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What To Consider When Choosing Languages For Developing SaaS Products

17/11/2022

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Over time, several programming languages have emerged as reliable tools that developers can use to bring software ideas to life. However, software end-users simply want a product that excels at solving the problem at hand. They don’t care that much about the ingredients and recipe behind it.

Nevertheless, it’s extremely crucial to choose the right programming language when developing SaaS products. Making the wrong choice can lengthen the development lifecycle, produce a sub-par app and cost you even more money post-release as you try to fix several issues.

With that in mind, let’s discuss the major factors to consider when choosing a programming language for developing a SaaS product:

User-friendliness

Even though software creation is mainly done by those with above-average tech-savviness, technology is supposed to make things easier for everyone. So if a programming language requires convoluted syntax spanning several lines just to create a basic instruction, the code will get clunky quickly. This makes it hard to follow, especially for newcomers who join the team while the project is already underway.

And don’t forget that it will also be harder to document. Honestly, many languages can do much of what Python does, but Python remains a favorite for many developers due to its user-friendliness.

This language tries to make coding resemble writing actual English commands as much as possible. User-friendliness also extends to functionality like code templates and the extent to which a language simplifies code reuse.

Ecosystem

The first part of the ecosystem to consider is supporting tools. Consider the variety of libraries you can hook up to the language you’re using. Besides the libraries, there are documentation tools, automation tools, testing and quality assurance tools, and office/team productivity tools.

The more tools a language can work with, the easier it is to take a piece of your work and run it through as many processes in your workflow, bringing it to readiness in the shortest time possible. In addition, strong integration capabilities also simplify intra-team and inter-team collaboration. For example, error detection, logging and subsequent communication happen more fluidly.

The second part of the ecosystem to evaluate is the community. Find out how large and active the forums related to certain programming languages are. Communities encourage knowledge sharing, which helps you solve problems faster and at a lower cost while also opening your mind to new ingenious approaches that you can apply beyond an immediate challenge.

Ecosystem

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This is where open-source languages like JavaScript and Python beat the competition. According to Statista, JavaScript’s community size reached 13.8 million developers by the end of 2021, while Python came in second with 10.1 million developers.

Delivery Platform and Software Elements

You need to ask yourself two critical questions when choosing a programming language for developing a SaaS product. One is, “On what platform/OS will the final product run?” For example, are you developing a product for Windows only, or do you want to cater to the Mac crowd too?

The same goes for mobile, “Are you building for Android, iOS or both?” This question is particularly crucial because even though many frameworks can be used to develop cross-platform apps, such as React Native, Flutter or Xamarin, others stand out when developing apps for a specific platform.

For instance, many developers find Swift to be one of the best options for developing iOS apps, and also like Kotlin for Android app development. Unfortunately, there’ll always be trade-offs regardless of the approach you take.

If you go with a more universal cross-platform language, you’ll probably save money and release faster, but the product may not fully maximize one OS’s capabilities, especially when it comes to OS-specific APIs or performance-intensive processes.

Furthermore, you may also have to spend some extra time fiddling with interpreters and libraries. But if you go the native route with an option highly geared toward a specific platform, you’ll likely produce something that excels on that platform. Sadly, you may incur higher development costs and work slower.

Secondly, it also helps to consider which aspects you’ll focus on for your minimum viable product and other early iterations. For example, if your UX goals require a concerted effort on back-end development with a super lean front-end, you can start out with a language that is superb for back-end work and adequate for your simpler front-end goals.

As you enhance the front end further down the road, you can spend more time exploring the valuable capabilities that differentiate Elm, TypeScript, CSS, HTML and other tools.

Human Resources

This factor may seem like one you have to deal with after you make a choice, but it’s worth keeping an eye on from the get-go. For starters, some languages are newer and have fewer developers with high proficiency levels, which often means higher pay demands.

Human Resources

Photo by Annie Spratt on Unsplash

But then again, because some languages are more widely used, even the developers with preliminary knowledge have jobs most of the time. Consequently, the salary ranges for developers using languages like Python and Java remain pretty high.

The trickier bit comes in when you intend to use multiple languages but you want to moderate the developer expenditure. Finding developers who are sufficiently skilled in the specific combination of languages you want to use might be harder. And if you do, you’ll probably need them more than they need you, and they’ll know it, so they won’t hesitate to charge you highly.

Wrapping Up

Ultimately, the question of how to choose the right programming language remains a complex one. Technology constantly evolves, and many tools roll out new amazing functionality faster than you can blink. Moreover, some entirely new tools come onto the scene every now and then.

So whatever you do, ensure that you have clear goals regarding the quality of the SaaS product you want to deliver and avoid shortcuts since they’ll probably cost you more later.

Luckily, a professional team like SupremeTech can relieve you of the burden of which programming language to choose. You can contact us for a free consultation on the scope of software development solutions we provide.

