Jul 11, 2025
Transforming Software Development with Low-Code and AI
Conor Bronsdon
Head of Developer Awareness
Conor Bronsdon
Head of Developer Awareness
Software development is changing. The space is undergoing a profound transformation, driven by the convergence of low-code platforms and artificial intelligence.
This shift was the focus of a recent episode of Chain of Thought, where host Conor Bronsdon, Head of Developer Awareness at Galileo, and co-host Atindriyo Sanyal, the CTO and Co-Founder of Galileo, had an engaging conversation with Rodrigo Coutinho, Co-Founder and AI Product Manager at OutSystems.
OutSystems has pioneered the integration of AI into low-code development tools, creating an ecosystem where developers can rapidly innovate and deliver enterprise applications. Their approach fundamentally changes development dynamics by compressing what once took weeks into mere moments.
"The ability to do these iterations in seconds completely changes the way you work," Coutinho observed during the conversation. This acceleration isn't merely about speed—it represents a paradigm shift in how software adapts to business needs, enabling developers to create immediate value through accessible tools that maintain professional quality.
How Low-Code Tools Enhance Speed and Efficiency
Traditional software development follows linear paths with extended feedback loops. Low-code platforms disrupt this model by enabling real-time development and validation. The immediacy of this approach transforms collaborative processes between technical teams and stakeholders.
Accelerating Development Timelines
The compression of development timelines represents perhaps the most tangible impact of low-code platforms. Projects that traditionally required months now conclude in weeks or even days. This acceleration doesn't sacrifice quality but rather redistributes development effort toward higher-value activities.
"Now you can ask someone what they want. You do it live, and you have, in seconds, a prototype of what the person told you they wanted," Coutinho explains. This capability reshapes planning sessions into dynamic creation workshops where ideas materialize instantly, allowing teams to refine concepts on the fly rather than waiting for the next development cycle.
Coutinho further characterizes these tools as "superpowers" that fundamentally alter resource allocation and market responsiveness. Organizations in highly regulated industries benefit particularly, as compliance requirements can be rapidly incorporated into applications without extensive delays. A financial institution, for instance, might iterate through multiple versions of a regulatory reporting system within a single sprint rather than enduring months of development.
These efficiency gains extend well beyond initial development. When market conditions or business requirements change, applications can evolve in near real-time, preventing the accumulation of technical debt that plagues traditional development approaches. This adaptability creates a sustainable competitive advantage, especially in dynamic industries where responsiveness determines market position.
Reducing Technical Debt Through Continuous Iteration
Low-code platforms fundamentally transform how organizations manage technical debt by enabling continuous refinement of applications. Leveraging practices like Continuous Integration for AI, organizations can systematically update low-code applications without extensive refactoring.
Coutinho explains how "the ability to modernize applications incrementally rather than through massive rewrites changes the economics of software maintenance". This ongoing evolution helps organizations avoid the resource-intensive rebuilds that typically occur when technical debt reaches critical levels.
The visual nature of low-code development also improves documentation by default, as the platforms maintain clear representations of application architecture and workflows. This transparency reduces the knowledge barriers that typically contribute to technical debt when team members transition or when applications require modification after extended periods.
Organizations using these platforms report significant reductions in maintenance costs, with resources previously dedicated to supporting legacy systems now redirected toward innovation initiatives that drive business value. This shift creates a virtuous cycle where reduced technical burden enables more rapid response to emerging opportunities.
Bridging Expertise Levels
The democratization of development represents one of the most promising aspects of AI-enhanced low-code platforms. These systems, including the use of AI agents, create scaffolding that enables less experienced developers to contribute meaningfully to complex projects.
"We started investing in AI back in 2018 specifically to help developers be more productive and create better enterprise applications," said Coutinho, highlighting OutSystems' early recognition of AI's potential. This investment materialized in tools like Mentor, which can generate complete enterprise applications from requirement documents while incorporating architectural best practices.
