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Will Software Engineers Or Citizen Developers Benefit More from Large Language Models?

AI Enhances Productivity for Engineers

The emergence of Large Language Models (LLMs) is reshaping the software development landscape, benefiting both software engineers and citizen developers, albeit in distinct ways. Software engineers are experiencing a paradigm shift where AI acts as an accelerant, automating routine coding tasks, debugging, and even architectural recommendations. This augmentation enhances productivity, allowing engineers to focus on higher-level problem-solving, system design, and optimization rather than getting bogged down by syntax-heavy implementation. However, while senior engineers benefit from AI-assisted development, junior developers may face a steeper challenge in proving their value, as many entry-level coding tasks are now automated by AI tools.

 

Conversely, LLMs significantly lower the technical barrier for citizen developers, democratizing software creation through natural language programming and low-code/no-code platforms. Business professionals, entrepreneurs, and non-technical users can now build applications, automate workflows, and query databases without deep programming knowledge. This shift empowers organizations to reduce IT bottlenecks and accelerate digital transformation, making software development more inclusive. However, while LLMs enhance accessibility, they do not replace the need for technical oversight-complex systems, scalability, and security considerations still require the expertise of software engineers.

 

Ultimately, the greatest beneficiaries of LLMs will be those who can integrate AI fluency with domain expertise. Software engineers who adapt to AI-driven development will transition into AI-augmented problem solvers, focusing on strategic thinking, system architecture, and AI governance. Meanwhile, citizen developers will leverage LLMs to build solutions without deep coding skills, but their reliance on AI-generated outputs means they will still require engineers to refine, validate, and scale their solutions. This evolving dynamic suggests that AI is not a zero-sum disruptor but rather a force multiplier, enhancing productivity across both technical and non-technical domains while shifting the nature of software development itself.

Mohammad Haqqani, Founder, Seekario

Both Engineers and Citizen Developers Gain

The rise of large language models (LLMs) is creating a fascinating shift in the software development landscape. It’s natural to wonder who will benefit most: seasoned software engineers or the increasingly empowered citizen developers. The truth is, both stand to gain, but in different ways. Engineers can leverage LLMs to automate repetitive tasks, accelerate coding, and even generate initial drafts of complex algorithms. This frees them to focus on higher-level design, architecture, and problem-solving, essentially supercharging their productivity and allowing them to tackle more ambitious projects.

 

On the other hand, citizen developers, those individuals with domain expertise but perhaps less coding experience, are seeing a new world of possibilities open up. LLMs can help them translate their ideas into functional applications with less reliance on traditional coding. Imagine a marketing manager being able to build a simple data analysis tool by describing what they need in plain language. This democratization of development could unlock a wave of innovation from those closest to the problems, leading to solutions we haven’t even imagined yet. It’s not about replacing engineers, but rather expanding the pool of those who can contribute to the creation of software.

 

Brandon Batchelor, Head of North American Sales and Strategic Partnerships, ReadyCloud 

Citizen Developers Benefit Most

Large Language Models (LLMs) are changing the game for both software engineers and citizen developers, but the biggest winners will be citizen developers. These AI-powered tools lower the barrier to entry, allowing non-technical users to build applications, automate tasks, and generate code without deep programming knowledge. Businesses can now train employees in no-code and low-code platforms, increasing efficiency and reducing dependency on traditional developers for routine tasks.

 

That said, software engineers will still have the edge when it comes to building, refining, and scaling AI-driven solutions. LLMs can generate code, but they still require human oversight to ensure accuracy, security, and efficiency. While citizen developers gain accessibility, software engineers who leverage AI for code generation, debugging, and automation will become even more valuable, focusing on high-level problem-solving rather than repetitive coding tasks.

 

Georgi Petrov, CMO, Entrepreneur, and Content Creator, AIG MARKETER

AI Pros Rate their Happiness With the Release of Deepseek R1

DeepSeek R1 Democratizes AI Innovation

The release of DeepSeek R1 under an MIT open-source license is a major win for the AI ecosystem. In a landscape where AI innovation is increasingly controlled by a few dominant players, open models provide a counterbalance – democratizing access, accelerating research, and fostering competition.

Why This Matters

  1. Faster Enterprise Adoption

Open-source models can be audited, customized, and integrated without reliance on external API access or restrictive licensing. For enterprises, this means faster deployment, better security control, and reduced vendor lock-in. DeepSeek R1 has the potential to make enterprise-grade AI more accessible than ever.

