Artykuł Financial consequences for boards amidst rising cybersecurity threats pochodzi z serwisu Inero Software - Software Consulting.

The development of broadly understood artificial intelligence is gaining momentum. This is evidenced by the widespread interest in this topic and an increasing number of media articles and publications. What draws particular attention are the data illustrating how much financial resources are allocated to investments in semiconductor technologies, i.e., the computational capabilities and memory of new AI data centers. Everything indicates that this development will be very dynamic in the coming years.

Reports such as “The Future of Jobs Report 2020″ prepared by the World Economic Forum and research conducted by the consulting firm McKinsey & Company highlight the dynamic changes in the job market that will take place in the coming years. Both sources agree that we will witness significant transformations in the types of professions and responsibilities, resulting from technological progress, automation, and changing economic and social needs.

In the article ” Most of 2030’s Jobs Haven’t Been Invented Yet” we can read:

“The IFTF, a nonprofit that seeks to identify emerging trends and their impacts on global society, forecasts that many of the tasks and duties of the jobs that today’s young people will hold in 2030 don’t exist right now.”

source:  https://www.voanews.com/a/most-of-2030-s-jobs-haven-t-been-invented-yet/4778002.html

From the management perspective, this presents a substantial challenge. The way relationships and duties among employees of different departments evolve will significantly change the operation of many organizations. Identifying these areas and any potential consequences arising from the AI revolution will be crucial for success in the coming years.

“In my opinion, understanding the capabilities that new technologies offer and assessing how they can improve a given organization will be a key managerial skill in the coming decade”- emphasizes the CEO of Inero Software, Andrzej Chybicki.

He points out two ways for businesses to develop their technological awareness in the area of AI:

The first is to explore products or services available on the market that can be applied as ready-made solutions. The decision to implement them will depend on the extent to which these solutions can be tailored to specific processes that require optimization and automation. However, it’s important to be aware that such software is delivered in a certain “bulk” that needs to not only be implemented but also integrated with internal organizational processes to effectively cooperate with the newly implemented product.

The alternative is creating in-house AI-based solutions, which large companies are already opting for. This includes, for example, designing their own language models tailored to the individual needs and requirements of a particular enterprise. These are usually multi-million dollar projects, but some can be completed within a smaller budget.

One of the global brands that decided to create its own LLM model is Amazon. The purpose of the “Rufus” model is to support potential customers at every stage of the purchasing path. Its implementation aims to assist users and optimize the order placement process.

“At Inero, we apply a product-service approach. Having knowledge on how to solve certain problems, using our proprietary systems like DocQuality or DeliverM8 – Freight Matching Platform, we aim to present a certain solution template and its potential. Then, we tailor it to the specific needs and processes carried out within the client company’s structure, rather than the other way around. Our products provide a template of possibilities that new technologies offer.” – highlights Andrzej Chybicki.

This solution combines the good features of a product approach with the flexibility of a service approach, while the cost is more affordable. For example, the DocsQuality application utilizes machine-learning techniques for document categorization and the recognition of illegible sections of files. This program can be easily and quickly integrated with a client’s internal infrastructure, optimizing the document circulation process by detecting problematic documents.

In summary, the development of artificial intelligence in business management opens up space for innovation. The challenges associated with adopting new technologies require a strategic approach, both in the context of implementing ready-made solutions and creating internal AI systems. Success in the coming decade will depend on managerial abilities to understand and utilize technological potential, as well as skills in managing a changing team that will require the implementation of new tools, tailored to new tasks.

Artykuł The possibilities brought by the development and popularization of AI in business management pochodzi z serwisu Inero Software - Software Consulting.

GitHub anticipates that in the coming years, 80% of the world’s code will be generated by AI [1]. Although it is difficult to find exact information on the number of sold GitHub Copilot licenses, it is undeniable that we are observing a change in the way organizations and programmers themselves create new IT solutions. At Inero, we are working on many projects simultaneously, so we are eager to test the latest solutions that are designed to optimize teamwork, deliver solutions faster and better.

In this article, we will talk about our experiences with GitHub Copilot.

What is GitHub Copilot?

