Training dogs has been a personal passion of mine since I was a teenager, and through this journey, I've seen shifts not only in my approach but also in the broader field of dog training. Initially, my methods were quite harsh, rooted in misconceptions about canine emotions and behavior. The prevailing belief was that dogs were either indifferent to pain or scheming to dominate their owners, leading to punitive training techniques that were less about understanding and more about control.

In those early years, training focused on command and compliance. A dog would receive a command, often without understanding, and then be physically coerced into performing the desired action, followed by praise. Some trainers began to adopt slightly more humane methods, like using treats to lure dogs into the correct position before enforcing commands.

However, my perspective shifted significantly when I was introduced to techniques rooted in behavioral psychology, particularly those developed for marine mammals. Unlike dogs, these animals cannot be physically moved into position, which led to the development of operant conditioning—where the learner interacts with their environment to achieve desired outcomes.

The groundwork for these techniques was laid by psychologist B.F. Skinner and later refined by practitioners like Keller and Marion Breland. Their work demonstrated that effective training hinges on rewarding desired behaviors rather than relying on punishment for undesirable actions.

While I won't delve too deeply into the science, I want to highlight practical takeaways that can be applied to both animal and human training. One insight that resonates with me is the idea that training often falters because individuals set unrealistic expectations for their animals while underestimating their own responsibilities.

The broader question I ponder is: "Have I done everything possible to support this individual or animal's success?" If not, placing blame seems unfair.

In the tech industry, I observe many so-called thought leaders advocating practices that could lead to detrimental outcomes for those who follow their advice. When sharing ideas publicly, it’s essential to consider the consequences of those recommendations.

A critical principle I apply is known as the "Dead Dog Rule." If a dead dog could execute a behavior, then it’s not a trainable action. For instance, if one wishes to train a dog not to jump upon arrival at home, they must first clarify what behavior they actually want to encourage. Perhaps the goal is for the dog to calmly lie on a mat until the owner is ready for interaction—this is a behavior that can be taught.

In software development, I often encounter bug reports that outline what shouldn’t happen without specifying what should occur instead. This highlights the importance of clear requirements; they should articulate explicit outcomes rather than merely pointing out deficiencies.

To foster effective behavior, one must first ensure that the desired behavior is consistently achievable. New trainers sometimes wait passively for the dog to perform a desired action before offering praise, but a more effective strategy involves creating an environment where the desired behavior is likely to occur.

Similarly, in software development, it’s unrealistic to expect developers to consistently produce quality code if they haven’t had the opportunity to see or create good code previously.

Setting up conditions for success is vital. When I started training my first dog, I wouldn't have thought to encourage her to lie on a mat. My earlier approach would have involved command and coercion, but positive reinforcement has shown me that rewarding incremental progress leads to better outcomes.

In many workplaces, onboarding processes are often chaotic and poorly documented, leaving new developers to navigate a frustrating maze of expectations. Consequently, these developers can struggle to contribute effectively, leading to increased inefficiency and frustration across the team.

My approach is proactive; I consider the resources new hires will need before they start. However, unexpected situations can arise, requiring rapid adjustments to ensure they become productive quickly.

In dog training, the principle of reinforcement dictates that behavior is shaped by the consequences that follow. If a dog learns that certain actions yield rewards, they will be more likely to repeat those behaviors. The same applies to developers; if they are rewarded for hastily assembled code, they may struggle to produce higher-quality work when the time comes for refinement.

It's crucial to reinforce the behaviors we want to see. For instance, if a developer is rewarded for cutting corners to meet deadlines, they may not develop the skills necessary for writing maintainable code. When time is finally allocated for cleanup, developers may find themselves lacking the skills they didn't practice.

The concept of "being a splitter, not a lumper" resonates strongly in both dog training and tech leadership. This means breaking down skills into manageable parts, making it easier to learn and master them. For example, when teaching a dog to heel, I begin with simpler tasks that build towards the final goal.

As a tech lead, I see myself as an instructor, helping my team navigate the specific practices we value. Good engineering practices allow me to present code in a way that helps developers grasp our processes more effectively.

The mnemonic D.A.S.H—Desire, Accuracy, Speed, Habitat—summarizes key principles that apply to both dog training and software development.

• Desire: A positive attitude is essential for success. Teams that feel supported are more likely to thrive.
• Accuracy: Focusing on accuracy during learning phases leads to better long-term outcomes.
• Speed: Developers who understand the fundamentals will work more efficiently than those who rush through their learning.
• Habitat: Skills should be transferable across different environments, as context can alter performance.

Navigating new work environments can feel like starting from scratch, and it's essential to recognize that rapid adaptation is a skill in itself. Leaders play a pivotal role in helping team members acclimate swiftly.

Ultimately, recognizing that your dog is doing their best with the training provided is crucial. Often, what appears as stubbornness can be traced back to environmental factors or gaps in training. The solution lies in identifying these gaps and addressing them rather than assigning blame.

In the tech world, junior developers often find themselves overwhelmed, thrust into complex environments with little guidance. Conversely, senior developers face rigorous interviews that may overlook the fact that every new hire will require some onboarding.

Success in transitioning from junior to senior developer can sometimes feel arbitrary, hinging on individual aptitude or the availability of effective mentorship. A supportive tech lead can be instrumental in this journey, while ineffective leadership can hinder growth and even push talented individuals out of the field.

As tech leads, we must recognize that our expertise in coding doesn't automatically translate to effective teaching or mentoring. We too must develop these skills, as there’s no definitive guide to balancing project momentum with providing appropriate challenges for less experienced developers.

Finally, it's important to grant ourselves the grace to learn in our roles. While we bear increased responsibilities compared to our previous positions, mastery takes time and practice.

Afterword: I won't be addressing dog training queries in the comments. For more information on dog training, consider checking out the Shaped by Dog podcast by Susan Garrett or the Kikopup YouTube channel.