  1. A True “Open AI”

The irony of OpenAI’s name is now more apparent than ever. While OpenAI has shifted towards a closed-source, API-gated model, DeepSeek R1 brings back the original vision of openly accessible, state-of-the-art AI models. Researchers, startups, and independent developers can all build on top of it – without waiting for permission.

  1. A Rising Tide for AI Innovation

Open-source AI is not a threat – it’s a multiplier. We’ve seen this before with foundational open-source technologies: Linux in operating systems, TensorFlow/PyTorch in deep learning, and Hugging Face in NLP. These platforms didn’t eliminate commercial competition; they expanded the market and accelerated breakthroughs.

  1. It’s Not About Geopolitics – It’s About Access

Some will frame DeepSeek R1’s release as part of a US vs. China AI arms race. But the real battle is between closed-source AI models and open alternatives. When AI is locked behind corporate paywalls, innovation slows. When AI is open, the entire ecosystem benefits.

The Bottom Line

DeepSeek R1’s release isn’t just a technical milestone – it’s a statement. A statement that AI should be open, accessible, and adaptable for all. We need more competition, more transparency, and more models that anyone can build on.

Whether this will change how leading AI companies operate remains to be seen. But one thing is clear: the open-source movement just gained a powerful new player.

Mohammad Haqqani, Founder, Seekario

Excitement for Deepseek R1’s Open Source Release

As an AI professional, I’m excited to see Deepseek R1 being released under an MIT open source license. This is a huge step forward because it opens up opportunities for greater accessibility, collaboration, and innovation within the AI community. Open-source licenses like MIT allow developers, researchers, and organizations to use, modify, and contribute to the software freely, which can significantly accelerate progress and lead to more diverse and robust AI solutions.

Releasing Deepseek R1 under this license makes it easier for a wider range of people to experiment with the technology and integrate it into various applications, from academic research to commercial products. The transparency that comes with open-source projects also ensures that the AI is developed in a responsible manner, with contributions coming from many different individuals and groups. This collaborative approach not only benefits the AI community but also pushes the boundaries of what AI can do in exciting, innovative ways. Overall, I see this as a fantastic move that will foster continued growth and exploration in the AI space.

Nikita Sherbina, Co-Founder & CEO, AIScreen

AI Development Moves Forward with Deepseek R1

The release of Deepseek R1 under an MIT open-source license is a huge step forward for AI development. Open-source models accelerate innovation, allowing researchers, developers, and businesses to build on existing advancements without the usual barriers of proprietary AI. This move creates more transparency and accessibility, which is something the AI space desperately needs.

From a business perspective, this opens up opportunities to customize and optimize AI models for specific use cases, whether for marketing automation, content creation, or customer insights. However, there’s also a concern—open-source AI can be misused without proper ethical considerations or security measures.

While I’m excited about the potential for more democratized AI, responsible usage and safeguards are just as important. If Deepseek R1 can maintain high performance while remaining adaptable, it could be a game-changer in making AI more accessible for businesses of all sizes.

Georgi Petrov, CMO, Entrepreneur, and Content Creator, AIG MARKETER

Will AI Replace Traditional SaaS Business Applications?

Introduction

Author: Niall McCarthy

Published: https://lordmatt.co.uk/technology/coding-and-development/the-most-significant-developments-in-web-development-for-professionals-and-why-it-isnt-ai/

“Will AI really kill the SaaS business application market, as Satya Nadella, CEO of Microsoft, has recently suggested? Or will the proportion of SaaS offerings dependent on AI simply grow?” Here is what 5 thought leaders have to say.

Interestingly, no-one fully agrees with Nadella…

AI Will Propel SaaS Forward

As the CEO of a cybersecurity firm, I’ve been closely watching the AI revolution unfold across various industries, including SaaS. Satya Nadella’s recent comments about AI potentially killing the SaaS market are certainly thought-provoking, but I believe the reality is more nuanced.

 

From my perspective in the cybersecurity world, I’ve seen how AI is reshaping our industry rather than replacing it entirely. We’re not seeing AI eliminate the need for cybersecurity solutions; instead, it’s becoming an integral part of them. I suspect the same will happen with SaaS.

 

AI isn’t the death knell for SaaS; it’s more like a supercharged engine that’s going to propel it into new territories.

