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Will your next coworker be an Agentic AI? The Artificial Intelligence revolution with Agency

Artificial Intelligence (AI) has moved from being a futuristic promise to a tangible reality that is redefining how we work. Beyond generative models that create text or images, a new wave of innovation is emerging: Agentic AI. At GreenSQA, we are exploring this transformative concept in depth.

What is Agentic AI and why does it matter?

Agentic AI is not just an evolution, it’s a revolution in software autonomy. While generative AI focuses on creating content (text, images, video), Agentic AI goes further: it refers to software agents capable of making decisions and executing actions autonomously to achieve a goal, with minimal or no human supervision.

Imagine a digital colleague who can:

Analyze massive volumes of data
Detect problems and suggest solutions
Coordinate tasks across business systems (CRM, ERP, email)
Even work while you sleep! Optimizing productivity 24/7

According to Gartner, Agentic AI is one of the five most strategic technologies this year, with striking projections: by 2028, an estimated 33% of enterprise software will include it, and up to 15% of daily decisions will be made autonomously by AI agents. This doesn’t mean replacing humans, but boosting productivity by up to 30%, freeing people for more complex, creative, and strategic work that drives innovation.

From thermostats to smart colleagues: The evolution of autonomous agents

The concept of an “agent” in AI is not new—its origins trace back to the 1960s with chatbots like ELIZA. An agent is any entity (hardware, software, or a combination) capable of perceiving its environment through sensors and acting upon it through actuators.

What’s new is the evolution:

Memory: Agents learn from past experiences to improve decision-making.
Planning and reasoning: They create action plans to achieve defined objectives.
Adaptability: They can navigate and act in dynamic environments, adjusting to new conditions.
Tools and control: They use other tools and APIs, but always within pre-set “guard rails” for safety.

The choreography of AI: Architectures and protocols

For multiple agents to collaborate effectively, robust architectures and well-defined communication protocols are needed. This enables smooth coordination among specialized agents, such as those dedicated to software quality evaluation, performance testing, or system monitoring.

Architectural models:

Vertical (Hierarchical): A supervising agent coordinates the work of others.
Horizontal (Network): All agents can communicate directly without a central coordinator.

Also, communication protocols include:

MCP (Model-Context Protocol): Enables agents to interact with external tools and data sources.
ANP (Agent Network Protocol): Peer-to-peer communication between agents.
ACP (Agent Communication Protocol): An open standard from IBM and the Linux Foundation for asynchronous communication.
Agent Protocol (A2A): Proposed by Google and over 500 companies—open through the Linux Foundation, supports robust asynchronous communication.

These protocols integrate into frameworks like LangChain, LangGraph, Camel AI, Crew AI, Google ADK, and IBM BAI, making it easier to build and deploy Agentic AI systems.

Building trust in autonomy: Key recommendations

At GreenSQA, we stress the importance of security and trust from the design stage:

Safety and trusting the design: Agents must align with human values and objectives, with secure shut-off mechanisms and protection against cyberattacks.
Traceability and transparency: Knowing what an agent did, how, and why through audits, monitoring, and governance.
AI Bill of Materials (AI BOM): Keep a detailed inventory of models, versions, training data, and dependencies.
Agent Persona: Define roles, ethical principles, and limitations to ensure coherent and responsible behavior.

Agentic AI in GreenSQA: Innovating in software quality

Applications we envision and apply:

Smart analysis & reporting: Specialized agents analyze testing data, generate historical reports, and perform advanced analytics—freeing human teams for strategic work.
Content generation: Agents assist in communications and marketing by summarizing meetings, extracting key insights, and creating multimedia content.
Knowledge & project management: Agents organize project histories and best practices repositories for easy access.
Automation maintenance: Detect outdated test scripts, notify teams, and auto-correct code.
Release automation: Validate acceptance criteria and deploy to production with infrastructure-as-code provisioning.
Key benefit: 300–400% time savings in testing processes, speeding up client negotiations and deliveries.

Conclusion: A Collaborative Future

Agentic AI is not a threat—it is an unprecedented opportunity to create more productive, innovative, and efficient organizations. At GreenSQA, we firmly believe that combining human intelligence with the autonomy of these agents is the path toward the future of work. We are excited to lead this conversation and apply these advanced capabilities for the benefit of our clients and teams.

