elev8ed - Elev8ed Storieselev8ed - Elev8ed Storieshttps://www.elev8ed.io/blogsFri, 13 Mar 2026 05:54:37 -0700http://zoho.com/sites/<![CDATA[Reflecting on AI Developer Agents]]>https://www.elev8ed.io/blogs/post/aI-developer-agents-futureExplore the rise of AI developer agents and their potential impact on software development. Are they the future of coding or just hype? Uncover insights, real-world applications, and expert opinions. Join the discussion on the real promise of AI in programming today. Dive in to discover more!]]>

AI Developer Agents: Future Breakthrough or Empty Promise?

Artificial Intelligence (AI) has rapidly transformed industries, and one of the most exciting yet controversial advancements is the rise of AI developer agents. These intelligent systems promise to assist programmers by automating tasks, optimizing code, and even generating full features autonomously. But are they truly the next breakthrough, or just an overhyped experiment that hasn’t quite lived up to its promise? 🤔


The Case for AI Developer Agents 🚀

For forward-thinking technology leaders, AI developer agents offer an opportunity to accelerate innovation. By automating tedious tasks like bug detection, code refactoring, and documentation generation, these tools free up developers to focus on more creative and high-impact work. AI-powered solutions like GitHub’s Copilot and OpenAI’s advanced coding AI have already demonstrated their ability to improve efficiency and reduce technical debt.

But why stop there? Some tools take things even further. Products like Cursor, Aide, and Void are part of a new wave of "AI Code Editors" that allow developers to build entire features with just a few well-crafted prompts. Imagine skipping the repetitive grunt work and jumping straight into refining and perfecting—saving time, money, and potentially even reducing the need for large development teams. Sounds like a dream for developers, right? 💡


The Reality Check: Not Quite There Yet 😬

However, let’s not break out the celebratory confetti just yet. Not everything in AI-land is sunshine and perfectly formatted code. One major concern is the quality and reliability of AI-generated code. Tech leaders focused on operational excellence know that poorly structured, inefficient, or insecure code can create long-term technical debt. Without proper safeguards, these tools might generate software that’s difficult to maintain and scale.

Another issue? The potential erosion of core engineering skills. If teams rely too much on AI to generate code, will developers lose their problem-solving abilities? And when (not if) AI-generated code contains bugs, who will fix them? Relying too heavily on black-box AI solutions could put organizations in a tough spot if they don’t fully understand the logic behind the generated code. For businesses planning for the long haul, these concerns need to be addressed before AI developer agents become a mainstay. 


Tackling the Challenges 🛠️

To ensure AI developer agents fulfill their promise, companies should take a strategic and thoughtful approach:

  1. Human + AI Collaboration: AI should be the sidekick, not the hero. Development teams should use AI to enhance their expertise while maintaining oversight.

  2. Quality Control Mechanisms: Implement rigorous testing, peer reviews, and AI explainability measures to prevent security vulnerabilities and unmanageable code. Tools like Cursor and Aide allow developers to enforce coding standards and mitigate risks.

  3. Strategic Integration: Rather than rushing into AI adoption, companies should align AI developer agents with their actual business goals, ensuring AI enhances workflows rather than creating unnecessary disruptions.


The Future Is Almost Here ✨

For those leading digital transformation, AI developer agents represent both an incredible opportunity and a unique challenge. While these tools could revolutionize development by boosting efficiency and innovation, they must be implemented with care. As with any transformative technology, success lies in strategic adoption—leveraging AI where it truly adds value while keeping human expertise at the core.

So, are AI developer agents the next big thing or just another overhyped trend? The answer depends on how they’re used. With the right approach, they could be a game-changer. Without it, they might just be another flashy tool that never quite takes off. 🚀

]]>Wed, 29 Jan 2025 17:02:02 -0500<![CDATA[Beyond Transformation: Evolutionary Agility]]>https://www.elev8ed.io/blogs/post/beyond-transformation-evolutionary-agilty

First - A Quick Rant

Stop trying to "Transform" your organization. It's not the correct long term cure for your organizational pains.


It simply sets the wrong mindset for folks, as transformations are inherently viewed as a "one and done" approach, which is very rarely the case. In addition, it often implies a sudden, all-encompassing change that can lead to resistance, confusion,

and a lack of sustainable improvements.


We've certainly seen it and sure there are now many examples/case studies highlighting where rigid transformations have unfortunately led to a "cargo cult" mentality, where the practices are simply adopted without understanding the underlying principles.


What instead then? Learn to Evolve...

So if merely attempting a transformation is misguided then what can we do instead? I'd like to suggest that a more nuanced approach of learning and evolving toward excellence over time is far more beneficial. 


Remember the overarching goals of shifting to be a more "agile" organization is to increase our speed to market and improve our responsiveness to change. Fundamentally we need to instill the better mindset within folks that we are focused on continuous improvement, adaptability, and team collaboration, rather than just a adopting a set of practices, frameworks or tools. We all know that that treating things as a checklist or a one-time project undermines its potential to drive genuine change.