 

In our own company, we’ve integrated AI into our threat detection systems, making them more efficient and accurate. But the core of what we do – protecting digital assets – remains unchanged. Similarly, I believe SaaS companies will incorporate AI to enhance their offerings rather than be replaced by it.

 

That said, the landscape is definitely shifting. Just last month, I attended a tech conference where several SaaS startups showcased AI-driven features that would have seemed like science fiction a few years ago. It’s clear that companies that don’t adapt to this AI wave might struggle to stay relevant.

 

However, it’s important to remember that AI, for all its power, still needs human oversight – especially in critical areas like cybersecurity. We’ve had instances where our AI systems flagged potential threats that turned out to be false positives, and it took human expertise to sort it out.

 

So, while I don’t see AI “killing” SaaS, I do think we’re moving toward a future where AI-powered SaaS becomes the norm. Companies that can successfully blend AI capabilities with their core services will likely thrive in this new ecosystem.

 

Ayush Trivedi, CEO, Cyber Chief

AI Enhances SaaS Platforms

I don’t believe AI will kill the SaaS business application market; rather, it will transform it. SaaS offerings will increasingly integrate AI, making them smarter and more adaptive to user needs. The proportion of AI-dependent SaaS solutions will undoubtedly grow, but that’s more of an evolution than an extinction.

 

In my experience, AI enhances SaaS platforms by automating workflows, delivering predictive analytics, and offering personalized user experiences. For example, we recently integrated AI into a customer management tool to predict churn rates and recommend proactive strategies. It didn’t replace the platform, it amplified its value.

 

Satya Nadella’s statement highlights a shift: companies that fail to adapt to AI will struggle, while those embracing it will lead the market. The key takeaway? AI isn’t killing SaaS, it’s making it indispensable. The future belongs to SaaS solutions that seamlessly combine AI with human-centric design to solve real business problems.

 

Nikita Sherbina, Co-Founder & CEO, AIScreen

AI Transforms SaaS Interaction

I don’t believe AI will wipe out the SaaS business application market, but it’s definitely going to change the way businesses interact with these platforms. SaaS will continue to grow, but it will evolve to heavily depend on AI to make services smarter and more intuitive. I’ve seen how AI already helps marketers make better decisions by analyzing data at a deeper level, which drives better results. I can only imagine how much further this will go.

 

For companies working with SaaS now, jumping on the AI train can’t be ignored. Don’t think of AI as a threat; think of it as a tool to enhance the service you’re already using. It will help optimize processes, improve customer experience, and scale efficiently. For any SaaS provider, AI isn’t just an option anymore—it’s part of staying relevant.

 

Natalia Lavrenenko, UGC manager/Marketing manager, Rathly

AI Reshapes SaaS Market

You know, I get why some folks think AI will “kill” the SaaS business app scene, but I’m not buying it. I see AI changing the game completely instead of taking it out. AI won’t wipe out SaaS, it’ll reshape it. Those who adjust and adapt will do well, and those who don’t? Well, they might just fall off.

 

We’re already seeing this in action. Take Microsoft 365 Copilot or Salesforce Einstein, for example. These tools use AI to make things smoother and give you insights in real time. Microsoft Word isn’t just about writing anymore; it can help you create proposals or reports in a smart way. And Salesforce? It’s not just a CRM tool anymore. It’s like having an AI buddy that understands customer behavior and helps with workflows. Sure, they’re still SaaS products, but AI is taking their usefulness up a notch.

 

What I think really matters here is the way people expect things to work. Customers won’t be happy with just tools that organize information anymore. They’ll want solutions that can act, analyze, and even make predictions. Picture a project management app that doesn’t just keep up with deadlines but suggests how to make timelines better. Or think about a marketing tool that can whip up entire campaigns based on what you want to achieve. SaaS companies that can’t keep up with this level of smartness might find themselves in trouble.

 

Business models are gonna change too. AI might push SaaS companies toward pricing based on performance. Instead of a flat monthly fee, users could pay based on the return they get from AI-driven suggestions or automations. This could open up access for smaller businesses and connect revenue to actual value delivered.

 

But let’s be real-AI is likely gonna consolidate the market. Big players like Microsoft and Google are gonna lead the way with their AI resources. Still, there’s definitely space for smaller SaaS solutions that tackle specific problems using AI. The trick will be staying flexible and willing to think outside the box.