This evolution redefines the developer's role within organizations, emphasizing the importance of AI fluency in validating code, ensuring quality, and orchestrating components. The shift opens new career pathways focused on solution architecture and business analysis rather than syntax mastery, allowing technical professionals to concentrate on creating business value through technology rather than wrestling with implementation details.
Aligning Software With Business Objectives
Perhaps the most significant impact of these platforms lies in their ability to bridge the persistent gap between business requirements and technical implementation. Traditional development processes often produced solutions that gradually diverged from original business objectives through layers of translation and documentation.
The immediacy of low-code development creates a shared visual language between technical and non-technical stakeholders. "Iterating in seconds during a meeting completely changes your workflow," Coutinho emphasizes. When a business analyst describes a needed feature, developers can model it instantly, enabling immediate refinement and ensuring alignment between vision and execution.
This accessibility extends beyond traditional development teams, enabling domain experts to participate directly in the creation process and maximize AI for business value. This evolution is a prime example of AI in human interactions, where technology facilitates closer collaboration and co-creation. This direct involvement embeds crucial domain expertise into applications, resulting in solutions that intuitively match workflow requirements and drive higher adoption rates.
Navigating Challenges in Software Development With Strategic AI Solutions
While AI-enhanced low-code platforms offer significant advantages, they introduce specific challenges that require strategic approaches. OutSystems has identified critical concerns, including quality assurance, security integration, and maintaining appropriate human oversight in increasingly automated development processes.
Quality validation, such as the application of AI evaluation metrics, becomes particularly crucial as development accelerates. OutSystems addresses this through automated testing frameworks and built-in validation processes that continuously evaluate applications against enterprise standards.
These mechanisms operate alongside development rather than as separate phases, preserving speed while ensuring technical excellence.
"Even as we automate more aspects of development, human expertise remains essential for evaluating context and appropriateness," Coutinho emphasizes. OutSystems deliberately structures their AI capabilities to augment rather than replace developer judgment, recognizing that balancing automation with expertise produces optimal results.
Security integration presents another significant challenge as development barriers lower, especially considering open-source LLM challenges. OutSystems approaches this through architectural guardrails that automatically implement security best practices and compliance requirements. These embedded protections help prevent common vulnerabilities without requiring developers to maintain specialized security expertise.
The risk of technical divergence increases as more stakeholders contribute to development. OutSystems addresses this through governance frameworks that maintain architectural consistency while enabling broad participation.
These structures help organizations balance democratization with necessary standards, preventing the proliferation of disconnected solutions that ultimately increase maintenance complexity.
As organizations adopt these technologies, OutSystems recommends phased implementation approaches that gradually expand capabilities while establishing appropriate governance structures. This measured adoption helps teams develop the skills and processes needed to maximize value while managing associated risks.
The Future of Software Development With AI and Low-Code
Looking ahead, the integration of AI and low-code development will likely transform software engineering education and career paths fundamentally. As Coutinho envisions, "In the future, we may see software engineering curricula that focus more on solution architecture and business value creation rather than programming language specifics."
This shift would prepare the next generation of developers to leverage AI-powered tools that handle implementation details while they focus on higher-order problem-solving.
The enterprise application landscape will likely evolve toward composable architectures where AI assists in assembling and optimizing pre-built components based on business requirements. This could eliminate the traditional distinction between "custom" and "off-the-shelf" software, creating a continuum where solutions are rapidly assembled from standardized building blocks but customized through intelligent adaptation to specific business contexts.
Galileo's platform embodies this forward-looking approach by providing robust evaluation, monitoring, and protection capabilities for AI applications. Galileo creates an environment where rapid iteration remains secure and reliable, allowing organizations to fully leverage the accelerated development cycles that AI systems enable without compromising on governance or quality.
Explore Galileo today platform to address many of the challenges Coutinho and Sanyal discussed around quality, security, and governance in AI systems.
For more insights, listen to the complete podcast for more on how these technologies are reshaping development practices today and what's coming next. And check out other Chain of Thought episodes, where we break down complex Generative AI concepts into actionable strategies for software engineers and AI leaders.