By embracing an evolutionary mindset we allow for the gradual adoption of better practices, tailored to the organization's unique context and challenges. There are also some intrinsic benefits of this approach, such as increased buy-in from team members, better alignment with organizational culture, and the ability to adapt the practices over time.


So how do we do it?

Without hopefully sounding to cliche about it, be "evolutionary" with your evolution. Or perhaps intentionally being cliche about it, be "agile" with your agile adoption. Start with small, manageable changes, fostering a culture of learning and experimentation, and involve the teams in the process of shaping the actual practices. It also can't be understated, but the importance of leadership buying in and harboring an environment where better practices can evolve organically is crucial. To borrow an adapted quote from the Dune books/movies...


"I must not fear. Fear is the change killer."


The Short Story

Changing how we work is hard. Always has been and always will be. Especially when it relates to us humans being involved. 


However, we've learned through experience that evolving better practices over time is more effective and sustainable than attempting a forced transformation. We'll be far more successful if we can help our organizations adopt a mindset of continuous learning and adaptability in the journey towards becoming better than we are now.


Wanna dig in deeper?

Contact Us
]]>Thu, 04 Apr 2024 17:07:25 -0400<![CDATA[Escaped Defects]]>https://www.elev8ed.io/blogs/post/escaped-defects
I was tempted to inject a typo in this post just for the irony. If you find it, post in the comments. ;-)

Software development is challenging. In an agile world, baking quality in—defect prevention—is the norm, or at least it should be. Done well, this kind of development can be incredibly rewarding and the feedback loops are almost instantaneous.

When teams are test driving, the world of software development simply shows up differently. Working, Tested Product is the primary measure of progress and the value of new functionality for changes can be recognized by customers quickly. Automation and quality is central to making that possible, but not everyone has built out Continuous Integration (CI) and Continuous Delivery (CD) such that something built today can also be tested and released to Production on the same day.

Teams that have established Definitions of Done, (DoD) including code quality standards and testing standards and automation throughout enjoy a different existence than the vast majority of teams that I have encountered.

Agile nirvana is rare, at least in my experience.

For a lot of organizations, development is separate from testing and developers may not sit with or even collaborate with testers. Work moves like a virtual assembly line from one person to the next; one environment to the next. For many organizations, the journey from development to Production (left to right) looks similar to the diagram below. 
With multiple stages of testing through multiple environments--an assembly line approach to testing--an issue can arise in any one of them. In fact, when software is not test driven, finding issues in these environments can be considered the norm.

When things go wrong though, issues can cause organizations real discomfort. Escaped defects are a pain and it is critical to ferret them out before they get to Production. For some organizations an “Escaped Defect” is an issue that is found in Production, but I believe that sets the bar too low. In my book, an escaped defect is any issue that is discovered after the development team is done with it. That means a separate defect is logged for anything found after it leaves the “Development Environments” depicted on the left in Green in the diagram above.
Escaped defects are a critical quality metric. The cost of addressing a defect increases significantly the later it is found. Remediation and then retesting are all incremental costs that basically double the cost of solution delivery. For every escaped defect, the organization is basically paying for the defect that was originally created and then paying again when it is remediated. Basically, at least twice the cost for any value that involves a defect.
In my view, those cost increase in a non-linear way. The later a defect is found, the more backflow it produces for remediation. The cost of backflow means that not just the functional code has to be rebuilt, but the test code associated with it as well. Each phase of testing may have separate test code that is affected by the changed functionality. The cost can increase exponentially depending on the extent of the defect.

The solution of course is to never produce a defect. If only the real world were that simple. Learning to test drive and evolving a DoD can help a team continually raise the quality bar and move closer to defect prevention rather than a sole reliance on defect detection. As the team learns, the DoD can change to reflect the new capabilities. Any team that is just learning TDD should not start with a quality standard of 80% automated test code coverage. It is just not realistic, and automated test code coverage may not be the most critical metric to track. Whatever metric you choose, start where you are and then increase the standard as the team develops the capability to meet it.

There are three key take-aways I want you to get from this:

  1. Traditional defect detection is an expensive way to ensure quality. Defect prevention is the ultimate goal. Just think if we could only have had today’s forward-looking radar on the bow of the Titanic.
  2. Start as early as you can with Software Craftsmanship and adoption of Test Driven Development. Agile organizations are continually working toward bulletproof quality, full stack test automation, CI & CD, and the sooner you can get started the better.
  3. The goal is to not just “do Agile”, but to “be agile” and escaped defects can be used as a barometer for progress towards that agility. As the number of them goes down, agility goes up.

The road to agility can sometimes be long and winding. The quality of your code and your products is central to making it successfully. Declare war on your escaped defects! Track the amount of backflow you are experiencing by designating every issue that is uncovered after a team has declared a story done as an escaped defect. Live in the pain of the imperfection and use defects as a forcing function to raise the bar on quality. Hemming and hawing about when a defect should be logged only muddies the waters. If a team said it was done and then more work gets uncovered later, declare it a defect and learn what needs to change in your process, skillset, tooling or whatever in order to prevent similar defects in the future.

Did you find the typo? I may not have had the heart to add it.

Happy Journeying.

Get Started Now
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