 

For me, this isn’t the end of SaaS-it’s a whole new start. AI will be as important as cloud tech or mobile design, and the companies that jump on board will really stand out. The real question isn’t if AI will change SaaS; it’s whether the providers can keep up with all this change.

 

What do you think? Will AI make SaaS better, or are we just headed toward a market ruled by a couple of tech giants?

 

Carlos Palop, CEO, UniteSync

AI Deepens SaaS Integration

I doubt AI will “kill” the SaaS business application market. Instead, it’s more likely that SaaS providers will deepen their AI integrations to stay competitive. When we began using AI-driven analytics in our own quote-comparison software, it didn’t replace the platform, it enhanced it by offering faster insights and more targeted recommendations. If anything, that improvement boosted customer loyalty and positioned us for future growth. SaaS platforms that evolve with AI tend to discover new revenue streams and features that help users do their jobs more efficiently. While companies that ignore AI might get left behind, those that embrace it will probably see AI as a growth catalyst rather than a threat.

James Shaffer, Managing Director, Insurance Panda

A Simple Privacy Concern with AI Data

Author: Niall McCarthy, CEO Aire AI
Published: Data Science Spotlight, 21 Jan 2025

The amount of information about ourselves and our businesses that we’re willing to give to AI, in particular Large Language Machines such as GPT and Claude, is disturbing.

Not so long ago, there was much concern about the giant sucking noise made by Google and other search engines. However, the practical reality is that traditional search engines were often based on getting to know you just through your search history and behavioral analysis. Of course, this concern hasn’t gone away, but the danger has increased by an order of magnitude.

Starting with search itself, it’s now well-known that users of AI voice-enabled search give far more away about themselves than with traditional written search. Their search question is longer and their recorded voice can be immediately analyzed for sentiment.

However, the real threat is the number of industry-specific applications being built directly upon Large Language Models. The potential market for this new generation of SaaS type solutions is immense. We see already how it’s revolutionizing the domain of marketing content generation. It goes even further in the domain of customer support, with AI Agents accessing entire knowledge bases of organizations and being rigorously “trained” with hundreds of examples of business processes to execute.

On the individual/consumer level, we see the mass adoption of voice assistants well beyond the domain of search (e.g., Alexa, Siri). We also see relatively few if any guardrails as to how users query AI. Large Language Models, for example, aren’t designed to say “no” to a child, but rather to generate never-ending output based on what has just been said. Commercially, it’s not in the interests of the software vendor to stop the conversation.

AI designs which incorporate “Human in the Loop” feedback are becoming more prevalent, but this is a double-edged sword. HITL improves the AI output, making it more accurate to the user’s requirement. However, it also fine-tunes what the owner of the AI knows about the user or their organization.

As the CEO of an AI software vendor, our approach to solution design has to take into account the digital sovereignty of our customers. As father to a young child, educating our boy not to trust a connected computer or mobile device, while simultaneously learning its potential has become a top parental challenge.

6 Expert Opinions on OpenAI Singularity Claims

OpenAI recently claimed that AI “singularity” is near. Is there truth to this claim? How does it make you feel?

Here is what 6 thought leaders have to say:

  • Approach Singularity Claims Cautiously
  • AI Advancements Are Rapid But Limited
  • Singularity Claim Requires Skepticism
  • AI Progress Sparks Cautious Optimism
  • Singularity Concept Oversimplifies Intelligence
  • AI Singularity Feels Like Hype

 

Approach Singularity Claims Cautiously

The idea of AI “singularity”-where AI surpasses human intelligence and becomes self-improving-has long been a topic of debate. While advancements in AI are progressing rapidly, claims that singularity is “near” should be approached cautiously and critically.

Current AI systems excel in specific tasks through vast data processing but lack the general reasoning, emotional intelligence, and adaptability of human cognition. The leap from advanced tools to autonomous, self-improving entities requires breakthroughs in understanding consciousness, ethics, and control mechanisms-challenges we’re far from solving comprehensively.

Personally, the prospect of singularity is both exciting and humbling. It inspires me to think about how we can responsibly design AI systems to enhance human life, not replace it. It also underscores the importance of creating ethical frameworks and collaboration between scientists, policymakers, and society to ensure AI development remains aligned with human values.