Software development is changing. The space is undergoing a profound transformation, driven by the convergence of low-code platforms and artificial intelligence.
This shift was the focus of a recent episode of Chain of Thought, where host Conor Bronsdon, Head of Developer Awareness at Galileo, and co-host Atindriyo Sanyal, the CTO and Co-Founder of Galileo, had an engaging conversation with Rodrigo Coutinho, Co-Founder and AI Product Manager at OutSystems.
OutSystems has pioneered the integration of AI into low-code development tools, creating an ecosystem where developers can rapidly innovate and deliver enterprise applications. Their approach fundamentally changes development dynamics by compressing what once took weeks into mere moments.
"The ability to do these iterations in seconds completely changes the way you work," Coutinho observed during the conversation. This acceleration isn't merely about speed—it represents a paradigm shift in how software adapts to business needs, enabling developers to create immediate value through accessible tools that maintain professional quality.
How Low-Code Tools Enhance Speed and Efficiency
Traditional software development follows linear paths with extended feedback loops. Low-code platforms disrupt this model by enabling real-time development and validation. The immediacy of this approach transforms collaborative processes between technical teams and stakeholders.
Accelerating Development Timelines
The compression of development timelines represents perhaps the most tangible impact of low-code platforms. Projects that traditionally required months now conclude in weeks or even days. This acceleration doesn't sacrifice quality but rather redistributes development effort toward higher-value activities.
"Now you can ask someone what they want. You do it live, and you have, in seconds, a prototype of what the person told you they wanted," Coutinho explains. This capability reshapes planning sessions into dynamic creation workshops where ideas materialize instantly, allowing teams to refine concepts on the fly rather than waiting for the next development cycle.
Coutinho further characterizes these tools as "superpowers" that fundamentally alter resource allocation and market responsiveness. Organizations in highly regulated industries benefit particularly, as compliance requirements can be rapidly incorporated into applications without extensive delays. A financial institution, for instance, might iterate through multiple versions of a regulatory reporting system within a single sprint rather than enduring months of development.
These efficiency gains extend well beyond initial development. When market conditions or business requirements change, applications can evolve in near real-time, preventing the accumulation of technical debt that plagues traditional development approaches. This adaptability creates a sustainable competitive advantage, especially in dynamic industries where responsiveness determines market position.
Reducing Technical Debt Through Continuous Iteration
Low-code platforms fundamentally transform how organizations manage technical debt by enabling continuous refinement of applications. Leveraging practices like Continuous Integration for AI, organizations can systematically update low-code applications without extensive refactoring.
Coutinho explains how "the ability to modernize applications incrementally rather than through massive rewrites changes the economics of software maintenance". This ongoing evolution helps organizations avoid the resource-intensive rebuilds that typically occur when technical debt reaches critical levels.
The visual nature of low-code development also improves documentation by default, as the platforms maintain clear representations of application architecture and workflows. This transparency reduces the knowledge barriers that typically contribute to technical debt when team members transition or when applications require modification after extended periods.
Organizations using these platforms report significant reductions in maintenance costs, with resources previously dedicated to supporting legacy systems now redirected toward innovation initiatives that drive business value. This shift creates a virtuous cycle where reduced technical burden enables more rapid response to emerging opportunities.
Bridging Expertise Levels
The democratization of development represents one of the most promising aspects of AI-enhanced low-code platforms. These systems, including the use of AI agents, create scaffolding that enables less experienced developers to contribute meaningfully to complex projects.
"We started investing in AI back in 2018 specifically to help developers be more productive and create better enterprise applications," said Coutinho, highlighting OutSystems' early recognition of AI's potential. This investment materialized in tools like Mentor, which can generate complete enterprise applications from requirement documents while incorporating architectural best practices.