GitHub Copilot is a tool designed for programmers, utilizing an advanced language model (known as LLM – Large Language Model) tailored for the analysis and understanding of source codes. A set of appropriate plugins and tools, allows for the optimization of the software development process, providing programmers with automatic coding hints and completions, suggestions, syntax analysis, and even generating documentation. Developed by Microsoft, the tool is based on artificial intelligence and was created to enhance the productivity of programmers and improve the quality of the source code.

Further than Closer, Slowly Towards the Goal

The use of GitHub Copilot in most cases allows us to speed up programming work, importantly, not only in creating the code itself but also in more tedious tasks. For example, since we started testing GitHub Copilot in our team, we have visited StackOverflow much less frequently. Copilot accelerates work when our programmers need to generate relatively simple and repetitive code that can be easily assessed as correct at first glance.

• • Copilot greatly speeds up work with regular expressions and certainly optimizes the time for writing repetitive code.
  • Copilot is also an effective tool for generating code documentation, essentially being able to almost entirely do it for us. Of course, the generated content always needs to be verified, but we haven’t encountered significant errors. Usually, we add more details to the result, however, in many cases Copilot is sufficient. Documenting, for example, a single block of code, when it’s quite extensive, can take approximately even a minute. With Copilot, this can be done in a few, up to several seconds, depending on whether we need to elaborate on the content.
  • From the perspective of experienced programmers, the use of this solution can be described as an advanced Intellisense working in Line-By-Line mode. The programmer, starting to create a block of code, further uses Copilot’s suggestions. In such a case, the verification is immediate and if something is wrong, we correct it ourselves right away. When Copilot suggests a larger block of code, e.g., 10-15 lines, then analyzing whether this code does exactly what it should, can take more time than writing it independently. Especially since among these 15 lines, 14 might be correct, but one is erroneous and needs to be identified.
  • From the perspective of a less experienced programmers, the reception of this solution may be different. Writing code takes them more time than it does for an experienced developers, so Copilot seems helpful. However, during the analysis of code from Copilot, the user might not notice at all if something is amiss – the problem might only be detected during a code review conducted by a more experienced person.
  • After some time, we get used to Copilot sending us suggestions, so it’s necessary to learn how to work with this tool. Initially, these suggestions can disrupt the rhythm of normal line-by-line code writing. Instead of continuing to write, we stop to read the proposed suggestions. However, in the plugin’s configuration, it’s possible to disable continuous prompting and leave only key shortcut-based prompting – here the decision depends on the programmer, who can choose the degree of “support” that suits them best.
  • When we work on more complicated functionalities, for example, using a new library, Copilot can guide us in some way. Its suggestions in such cases can be accurate and even if they are not fully correct, they allow for a quicker understanding of how to reference the library, which otherwise would require analyzing the documentation.

Comment from the CEO of Inero Software

Andrzej Chybicki: Measuring the effectiveness of using Copilot from a management perspective is difficult – we don’t have objective indicators telling us whether and to what extent the investment in the license has shortened the time spent on the software projects we are entrusted with. That’s the first point. Secondly, some clients express concerns about the security of code analyzed by AI, especially in projects related to cybersecurity or involving sensitive data processing. Hence, we encounter situations where using Copilot is not advisable.

What advantages and disadvantages have we noticed?

Analyzing the experiences of our team, we can identify the pros and cons of using GitHub Copilot.

Will we continue to use GitHub Copilot at Inero? Definitely yes.

The use of GitHub Copilot in daily work brings many benefits. However, it’s important not to lose vigilance and not to fully rely on its suggestions. It’s crucial to continuously monitor the code prepared with this tool. The development of the technology, which Microsoft is working on, will surely bring many updates and improvements in the coming months.

[1] https://github.blog/2023-02-14-github-copilot-for-business-is-now-available/

Artykuł GitHub Copilot – review of pros and cons in a programmer’s work pochodzi z serwisu Inero Software - Software Consulting.

Experts predict that the market for software utilizing artificial intelligence (AI) to automate tasks and generate content in response to user commands will nearly quadruple by the year 2027. How can you benefit from this growth and prepare your team for new challenges and projects? CEO of Inero Software, Andrzej Chybicki, has shared his extensive experience and observations. In the following interview, he discusses how to manage remote teams in the IT services market and whether he foresees the advent of “teams of the future”.