Rather than fearing singularity, I focus on how AI can complement human capabilities, solving complex problems in healthcare, education, and the environment. Whether or not singularity is near, it’s our responsibility to guide AI’s trajectory toward a future that prioritizes collaboration, safety, and inclusivity.

Marin Cristian-Ovidiu, CEO, Online Games

AI Advancements Are Rapid But Limited

The claim that AI ‘singularity’ is near is both intriguing and contentious. The concept of AI singularity, often associated with the idea that artificial intelligence will surpass human intelligence and become self-improving, has been a topic of debate for decades.

OpenAI’s statement reflects the rapid advancements in AI technology, particularly in areas like machine learning and natural language processing. However, whether we are truly on the verge of achieving singularity is still uncertain.

From my perspective, while AI has made tremendous strides, particularly in automation, data processing, and even creative tasks, the leap to true artificial general intelligence (AGI)—where AI can independently improve itself and surpass human cognitive abilities in every domain—feels like a far-off prospect. We’re still facing challenges with AI systems that require a lot of human oversight, training, and fine-tuning to perform at a high level.

The idea of singularity is exciting but also somewhat unnerving. If AI could truly become self-improving, it could bring about profound changes in society, both positive and negative. On one hand, it could accelerate innovation and help solve complex global challenges. On the other hand, there are concerns about the potential risks, including job displacement, loss of control, and ethical issues.

For me, the focus should be on using AI responsibly and ensuring that advancements are guided by thoughtful governance, transparency, and an understanding of the long-term impact on society.

The fear of singularity shouldn’t stop us from embracing the benefits AI offers, but it does serve as a reminder to approach these technologies with caution and a plan for managing potential consequences.

Georgi Petrov, CMO, Entrepreneur, and Content Creator, AIG MARKETER

Singularity Claim Requires Skepticism

The notion that the AI singularity is ‘near’ is a bold claim but should be approached with reasonable skepticism.

Though recent advancements like OpenAI’s progress with models such as the upcoming ‘o3 mini,’ reveal rapid strides in AI development, the so-called singularity – the point where AI surpasses human intelligence – is a speculative concept. There’s still major technical, ethical, and philosophical challenges to grapple with before we can confidently predict its arrival.

Devan Leos, co-founder & CCO, Undetectable AI

AI Progress Sparks Cautious Optimism

The claim that AI “singularity” is near sparks both intrigue and skepticism. While advancements in AI have been undeniably rapid, with models capable of generating sophisticated outputs and solving complex problems, we’re still far from a system that can truly mimic or surpass human general intelligence across all domains.

For one, AI systems remain highly specialized and reliant on vast amounts of pre-existing data, lacking the nuanced creativity, emotional intelligence, and moral reasoning inherent to humans. Plus, the singularity concept tends to oversimplify the complexity of intelligence itself—equating raw computational power to the multifaceted nature of human cognition.

As for how it makes me feel, it’s a mix of curiosity and cautious optimism. AI’s potential to revolutionize industries, improve lives, and solve pressing global challenges excites me. But it also highlights the importance of ethical guardrails, transparency, and collaboration in AI development to ensure it aligns with humanity’s best interests. Whether or not singularity is near, the journey toward increasingly advanced AI will shape our future profoundly, and that’s where the focus should be.

Hubertus Von Aulock, Editor in Chief, Config Craft

Singularity Concept Oversimplifies Intelligence

The idea of AI “singularity”—where AI surpasses human intelligence—is fascinating, but it’s also loaded with hype. While AI is making crazy leaps, we’re still far from a system that can fully replicate human intuition, creativity, and emotional understanding. Claims like this often oversimplify the complexities of both AI development and human intelligence. As for how it feels? A mix of excitement and caution. The tech has massive potential, but it also needs guardrails to make sure we’re steering it in a way that benefits everyone, not just a select few.

Justin Belmont, Founder & CEO, Prose

AI Singularity Feels Like Hype

The idea of AI “singularity” being near is fascinating but feels more like hype than reality right now. While AI is advancing rapidly and transforming industries, we’re still far from creating machines with true human-like intelligence or self-awareness. As a business owner, I see AI as a tool, not a threat—it’s all about how we use it. Honestly, it motivates me to stay adaptable and think creatively about leveraging these advancements to grow and innovate, rather than worrying about doomsday scenarios.

Tomasz Lewandowski, Business Owner | Web Designer, 2D Figure Painting