This evolution redefines the developer's role within organizations, emphasizing the importance of AI fluency in validating code, ensuring quality, and orchestrating components. The shift opens new career pathways focused on solution architecture and business analysis rather than syntax mastery, allowing technical professionals to concentrate on creating business value through technology rather than wrestling with implementation details.
Aligning Software With Business Objectives
Perhaps the most significant impact of these platforms lies in their ability to bridge the persistent gap between business requirements and technical implementation. Traditional development processes often produced solutions that gradually diverged from original business objectives through layers of translation and documentation.
The immediacy of low-code development creates a shared visual language between technical and non-technical stakeholders. "Iterating in seconds during a meeting completely changes your workflow," Coutinho emphasizes. When a business analyst describes a needed feature, developers can model it instantly, enabling immediate refinement and ensuring alignment between vision and execution.
This accessibility extends beyond traditional development teams, enabling domain experts to participate directly in the creation process and maximize AI for business value. This evolution is a prime example of AI in human interactions, where technology facilitates closer collaboration and co-creation. This direct involvement embeds crucial domain expertise into applications, resulting in solutions that intuitively match workflow requirements and drive higher adoption rates.
Navigating Challenges in Software Development With Strategic AI Solutions
While AI-enhanced low-code platforms offer significant advantages, they introduce specific challenges that require strategic approaches. OutSystems has identified critical concerns, including quality assurance, security integration, and maintaining appropriate human oversight in increasingly automated development processes.
Quality validation, such as the application of AI evaluation metrics, becomes particularly crucial as development accelerates. OutSystems addresses this through automated testing frameworks and built-in validation processes that continuously evaluate applications against enterprise standards.
These mechanisms operate alongside development rather than as separate phases, preserving speed while ensuring technical excellence.
"Even as we automate more aspects of development, human expertise remains essential for evaluating context and appropriateness," Coutinho emphasizes. OutSystems deliberately structures their AI capabilities to augment rather than replace developer judgment, recognizing that balancing automation with expertise produces optimal results.
Security integration presents another significant challenge as development barriers lower, especially considering open-source LLM challenges. OutSystems approaches this through architectural guardrails that automatically implement security best practices and compliance requirements. These embedded protections help prevent common vulnerabilities without requiring developers to maintain specialized security expertise.
The risk of technical divergence increases as more stakeholders contribute to development. OutSystems addresses this through governance frameworks that maintain architectural consistency while enabling broad participation.
These structures help organizations balance democratization with necessary standards, preventing the proliferation of disconnected solutions that ultimately increase maintenance complexity.
As organizations adopt these technologies, OutSystems recommends phased implementation approaches that gradually expand capabilities while establishing appropriate governance structures. This measured adoption helps teams develop the skills and processes needed to maximize value while managing associated risks.
The Future of Software Development With AI and Low-Code
Looking ahead, the integration of AI and low-code development will likely transform software engineering education and career paths fundamentally. As Coutinho envisions, "In the future, we may see software engineering curricula that focus more on solution architecture and business value creation rather than programming language specifics."
This shift would prepare the next generation of developers to leverage AI-powered tools that handle implementation details while they focus on higher-order problem-solving.
The enterprise application landscape will likely evolve toward composable architectures where AI assists in assembling and optimizing pre-built components based on business requirements. This could eliminate the traditional distinction between "custom" and "off-the-shelf" software, creating a continuum where solutions are rapidly assembled from standardized building blocks but customized through intelligent adaptation to specific business contexts.
Galileo's platform embodies this forward-looking approach by providing robust evaluation, monitoring, and protection capabilities for AI applications. Galileo creates an environment where rapid iteration remains secure and reliable, allowing organizations to fully leverage the accelerated development cycles that AI systems enable without compromising on governance or quality.
Explore Galileo today platform to address many of the challenges Coutinho and Sanyal discussed around quality, security, and governance in AI systems.
For more insights, listen to the complete podcast for more on how these technologies are reshaping development practices today and what's coming next. And check out other Chain of Thought episodes, where we break down complex Generative AI concepts into actionable strategies for software engineers and AI leaders.