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Instead of seeing it as an obstacle, the team saw great potential in this topic: “It’s actually very close to what SupremeTech does,” one member shared. “Tourism and service coordination are among the industries where our clients face similar pain points. If developed further, this could even become a real product for the company”. For most teams, tackling something this wide in just 24 hours would be overwhelming. But for Người Việc, it became the perfect opportunity to combine business logic, agile thinking, and AI-assisted development into a single solution. Dũng, one of the front-end engineers shared: “We didn’t see it as just a travel problem. It’s a coordination problem that every company faces because of too many people, too little time, and too many things to track.” The Idea: Transforming Tourism Coordination with AI Manual planning and coordination often create time-consuming processes, lack of feedback, and fragmented communication across travel agencies, corporate HR departments, and trip participants. To solve this, Người Việc envisioned an end-to-end platform that connects all stakeholders, from travel agencies and corporate planners to event organizers and trip participants.The system enables users to: Create and customize travel itinerariesConnect directly with travel agencies through a marketplace modelTrack schedules via QR codeProvide instant feedback during the trip. In short, it bridges the gap between demand and supply in hospitality, creating a more transparent, interactive, and seamless travel experience. The Process: From Brainstorming to AI-Assisted Development What set Người Việc apart was their strategic mindset before touching a single line of code. Instead of rushing to use AI tools right-away, the team began with a face-to-face brainstorming session, mapping out what a real group trip looks like from start to finish: from planning and agency communication to real-time updates and user feedback. To validate their ideas, they even called friends working in hospitality to understand pain points from the field such as: how agencies handle client requests, where information gets lost, and what travelers actually expect. Only after this discovery phase, the team moved into design and development. They first created clear user stories and workflows on their own, then applied story-based prompting by feeding those stories into ChatGPT and Copilot to generate database schemas, API endpoints, and code snippets. This structured use of AI helped them align technical output with business logic and speed up development. Their approach became a model of how AI-assisted development and agile methodology can complement each other, keeping logic clear while boosting speed. Their mantra throughout the process was simple yet powerful: Think first, then use AI smartly. This mindset kept their workflow focused, turning AI into a productivity multiplier instead of a shortcut, and became a highlight in their AI hackathon journey.Without a QC member, the team stayed flexible and shared responsibilities across roles. Each member could take on multiple tasks when needed, but they still kept a clear structure in how they worked. The PTL and BA stepped in as real users, testing features and giving feedback from a user’s point of view. After defining their user roles and business logic, Team Người Việc translated their ideas into a working prototype. Their platform acts as a bridge between corporate planners and travel agencies, creating a space where requests, itineraries, and feedback flow seamlessly in real time. The system’s core features included: Trip creation and customization: HR or operation teams can build itineraries, adjust timelines, and submit requests tailored to their needs.Agency collaboration: Travel agencies receive those requests, update details, and negotiate directly through the platform, no more back-and-forth emails or lost messages.Participant tracking: Each trip generates a public QR code, allowing members to follow updates, view schedules, and send instant feedback during the journey.Transparency and engagement: The platform closes the communication loop, giving every stakeholder a clearer view of the process. With these key flows completed, the team delivered a functional MVP, a product with clean logic, smooth handoffs between roles, and enough structure to be reused or scaled for other industries. Modern Tech Stack Built for AI-Driven Innovation To bring their concept to life within 24 hours, Team Người Việc designed a tech stack that was modern, lightweight, and AI-friendly. Every layer from frontend to deployment was chosen to balance speed, scalability, and maintainability. Frontend Layer: Fast and Built for Clarity The team developed the user interface using Next.js 15 to handle both page rendering and API routes. Combined with TypeScript, it provided type safety and consistency across all modules, reducing human errors in the rush of development. For styling and components, they used Tailwind CSS and shadcn/ui, which allowed them to quickly create a clean, responsive design without spending time reinventing basic UI elements. Despite the tight schedule, the frontend still delivered a cohesive experience from trip creation to QR-based tracking, proving that with the right stack, agility doesn’t mean sacrificing structure. Backend Layer: Structured Logic and Data Flow Behind the interface, the team used Prisma ORM to manage the database layer. Its schema-first approach, paired with TypeScript integration, helped them maintain data consistency while iterating rapidly. The backend services were also written in Next.js, utilizing server functions to keep everything unified and easy to deploy. This setup gave the team clear control over their data models and allowed them to focus on the business logic, ensuring that trip creation, feedback collection, and participant interactions all flowed smoothly without manual handling. Infrastructure & Deployment: Stability under Pressure To keep their development-to-demo pipeline fast and reliable, Người Việc deployed their system on AWS using Dokploy - a self-hosted CI/CD solution that automates Docker-based deployments. This environment allowed them to push code, test changes, and release updates seamlessly without dependency conflicts. By using Docker containers, they replicated production conditions from the start, ensuring that the MVP remained stable and