Are you ready to explore how Agentic AI can transform your organization? Contact us for more information!

August 13, 2025/by GreenSQA

Software releases: More than just a launch

News, Technical Contents

Software Releases: Beyond a Simple Launch

The release of a new version is a critical moment. It is not just the act of putting a product into the hands of users—it is the culmination of an intensive cycle of work, testing, and preparation. A successful release is the result of careful orchestration, where quality, stability, and user experience are top priorities.

What does a software release really involve?

A software release refers to the formal and controlled process of making a new version of a product or system available for use. This may be for customers, end users, or even internal teams. It goes far beyond simply copying files to a server; it involves:

Thorough planning: Defining which features will be included, the release objectives, and the communication strategy.
Rigorous testing: Ensuring the software works as expected, is free from significant errors, and meets quality and security requirements.
Controlled deployment: Implementing the software in the production environment efficiently and safely.
Post-release monitoring: Tracking the performance and stability of the new version once it is live.

Common challenges in the release process

Although it may seem like a linear process, software releases often face obstacles that can delay or compromise success:

Communication issues: Lack of coordination between development, QA, operations, and marketing teams can lead to misunderstandings and errors.
Dependency management: Modern systems often rely on multiple components and services, complicating version and compatibility management.
Testing failures: Incomplete or ineffective testing can allow critical defects to reach production.
Environment inconsistencies: Differences between development, testing, and production environments can cause unexpected issues.
Complex rollbacks: Difficulty reverting to a previous version if something goes wrong can create panic and further disruptions.

Keys to a successful release

To mitigate these challenges and ensure a smooth transition, it’s vital to take a strategic approach:

Automation: Implement CI/CD tools to automate testing, builds, and deployments, reducing manual errors and speeding up the process.
Continuous testing: Integrate testing at every stage of the development cycle, from unit tests to regression and performance tests.
Consistent environments: Use containers (like Docker) or configuration management tools to ensure environments are identical.
Rollback plan: Have a clear, tested plan to revert to a previous version in case of serious issues.
Active monitoring: Deploy monitoring and alert systems that provide real-time insights into the application’s performance and behavior in production.
Cross-team collaboration: Foster open, constant communication among all teams involved in the software lifecycle.
Detailed documentation: Keep clear records of each release, including changes, known issues, and resolutions.

Software release is an art refined through experience and the adoption of best practices. By treating each launch as a critical project and focusing on preparation, automation, and collaboration, organizations can transform what used to be a stressful event into a predictable, successful process that delivers value to users.

Ready to take your quality to the next level? Contact us here

July 30, 2025/by GreenSQA

Optimizing security in the software development lifecycle

News, Technical Contents

Security in software development is no longer an afterthought—it is an integral and fundamental part of the entire lifecycle, especially in Continuous Integration and Continuous Delivery (CI/CD) environments. At GreenSQA, we understand that efficiency and quality are achieved when security is seamlessly and proactively integrated, minimizing vulnerabilities and risks throughout the process.

The Transformation of Security in CI/CD

Integrating security testing into CI/CD pipelines is crucial to identifying and addressing vulnerabilities early and efficiently. This is not about adding more layers of complexity but rather about connecting existing elements to strengthen software development and delivery. We consider the following essential:

Complete Code Visibility: It is vital to understand the flow of code from conception to deployment. This involves observing how the code moves through each stage, identifying any areas that may have been overlooked, such as hard-coded secrets or third-party library dependencies that could introduce risks.

Strategic Test Placement: Each type of security test should be positioned where it will be most effective. For example, detecting credentials or passwords in code can be done immediately after a push, while static application security testing (SAST) benefits from being executed in the earliest stages of the pipeline.

Connecting Findings to Daily Work: For security tests to be actionable, their findings must be directly linked to developers’ daily tasks, such as code reviews or issue-tracking systems. This ensures that teams have the necessary context to fix vulnerabilities quickly.

Intelligent Alerts and Noise Reduction: Limiting unnecessary alerts and prioritizing findings based on relevance is key to avoiding “security fatigue.” Setting thresholds and performing periodic reviews helps maintain focus on the most critical threats.