Software development is changing. The space is undergoing a profound transformation, driven by the convergence of low-code platforms and artificial intelligence.
This shift was the focus of a recent episode of Chain of Thought, where host Conor Bronsdon, Head of Developer Awareness at Galileo, and co-host Atindriyo Sanyal, the CTO and Co-Founder of Galileo, had an engaging conversation with Rodrigo Coutinho, Co-Founder and AI Product Manager at OutSystems.
OutSystems has pioneered the integration of AI into low-code development tools, creating an ecosystem where developers can rapidly innovate and deliver enterprise applications. Their approach fundamentally changes development dynamics by compressing what once took weeks into mere moments.
"The ability to do these iterations in seconds completely changes the way you work," Coutinho observed during the conversation. This acceleration isn't merely about speed—it represents a paradigm shift in how software adapts to business needs, enabling developers to create immediate value through accessible tools that maintain professional quality.
How Low-Code Tools Enhance Speed and Efficiency
Traditional software development follows linear paths with extended feedback loops. Low-code platforms disrupt this model by enabling real-time development and validation. The immediacy of this approach transforms collaborative processes between technical teams and stakeholders.
Accelerating Development Timelines
The compression of development timelines represents perhaps the most tangible impact of low-code platforms. Projects that traditionally required months now conclude in weeks or even days. This acceleration doesn't sacrifice quality but rather redistributes development effort toward higher-value activities.
"Now you can ask someone what they want. You do it live, and you have, in seconds, a prototype of what the person told you they wanted," Coutinho explains. This capability reshapes planning sessions into dynamic creation workshops where ideas materialize instantly, allowing teams to refine concepts on the fly rather than waiting for the next development cycle.
Coutinho further characterizes these tools as "superpowers" that fundamentally alter resource allocation and market responsiveness. Organizations in highly regulated industries benefit particularly, as compliance requirements can be rapidly incorporated into applications without extensive delays. A financial institution, for instance, might iterate through multiple versions of a regulatory reporting system within a single sprint rather than enduring months of development.
These efficiency gains extend well beyond initial development. When market conditions or business requirements change, applications can evolve in near real-time, preventing the accumulation of technical debt that plagues traditional development approaches. This adaptability creates a sustainable competitive advantage, especially in dynamic industries where responsiveness determines market position.
Reducing Technical Debt Through Continuous Iteration
Low-code platforms fundamentally transform how organizations manage technical debt by enabling continuous refinement of applications. Leveraging practices like Continuous Integration for AI, organizations can systematically update low-code applications without extensive refactoring.
Coutinho explains how "the ability to modernize applications incrementally rather than through massive rewrites changes the economics of software maintenance". This ongoing evolution helps organizations avoid the resource-intensive rebuilds that typically occur when technical debt reaches critical levels.
The visual nature of low-code development also improves documentation by default, as the platforms maintain clear representations of application architecture and workflows. This transparency reduces the knowledge barriers that typically contribute to technical debt when team members transition or when applications require modification after extended periods.
Organizations using these platforms report significant reductions in maintenance costs, with resources previously dedicated to supporting legacy systems now redirected toward innovation initiatives that drive business value. This shift creates a virtuous cycle where reduced technical burden enables more rapid response to emerging opportunities.
Bridging Expertise Levels
The democratization of development represents one of the most promising aspects of AI-enhanced low-code platforms. These systems, including the use of AI agents, create scaffolding that enables less experienced developers to contribute meaningfully to complex projects.
"We started investing in AI back in 2018 specifically to help developers be more productive and create better enterprise applications," said Coutinho, highlighting OutSystems' early recognition of AI's potential. This investment materialized in tools like Mentor, which can generate complete enterprise applications from requirement documents while incorporating architectural best practices.
This evolution redefines the developer's role within organizations, emphasizing the importance of AI fluency in validating code, ensuring quality, and orchestrating components. The shift opens new career pathways focused on solution architecture and business analysis rather than syntax mastery, allowing technical professionals to concentrate on creating business value through technology rather than wrestling with implementation details.