demo-ready throughout the hackathon. The setup was simple enough for rapid iteration yet robust enough to be scaled for real client use. AI Tools: A Smarter, Not Faster, Way to Build AI played a key role in the team’s workflow but only after the foundation was set.ChatGPT acted as their assistant for ideation and logic design, helping refine user stories, define acceptance criteria, and clarify user flows. Meanwhile, GitHub Copilot served as their pair programmer, generating clean snippets, suggesting improvements, and handling repetitive coding tasks. Instead of using AI as a shortcut, Người Việc used it as an accelerator by integrating it at the right moments to enhance productivity while keeping control of direction and logic. >>> Read more related articles: AI-Assisted Ecommerce Solution Wins Third Place at SupremeTech AI Hackathon 2025How Human Intelligence and AI Capabilities Can Redefine Software Development | Featuring The 1st Runner-Up of SupremeTech AI Hackathon 2025 Judges’ Feedbacks Business Perspective From a business perspective, the judges saw Team Người Việc as a perfect example of practicality and vision. Their solution showed how AI-driven development can address real client needs, especially in industries like travel and hospitality. However, the judges also provided constructive feedback for future improvement. While the idea covered a broad scope from sales to operations, they suggested narrowing the focus to one specific stage in the travel management cycle. By doing so, the solution could achieve higher feasibility and faster adoption in real-world scenarios. The judges also encouraged documenting the team’s AI-assisted project management workflow as a reference for future AI hackathon journeys within SupremeTech. The final presentation showcased all the best qualities of their teamwork. The judges highlighted Người Việc’s clear storytelling, strong time management, and smooth demo delivery that effectively illustrated how their system worked. The team’s confident, structured presentation left a lasting impression and perfectly captured the spirit of SupremeTech’s AI Hackathon. Technical and Engineering Perspective From a technical point of view, the judges recognized Người Việc as a team that combined strong engineering skill with thoughtful use of modern tools. They developed their product on a well-defined code base with clear development standards, following a structured flow from analysis and design to implementation, which is remarkable under the time pressure of a 24-hour hackathon. The highlight of their approach was the story-based prompting technique, which kept the project’s logic coherent from start to finish. By crafting prompts around user stories rather than isolated tasks, the team ensured that every AI-generated piece of code served a real business purpose. This balance between automation and human reasoning became one of the defining features of their success. Teamwork: Staying Calm When Things Went Wrong No hackathon story is complete without chaos and Người Việc had their moment too. Just before the final presentation, disaster happened: the team’s slide suddenly became inaccessible because their shared drive was locked by the judges. With only minutes left, they borrowed a laptop, rebuilt the slides from scratch, and walked onto the stage calm and composed delivering a confident demo that looked effortless to the audience. The team recalled “After 22 hours of coding, what stayed with us wasn’t exhaustion. It was that moment when everyone looked at each other and said: We'll make it work, no matter what.” Voices from the Winners For Team Người Việc, winning the hackathon was not just about the prize, it was about learning how humans and AI can truly collaborate. Reflecting on the experience, Dũng shared: “We realized that AI isn’t just a tool, it’s a real teammate, if you know how to ‘talk’ to it. Each team used AI differently: some for brainstorming, some for UI design, others for presentation. But the prompts we gave were never the same, and that’s why the results were so different. AI only shows its real power when people know how to guide it.” As winners, the team also offered advice for those who will join future hackathons: “Prepare everything you can beforehand: boilerplate code, deployment setup, tools, and your fighting spirit. Once the event starts, every minute counts. And above all, trust your team” Conclusion Team Người Việc proved that real innovation is not only about technology, but about people working together with purpose. By combining business insight, teamwork, and the smart use of AI, they turned a difficult 24-hour challenge into a real achievement. For SupremeTech, this victory is more than just a competition result. It’s a reminder that the future of development starts with clear thinking, strong teamwork, and the courage to explore new ways of building with AI. Appendix: 1. How the Team Applied AI Throughout the Project StageApproachAI Application/ Tools UsedAnalysis & DesignThe whole team brainstormed together, role-playing as real users to map out workflows and features.No AI used — this was the most human-driven stage focused on critical thinking.User Story writingConverted rough ideas into logical workflows, defined goals, and acceptance criteria.ChatGPT acted as a virtual BA, turning brainstorm notes into professional User Stories and Acceptance Criteria.Coding (User Story Based)Developers implemented each User Story while communicating directly with the AI assistant for suggestions and refactoring.GitHub Copilot served as a coding partner, reading stories, suggesting code, refining syntax, and accelerating implementation.Testing & ReleaseThe PTL and BA acted as real users to test the product, identify bugs, and refine the UX before release.No AI used — manual testing for real-user validation. 2. Team Tech Stack LayerTech StackFrontend & Backend (Fullstack)Next.js 15 (App Router)UI Libraryshadcn/ui + TailwindCSSAI AssistantChatGPT + GitHub CopilotInfra / DeployAWS + Dokploy 📩 Read more articles about us here: SupremeTech’s Blog

            22/10/2025

            273

            Quy Huynh

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            • AI-assisted development

            How Team Người Việc Won SupremeTech’s AI Hackathon 2025 with AI-Assisted Development and Agile Thinking

            22/10/2025

            273

            Quy Huynh

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