Marta Kuprasz: I would like to ask you, as an experienced leader of a team of developers, how do you organize the work of distributed teams that are working on several projects? Additionally, I’m curious about your perspective on whether there’s a crisis in the IT services market and whether significant changes are on the horizon. To start from the beginning: For six years, you and Waldemar Korłub have been building Inero Software. During this time, you have refined processes related to managing a team of programmers. How do you approach the topic of implementing a new project and dividing tasks?

Andrzej Chybicki: The pandemic has changed the approach to remote work. What was previously rarely used has become fashionable and acceptable to both sides. Both employees and we – employers have noticed many advantages of this solution, such as lower labor costs, convenience, access to a larger pool of specialists, and time savings. There are also, of course, disadvantages. After a few years of such cooperation, we see that it is definitely more difficult to build interpersonal relationships when there is a lack of a common office, conversations, and meetings. The situation has made it possible for employees to lose the sense that they are part of a team, that they are building something together. We decided to create a process and culture, the combination of which helped us build a good framework for cooperation between the parties. We know that conversations are not only an exchange of information but also relationships, which is why we included regular project meetings in our work schedule. These are sometimes tedious but necessary processes of code quality verification, meetings monitoring progress, planning that takes into account the needs of our clients. During these meetings, we discuss what we expect from the team, while also collecting feedback from our programmers. I believe that a clear definition of responsibilities is more important than ongoing micromanagement. It is key that everyone knows how their actions affect the entire project. Awareness of these issues is extremely important.

“We decided to create a process and culture, the combination of which helped us build a good framework for cooperation between the parties. “

It’s also essential to set clear, realistic goals for a given project, which are delegated to individual teams or people. The team must be aware of how to implement a given idea and who is responsible for each area. Transparency in communication is, in my opinion, very important, especially among young people working remotely. Importantly, it should work both ways, i.e., we make our programmers aware that they also need to clearly communicate problems, delays, and errors, that occur in every project.

MK: What tools do you use for work planning and task assignment?

AC: In this, tools like Jira and GitLab help, but it must be remembered that they do not create the quality of services – that is our task. In long-term cooperation with a client, regularity and a developed action scheme are key. For several years now, methodologies such as Scrum and Agile have been widely used, which give technology teams the ability to work in a structured, yet appropriately flexible formula. They can define business needs and translate them into specific actions that are then implemented at the client’s site. However, I believe that entrusting project management to someone who only knows methodologies is a mistake. At Inero, we assume that managing a technology project is a skill, but knowledge of the domain to which the implementation pertains is also necessary. We know our weaknesses and strengths, so it is natural that we more often undertake projects in which we have the knowledge, in which we have access to industry experts because very often this purely theoretical knowledge is not enough. We focus on solutions whose applications we understand, such as logistics or the digital health industry.

“At Inero, we assume that managing a technology project is a skill, but knowledge of the domain to which the implementation pertains is also necessary.”

MK: So, how do you assemble a team of specialists in such a way that they complement each other at every stage of the project?

AC: Remember that a team consists of people with different skills, experiences, and processes they are already trained in. That’s why it’s so important to set clear, realistic goals for a given project, which are then transferred to individual team members. Everyone must be aware of how to implement a given idea and who is responsible for which area.

And probably most importantly: When we have a balanced team, meaning there are younger people who make mistakes, who may not always be able to handle all tasks, project management plays a crucial role. The team leader must catch these things and assign subsequent tasks that are still on the edge of possibility because they are an opportunity for further learning. However, it is essential not to have a tendency to find fault when something doesn’t work. We don’t forcibly look for problems. We should focus on the solution that will allow us to avoid a similar mistake next time. It is our role to motivate employees. By giving a challenging task, we want to get to know the new employee, his capabilities, and find out how he reacts to being confronted with a problem that may exceed his abilities. It’s better to understand his approach to problem-solving than to solve the problem itself. See if he communicates the difficulties he encounters and how he copes in a situation where he doesn’t know what to do.

“By giving a challenging task, we want to get to know the new employee, his capabilities, and find out how he reacts to being confronted with a problem that may exceed his abilities. “

I would like to add one more note here. There is something that can be called cognitive bias. Young programmers often want to prove themselves in projects, they are ambitious, they want to achieve success as quickly as possible. This is understandable. However, I sometimes see that they take on too many tasks and, as a result, find it hard to meet deadlines. We must take this into account when planning. In summary, when planning a team’s work, we must look at it as a whole, being aware that this is something that is supposed to function for a long time, without forgetting about the employees.