Aligning Software With Business Objectives
Perhaps the most significant impact of these platforms lies in their ability to bridge the persistent gap between business requirements and technical implementation. Traditional development processes often produced solutions that gradually diverged from original business objectives through layers of translation and documentation.
The immediacy of low-code development creates a shared visual language between technical and non-technical stakeholders. "Iterating in seconds during a meeting completely changes your workflow," Coutinho emphasizes. When a business analyst describes a needed feature, developers can model it instantly, enabling immediate refinement and ensuring alignment between vision and execution.
This accessibility extends beyond traditional development teams, enabling domain experts to participate directly in the creation process and maximize AI for business value. This evolution is a prime example of AI in human interactions, where technology facilitates closer collaboration and co-creation. This direct involvement embeds crucial domain expertise into applications, resulting in solutions that intuitively match workflow requirements and drive higher adoption rates.
Navigating Challenges in Software Development With Strategic AI Solutions
While AI-enhanced low-code platforms offer significant advantages, they introduce specific challenges that require strategic approaches. OutSystems has identified critical concerns, including quality assurance, security integration, and maintaining appropriate human oversight in increasingly automated development processes.
Quality validation, such as the application of AI evaluation metrics, becomes particularly crucial as development accelerates. OutSystems addresses this through automated testing frameworks and built-in validation processes that continuously evaluate applications against enterprise standards.
These mechanisms operate alongside development rather than as separate phases, preserving speed while ensuring technical excellence.
"Even as we automate more aspects of development, human expertise remains essential for evaluating context and appropriateness," Coutinho emphasizes. OutSystems deliberately structures their AI capabilities to augment rather than replace developer judgment, recognizing that balancing automation with expertise produces optimal results.
Security integration presents another significant challenge as development barriers lower, especially considering open-source LLM challenges. OutSystems approaches this through architectural guardrails that automatically implement security best practices and compliance requirements. These embedded protections help prevent common vulnerabilities without requiring developers to maintain specialized security expertise.
The risk of technical divergence increases as more stakeholders contribute to development. OutSystems addresses this through governance frameworks that maintain architectural consistency while enabling broad participation.
These structures help organizations balance democratization with necessary standards, preventing the proliferation of disconnected solutions that ultimately increase maintenance complexity.
As organizations adopt these technologies, OutSystems recommends phased implementation approaches that gradually expand capabilities while establishing appropriate governance structures. This measured adoption helps teams develop the skills and processes needed to maximize value while managing associated risks.
The Future of Software Development With AI and Low-Code
Looking ahead, the integration of AI and low-code development will likely transform software engineering education and career paths fundamentally. As Coutinho envisions, "In the future, we may see software engineering curricula that focus more on solution architecture and business value creation rather than programming language specifics."
This shift would prepare the next generation of developers to leverage AI-powered tools that handle implementation details while they focus on higher-order problem-solving.
The enterprise application landscape will likely evolve toward composable architectures where AI assists in assembling and optimizing pre-built components based on business requirements. This could eliminate the traditional distinction between "custom" and "off-the-shelf" software, creating a continuum where solutions are rapidly assembled from standardized building blocks but customized through intelligent adaptation to specific business contexts.
Galileo's platform embodies this forward-looking approach by providing robust evaluation, monitoring, and protection capabilities for AI applications. Galileo creates an environment where rapid iteration remains secure and reliable, allowing organizations to fully leverage the accelerated development cycles that AI systems enable without compromising on governance or quality.
Explore Galileo today platform to address many of the challenges Coutinho and Sanyal discussed around quality, security, and governance in AI systems.
For more insights, listen to the complete podcast for more on how these technologies are reshaping development practices today and what's coming next. And check out other Chain of Thought episodes, where we break down complex Generative AI concepts into actionable strategies for software engineers and AI leaders.
