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I have spent 15+ years in building several tech projects and cultures – starting in Vietnam, sharpening my skills in Japan and Singapore, then spreading to the United States, Australia and Europe. Each stop taught me how different environmental system obstacles transform me into capacity: how to send products under pressure, build zero companies, increase talent pipelines and make teams lead teams through the toughest implementation challenges.
On the way, I laid the foundation for a joint venture across the domains.
This trip left me with a simple conviction: AI is basically changing how we make software, how we make companies and how to work on a new level of business innovation. The shift is so deep that non -tax founders, businessmen and SME owners have to review how they imagine products, platforms and changes. Or the right features on the wrong grounds are at risk of shipping. That is why I am sharing what I have now learned about the construction of AI first products and AI first companies.
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Software evolution over decades
In the last forty years, we have been going through clear visits to the software. Prior to the year 2000, the period of the PC and the operating system was defined by “software in a box”. You bought a CD, installed it on your personal computer and hoped it would easily work.
The updates were rarely, which often requires any other CD or manual patch, and the builders run on a simple model: a large release and trust that it will run on more machines. The Microsoft Office is a classic example of this model-consisting of itself, tied to the machine and stable to the next big refreshing.
In the early 2000s, the world moved to the cloud and mother -in -law – the software provided by the browser. Suddenly, the obstruction of the same device disappeared. You can log in anywhere and access your tools anytime. Gmail converted desktop email clients, sales force and shopkeepers into a large -scale business backbone and updates became permanent and invisible.
Builder mentality also changed: The challenge was no longer compatible with local machines, but designing system for mass scale, flexible infrastructure and frequent purchases. Release Multi -year bicycles slip weekly or even daily push, as the software turns into a living service rather than a fixed product.
We’re in an AI First Period
Now, we are entering which can only be described as the AI ​​first period-a world where the model itself becomes a new run time. Instead of clicking the buttons or typing in the form fields, we describe our goals in a simple language and intelligent agents withdraw planning steps, calling tools, and just withdrawing when needed.
The jump here is not just a convenience. This is a new explanation of the conversation. Examples of every day are already here: a support assistant that drafts a response for you or a finance co -coin that is affiliated with books.
Related: According to Open AI, how are people actually using Chat GPT
From clicks to conversion
In fact, what is happening under the hood is deep. We are moving towards clicks: Where yesterday’s software waited for our buttons to suppress, today’s systems can understand and translate the goals expressed in natural language.
We are moving from apps to agents: the software that not only sits useless but also actively plans, connects with CRM, ERPs or payment systems and returns the results with the audit trail. And we “work” from “it works, is safe and proves,” to lay in guardians, diagnostic matrix and rollback system, so AI not only performs but also directly and adapted.
Even the infrastructure itself is changing – from the Brett Force of major servers to intelligent placement, some AI operates in the cloud, while the other works close to the user for privacy and immediate response to other tasks.
The way for the founders is clear: moving from OS to the cloud as a model is not just another product cycle-this is a change of mindset. Thinking in tomorrow’s category, whether screens, clicks or tickets, mean that you will bolt the AI ​​on top of an old product.
Thinking in today’s category-unlocks the targets, agents, tools, guardians and proof-AI first products, and even more importantly, AI first companies. Shift differences because it directly has an impact on how organizations will run and where there will be profits and losses.
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Impact on non -technical founders
Perhaps most importantly, this moment is unique for non -technical founders and businessmen. For decades, building software needs deep technical skills. But in the first world, the knowledge of the domain becomes the real benefit. If you already know the facts of Freight, Healthcare Clinic, Food and Drinks, Construction or Retail Finance, you are in a better position to turn this skill into AI’s first operations.
Large businesses are also trying to adapt, but their size slows down them. This friction creates an opportunity. Even the administrative advisers are admitting that the Agent AI calls for a re -establishment of the change procedures. Little founders, the window is open: you can explain the results in simple language, make them wire on existing tools and maintain human surveillance where decisions are really important.
In the Digax Group, we created our company on the idea of ​​connecting Tech Talent Hub, AI Factory and Startup Studio to meet the needs of our region. This approach has reinforced everything from self -cleansing catalog system to multi -linguistic communication logistics agents.
The biggest challenge was not technology, but to help teams change their mentality – where change management and open communication code proved to be more important.
Pay attention to the effect
Another lesson: First of all. Not every work flu is benefited from AI. We lure the automation everywhere and resisted in the priority areas, where it can be the biggest difference, quality, quality or decision-making power. From there, what did we do. And finally, we learned to be automatic with intention. If the AI ​​increased the standard, accelerated things or improved the decisions, we left it. The discipline turned out to be the same as imagination.
That is why this period is important. If the 2000s were about the cloud first design, the 2020 and beyond AI are about the first thought. This is not about slapping new features in the upper part of the old software. This is about adopting a new building. Model is run time, language interface, agent services and LLMOPS production is the new discipline. The companies that make it internal will not just be able to ship faster – they will measure the quality, confidence and the cost of everything that is measuring up -time.
For non -technical founders, small business owners and real -world businessmen, the door is open. You can measure globally from the first day, have ten times the production capacity where it is mostly inconvenient, and has access to insights, which costs advisor level fees. For the first time in decades, the playground is bent towards people who understand the problem, not those who can only write the code.
I have spent 15+ years in building several tech projects and cultures – starting in Vietnam, sharpening my skills in Japan and Singapore, then spreading to the United States, Australia and Europe. Each stop taught me how different environmental system obstacles transform me into capacity: how to send products under pressure, build zero companies, increase talent pipelines and make teams lead teams through the toughest implementation challenges.
On the way, I laid the foundation for a joint venture across the domains.
This trip left me with a simple conviction: AI is basically changing how we make software, how we make companies and how to work on a new level of business innovation. The shift is so deep that non -tax founders, businessmen and SME owners have to review how they imagine products, platforms and changes. Or the right features on the wrong grounds are at risk of shipping. That is why I am sharing what I have now learned about the construction of AI first products and AI first companies.
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