Automation and Smart Tools: Automation is essential to scaling security coverage. Modern tools—especially those powered by artificial intelligence—can significantly expand vulnerability detection capabilities and provide actionable insights by correlating different risk signals.

Post-Deployment Feedback and Continuous Improvement: The process does not end at deployment. It is critical to include post-deployment feedback mechanisms to track runtime vulnerabilities and trace them back to their source in the code. This not only improves long-term security but also strengthens the organization’s overall security posture. Continuous alignment of testing with compliance requirements and ongoing evolution of the testing strategy are vital for a robust and adaptable security approach.

At GreenSQA, our expertise enables us to guide organizations in implementing these practices, transforming security into a driver of innovation rather than an obstacle. By embedding security at the heart of your CI/CD, your company can deliver software faster, with greater confidence, and with significantly lower risk.

July 30, 2025/by GreenSQA

Cloud Service Delivery Models (Cloud Computing)

News, Technical Contents

Cloud Computing services are based on technology via the Internet. To be more precise, the model of providing technology services over the Internet is characterized by being scalable and flexible, since it is on demand services. These are the different presentation of services models in the cloud:

1. Infrastructure as a Service (IaaS):

Infrastructure as a Service offers computer resources equivalent to virtualized hardware, mainly comprising aspects of physical resources, such as storage, network devices, RAM, computer servers, and so on. This type of model allows us to build our own infrastructure by means of different virtual components on which we install specialized tools to execute software-testing projects. These infrastructures allow us to expand our capacity according to the specific needs of your business. Using resources such as:

Caching
Legacy
File
Networking
Security
SystemMgm
Bandwidth

2. Platform as a service (PaaS, Platform as a Service)

It provides a platform and an environment that allows developers to create applications and services that work over the Internet. PaaS services are hosted in the cloud, and users can configure and access them simply through their web browser. Therefore, this provides all the necessary environment for the executions that are demanded, from development or testing environments and equipment.

Among its advantages are: flexibility, because the customer has full control over the tools installed on his/her platform; adaptability, since you can change the characteristics according to your needs; mobility, as you can access the platform from any device just by connecting to the Internet; and speed in development, because with this infrastructure the environment will be prepared for that purpose – many include CMS.

Application Development
Decision Support
Web
Databases
APIS Management
Streaming

We are able to test these platforms from an external system that may be located in another cloud or in the facilities where software testing is required or from a TAAS (testing as a service) infrastructure.

3. Software as a Service (SaaS Software as a Service):

This model offers an end-to-end software solution that is purchased from a cloud service provider using a pay-per-use model. You rent the use of an application for your organization and users connect to it through the Internet, usually with a web browser. The availability and performance of all underlying infrastructure, middleware, software and data of the applications are the responsibility of the SAAS provider.

Usually these platforms require a parameterization and configuration of behaviors and specific rules that respond to the needs of the business while we are able to ensure that these platforms work. For this, we make use of an external system that can be located in the cloud or in the facilities from where they require performing software testing.

At GreenSQA we provide a complete and innovative solution to perform Cloud Testing, in a model on demand, at low cost and without infrastructure investment.

January 30, 2019/by GreenSQA

Appcenter for Mobile Testing

Technical Contents

For developing mobile applications, we can find huge variety of environment and frameworks; while we are developing, some questions could arise, ¿Could it run on old-version devices? ¿It is compatible with current market devices? ¿How can we test all functions with several devices and versions? ¿Might It delay the release? We might be imagining a lot of issues if we don’t test our application in the right way.

A good solution that we have been working on is Appcenter. With Appcenter we can test an application and customize a workspace; we can adjunct the compiled test and select if you like to execute it on multiple devices and versions. We could evaluate each scenario in terms of performance, resource costs, and execution. It is possible to write the test-cases in .NET code. Then we select and follow a step by step for our test-cases including the list of devices; It runs the test and shows the results. A big upside of Appcenter is that the tests are executed in a network of Non-Emulated Devices so we could have better results.

All days we can find a competitive market growing up, Appcenter helps us to build a space to release our applications tests, watch reports and figure out a decision if our application has a positive or negative behavior.

September 19, 2018/by Estefania Vega