Software development is changing. The space is undergoing a profound transformation, driven by the convergence of low-code platforms and artificial intelligence.
This shift was the focus of a recent episode of Chain of Thought, where host Conor Bronsdon, Head of Developer Awareness at Galileo, and co-host Atindriyo Sanyal, the CTO and Co-Founder of Galileo, had an engaging conversation with Rodrigo Coutinho, Co-Founder and AI Product Manager at OutSystems.
OutSystems has pioneered the integration of AI into low-code development tools, creating an ecosystem where developers can rapidly innovate and deliver enterprise applications. Their approach fundamentally changes development dynamics by compressing what once took weeks into mere moments.
"The ability to do these iterations in seconds completely changes the way you work," Coutinho observed during the conversation. This acceleration isn't merely about speed—it represents a paradigm shift in how software adapts to business needs, enabling developers to create immediate value through accessible tools that maintain professional quality.
How Low-Code Tools Enhance Speed and Efficiency
Traditional software development follows linear paths with extended feedback loops. Low-code platforms disrupt this model by enabling real-time development and validation. The immediacy of this approach transforms collaborative processes between technical teams and stakeholders.
Accelerating Development Timelines
The compression of development timelines represents perhaps the most tangible impact of low-code platforms. Projects that traditionally required months now conclude in weeks or even days. This acceleration doesn't sacrifice quality but rather redistributes development effort toward higher-value activities.
"Now you can ask someone what they want. You do it live, and you have, in seconds, a prototype of what the person told you they wanted," Coutinho explains. This capability reshapes planning sessions into dynamic creation workshops where ideas materialize instantly, allowing teams to refine concepts on the fly rather than waiting for the next development cycle.
Coutinho further characterizes these tools as "superpowers" that fundamentally alter resource allocation and market responsiveness. Organizations in highly regulated industries benefit particularly, as compliance requirements can be rapidly incorporated into applications without extensive delays. A financial institution, for instance, might iterate through multiple versions of a regulatory reporting system within a single sprint rather than enduring months of development.
These efficiency gains extend well beyond initial development. When market conditions or business requirements change, applications can evolve in near real-time, preventing the accumulation of technical debt that plagues traditional development approaches. This adaptability creates a sustainable competitive advantage, especially in dynamic industries where responsiveness determines market position.
Reducing Technical Debt Through Continuous Iteration
Low-code platforms fundamentally transform how organizations manage technical debt by enabling continuous refinement of applications. Leveraging practices like Continuous Integration for AI, organizations can systematically update low-code applications without extensive refactoring.
Coutinho explains how "the ability to modernize applications incrementally rather than through massive rewrites changes the economics of software maintenance". This ongoing evolution helps organizations avoid the resource-intensive rebuilds that typically occur when technical debt reaches critical levels.
The visual nature of low-code development also improves documentation by default, as the platforms maintain clear representations of application architecture and workflows. This transparency reduces the knowledge barriers that typically contribute to technical debt when team members transition or when applications require modification after extended periods.
Organizations using these platforms report significant reductions in maintenance costs, with resources previously dedicated to supporting legacy systems now redirected toward innovation initiatives that drive business value. This shift creates a virtuous cycle where reduced technical burden enables more rapid response to emerging opportunities.
Bridging Expertise Levels
The democratization of development represents one of the most promising aspects of AI-enhanced low-code platforms. These systems, including the use of AI agents, create scaffolding that enables less experienced developers to contribute meaningfully to complex projects.
"We started investing in AI back in 2018 specifically to help developers be more productive and create better enterprise applications," said Coutinho, highlighting OutSystems' early recognition of AI's potential. This investment materialized in tools like Mentor, which can generate complete enterprise applications from requirement documents while incorporating architectural best practices.
This evolution redefines the developer's role within organizations, emphasizing the importance of AI fluency in validating code, ensuring quality, and orchestrating components. The shift opens new career pathways focused on solution architecture and business analysis rather than syntax mastery, allowing technical professionals to concentrate on creating business value through technology rather than wrestling with implementation details.