MK: Do you take employee turnover into account when planning a project?

AC: As a technology company, Inero provides value by offering structured and comprehensive software development services. When we establish a collaboration, we always think of it as a long-term relationship. In such a time frame, team turnover is natural, both on our side and on the client’s side. When we start a project, we assume that turnover will occur, so from the beginning, we strive to build a knowledge base for the project – a collection of experiences, facts, documents, multimedia, procedures, and information. We often use tools like GitLab (Wiki section) or Jira for this purpose. We record important data there, which will be necessary for a new team member to smoothly transition into the project.

“We have learned to automate repeatable procedures, and this applies to integrating new employees into the team.”

We have learned to automate repeatable procedures, and this applies to integrating new employees into the team, whether it’s front-end developers, back-end developers, cybersecurity matters, or others. For example, it includes a database of ready-made software solutions such as project templates or sample solutions. When integrating new team members, we assign them the task of analyzing and modifying these solutions in their first weeks of work. This is not so much to bring business value, but to teach them how we design solutions, how we solve specific technological problems, and how we approach problem analysis. We care about having an efficient way of transferring knowledge within the team. This translates into the quality and cost of our services.

MK: Recently, we have seen a growing interest in the topic of artificial intelligence. It influences many fields. Is this also visible in the industry in which Inero operates? Will “teams of the future” emerge soon?

AC: Undoubtedly, what has happened in the field of AI over the last 2-3 years, especially when OpenAI launched its new product, followed by Google’s Palm system and solutions available at HuggingFace, carries immense potential and can change the way new solutions are developed. We are closely monitoring how Copilot works. We use it in selected internal projects where we have no doubts related to SLA (Service Level Agreement), copyright, and code analysis.

” We are closely monitoring how Copilot works. We use it in selected internal projects where we have no doubts related to SLA, copyright, and code analysis.”

For sure, tasks related to the use of artificial intelligence already constitute a significant part of the projects carried out by our team – I would even say that currently, it’s more than half of all our work. The biggest challenge associated with AI is the ability to quickly adapt to changes and understand trends in this highly dynamic market. Those who adapt quickly will undoubtedly gain a lot, especially in areas supporting routine tasks, such as back-office operations, data analysis, predictive analysis, the use of conversational bots, and knowledge analysis (documents, contracts, emails, etc.). These are the areas of business activities that, in our opinion, have the greatest potential for transformation in the coming years. In the context of these projects, we see Inero not only as a team of developers but also as advisors. We try to identify trends, present conclusions, and communicate them to our clients and partners, indicating what deserves special attention in the coming months and years in the context of their business needs or development plans. We share our insights, which we believe will be applicable in a year, two, or five years.

MK: Have you noticed that there’s a crisis in the IT services market? How do you perceive what’s happening?

AC: For those who have recently become interested in software development, the situation where developers are not in high demand and don’t have a queue of orders may seem shocking. However, the years 2010-2015 were similar. Back then, the main advantage of programmers from our region was relatively low rates (compared to those in the USA or DACH countries). As a result of market changes post-COVID, the globalization of IT, and the convergence of salaries, the rates of our programmers are no longer as attractive to partners from the West. Therefore, we need to think differently about the value we want to deliver. For example, at Inero, we offer a product-service bundle where, on one hand, we provide services for our programmers, but on the other, we also offer ready-made logistics products that are part of a comprehensive IT offer. Additionally, we offer the entire process of creating IT solutions in the BOT model, not just our programmers on an hourly basis. In other words, the market is seeking balance after the turbulent years of 2021-2023 – it’s necessary to create new values and offer them.

Should you have any proposals or concepts you’d like to discuss, please feel free to reach out to me at your earliest convenience. I am very interested in exploring potential opportunities together.

Andrzej Chybicki, PhD Eng.
CEO, Inero Software Sp. z o. o.
andy@inero-software.com

Artykuł Andrzej Chybicki: The use of Artificial Intelligence already constitutes a significant part of the projects carried out by our team pochodzi z serwisu Inero Software - Software Consulting.