuity. But it’s not just opening Pinterest or just

[22:18] going to museums and looking, but rather thoughtful observation. For example, when you go to a museum, take a guide with you so that he can explain why this painting is worth 400 million and that one is not. My hobby. Well, because I just really

[22:32] love design. I love watching videos from designers with detailed analyses. Why did he combine these two textures? Why exactly these colors? Why this particular arrangement? Many. Why? Why? Why is this why

[22:46] it will make you aware of this or that decision and develop taste accordingly? I really like where we are going, where we are developing, because we had this, then we lost it, and now

[23:01] we will be forced to return to it from AI . To return to the fact that, in principle, well, in my opinion, one of the characteristics of a human being is pleasure, it is the creation of art. There is art in everything in engineering

[23:15] too. That is, this is such a conscious choice, this is deep work. When routine is automated by AI, the most enjoyable things are left to the person. Next forecast. AI-involved fraud will rise sharply in 2026 .

[23:32] Phishing, fake calls, emails from relatives or colleagues, video tutorials on Telegram, or audio that is indistinguishable from the real thing. And now I have made fraud personalized, mass-produced, and frighteningly effective. There are

[23:48] already research results showing that when a person writes a phishing email, approximately one in ten recipients opens it. And when the same letter is written by AI, five out of ten people open it. The difference is

[24:02] huge. So in 2026, a skill that is difficult to measure, but without which it will be simply impossible to survive, will become critically important. in the new reality. Critical thinking

[24:14] reality. Critical thinking and digital awareness skills. That is, here, unfortunately, there are no specific protection mechanisms yet, no absolutely effective methods for protecting oneself from scammers. But the

[24:26] main tool of protection here will be your awareness, when you know what he is capable of, and with a greater degree of probability you will be able to catch the to deceive you. That is, ask yourself

[24:38] questions: "Why did this email come now? Why am I being asked to act urgently? Why is the tone a little different than usual? Why? Why? Why? When there are any suspicions, even the slightest, you can

[24:51] ask the task again, clarify an alternative method of communication. This will be alternative method of communication. This will be your critical thinking in the AI ​​era. And the last prediction. In 2026, AI-free barriers to verification and testing will appear.

[25:06] What am I talking about now? Just recently, I read about cases where a candidate was interviewed via video call. So, suddenly HR says: "Close your eyes and answer the question." And she asks a question precisely on the topic of the position for which the

[25:19] person is applying. Why did she do this ? Because now there are programs that catch what a person says on the fly , and immediately the GPT chat or any other model gives an answer. The person looks at the screen, reads and

[25:31] answers as if from himself. So, these kinds of checks, they are appearing more these kinds of checks, they are appearing more and more often, and for good reason. Companies also look On abilities, on personal prospects. Now more and more

[25:43] research shows that when we delegate too much to AI, our cognitive skills naturally decline. We form thoughts worse, we hold complex logic less often in our heads. What to do about this? Of course,

[25:56] abandoning AI is not an option, but we will need to maintain our thinking muscles. And the key skill in 2026 and all subsequent years is the ability to consciously

[26:08] alternate work modes. Do some tasks with AI for the sake of speed and scale of efficiency, and some completely independently, so as not to lose car. If you only drive a car, your

[26:23] legs will atrophy. If you only walk, you will be slow. Therefore, you need to alternate depending on the situation. Therefore, it is very important to regularly write texts without prompts, independently search for arguments,

[26:38] analyze information manually, and form conclusions before showing them to AI. I believe that this is the most important skill that we must not forget and which we need to critically develop, that is, to remain HMO sapien

[26:50] with a thinking person. And so, all these nine skills are A foundation right now and for the entire coming year. If you'd like to explore any of the skills in more detail, please let me know in the comments or let me know how you'd

[27:04] add to the list I've created . We truly live in amazing times. This is a time of enormous change, both within us and outside of us. What a wonderful year, we are wonderful. Let's remain

[27:17] we are wonderful. Let's remain human. I wish you a wonderful 2026. Thanks for watching. There's lots to come. Happy New Year! And have a great start to this year. Bye.