Aligning Software With Business Objectives
Perhaps the most significant impact of these platforms lies in their ability to bridge the persistent gap between business requirements and technical implementation. Traditional development processes often produced solutions that gradually diverged from original business objectives through layers of translation and documentation.
The immediacy of low-code development creates a shared visual language between technical and non-technical stakeholders. "Iterating in seconds during a meeting completely changes your workflow," Coutinho emphasizes. When a business analyst describes a needed feature, developers can model it instantly, enabling immediate refinement and ensuring alignment between vision and execution.
This accessibility extends beyond traditional development teams, enabling domain experts to participate directly in the creation process and maximize AI for business value. This evolution is a prime example of AI in human interactions, where technology facilitates closer collaboration and co-creation. This direct involvement embeds crucial domain expertise into applications, resulting in solutions that intuitively match workflow requirements and drive higher adoption rates.
Navigating Challenges in Software Development With Strategic AI Solutions
While AI-enhanced low-code platforms offer significant advantages, they introduce specific challenges that require strategic approaches. OutSystems has identified critical concerns, including quality assurance, security integration, and maintaining appropriate human oversight in increasingly automated development processes.
Quality validation, such as the application of AI evaluation metrics, becomes particularly crucial as development accelerates. OutSystems addresses this through automated testing frameworks and built-in validation processes that continuously evaluate applications against enterprise standards.
These mechanisms operate alongside development rather than as separate phases, preserving speed while ensuring technical excellence.
"Even as we automate more aspects of development, human expertise remains essential for evaluating context and appropriateness," Coutinho emphasizes. OutSystems deliberately structures their AI capabilities to augment rather than replace developer judgment, recognizing that balancing automation with expertise produces optimal results.
Security integration presents another significant challenge as development barriers lower, especially considering open-source LLM challenges. OutSystems approaches this through architectural guardrails that automatically implement security best practices and compliance requirements. These embedded protections help prevent common vulnerabilities without requiring developers to maintain specialized security expertise.
The risk of technical divergence increases as more stakeholders contribute to development. OutSystems addresses this through governance frameworks that maintain architectural consistency while enabling broad participation.
These structures help organizations balance democratization with necessary standards, preventing the proliferation of disconnected solutions that ultimately increase maintenance complexity.
As organizations adopt these technologies, OutSystems recommends phased implementation approaches that gradually expand capabilities while establishing appropriate governance structures. This measured adoption helps teams develop the skills and processes needed to maximize value while managing associated risks.
The Future of Software Development With AI and Low-Code
Looking ahead, the integration of AI and low-code development will likely transform software engineering education and career paths fundamentally. As Coutinho envisions, "In the future, we may see software engineering curricula that focus more on solution architecture and business value creation rather than programming language specifics."
This shift would prepare the next generation of developers to leverage AI-powered tools that handle implementation details while they focus on higher-order problem-solving.
The enterprise application landscape will likely evolve toward composable architectures where AI assists in assembling and optimizing pre-built components based on business requirements. This could eliminate the traditional distinction between "custom" and "off-the-shelf" software, creating a continuum where solutions are rapidly assembled from standardized building blocks but customized through intelligent adaptation to specific business contexts.
Galileo's platform embodies this forward-looking approach by providing robust evaluation, monitoring, and protection capabilities for AI applications. Galileo creates an environment where rapid iteration remains secure and reliable, allowing organizations to fully leverage the accelerated development cycles that AI systems enable without compromising on governance or quality.
Explore Galileo today platform to address many of the challenges Coutinho and Sanyal discussed around quality, security, and governance in AI systems.
For more insights, listen to the complete podcast for more on how these technologies are reshaping development practices today and what's coming next. And check out other Chain of Thought episodes, where we break down complex Generative AI concepts into actionable strategies for software engineers and AI leaders.
Conor Bronsdon
Conor Bronsdon
Conor Bronsdon
Conor Bronsdon