Generative AI: The Little Things

I know everyone and their dog has been talking about generative AI and all the exciting opportunities it offers. However, sometimes it’s the simple things that have the most profound impact. For me, Alexa was a game-changer when I could ask it how to spell a specific word.

Now, with tools like ChatGPT and Bard, I’m finding their proofreading capabilities to be incredibly helpful! Like many software engineers, the neurodivergence that aids me in building software also makes proofreading exceptionally challenging.

When I’ve written white papers or crucial proposals in the past, I’ve often had to meticulously go through the content line by line. I’d start from the bottom, working my way up, reading each line out loud three times to even come close to producing something error-free. Now, with so many tools at my disposal (including for this post!), I can simply paste my text into ChatGPT, kindly request a proofread, and off we go!

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Ask Your Developer

Ask Your Developer: How to Prosper in a ‘Build or Die’ Business Landscape” by Twilio CEO Jeff Lawson is an outstanding book for numerous reasons. Most notably, Lawson delves deep into the significance of integrating engineering needs into the business and emphasizes the importance of maintaining frequent and effective communication with engineers.

All too often, I’ve witnessed software planning and discussions taking place in secluded meetings or sessions involving sales teams, account managers, and senior IT managers, but excluding the very people who will be building the software. Regrettably, I’ve sometimes been that IT manager. At its core, software development is a collaborative process that demands consistent and clear communication. This ensures all stakeholders understand what they are building, what they will receive, and the value it will bring.

Another pivotal aspect of Lawson’s approach is framing any piece of work for an engineer as a problem that needs a solution, rather than a task to be completed. Managers frequently fall into the trap of dictating to engineers how to address an issue, rather than allowing engineers to leverage their extensive technical expertise to devise a solution. Managers should pinpoint the problems (or opportunities), while engineers should be entrusted to resolve those problems (or capitalize on the opportunities).

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Taking the Leap

How do you decide when it’s time to take the leap? regardless of what that leap might be?

It’s challenging to truly convey the intense anxiety and fear that accompanies the switch from one airline reservation system to another. After what feels like an eternity of managing spreadsheets, determining fare bases, setting baggage allowances, comparing economy to premium economy equivalents, and juggling a myriad of other variables, there comes a pivotal moment. Sales are halted, and all existing tickets are converted into new ones with new booking codes. In just a few hours, everything will either proceed smoothly, allowing customers to purchase flights, check in, and perform all the expected tasks, or the entire system will come to a standstill, leading to widespread panic.

For me, the most significant insights are these: The go/no-go decision-making process has its time and place. It’s crucial not to take that leap until you’ve done everything possible to mitigate the risks. However, there comes a moment when you simply have to take the plunge, see where you end up, and then continue pushing forward. Fortunately, when we faced this challenge, everything worked out in the end. But I’ll never forget that day and the overwhelming fear it brought!

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When Life Goes Wrong

Life is unpredictable. Somewhere in the midst of 2015, the brilliant startup company I was part of turned out to be not so brilliant, and it fell apart. I had exhausted all my savings, and when the paychecks ceased, I spent three months supporting my family solely on credit cards. A promising opportunity emerged, contracts were drafted, but it never came to fruition. Then, another exciting chance in IoT presented itself. Just after they made an offer, but before anything was finalized, the company was acquired, and all hiring was halted.

Out of sheer necessity, I found myself working at a regional airline. This unexpected turn proved to be transformative, largely due to the incredible colleagues and mentorship I received (a special shoutout to Colin Lewis!). Additionally, we embarked on an extensive digital transformation, introducing a new website, check-in systems, and a revamped ticketing system. This experience provided me with a deep understanding of how airline ticketing systems operate.

From there, my career trajectory was swift. I evolved into roles such as a technical architect, product manager, and now, a CTO for product-based software. Throughout this journey, I constantly battled the nagging feeling that I wasn’t good enough, a sentiment rooted in the memory of the failed startup. There are profound lessons to be gleaned from failures, but even more significant lessons emerge when things go unexpectedly well. It’s crucial to resist doubting your worth and to understand that you’re as valid as anyone else. The true lesson lies in humility. If you believe you’re superior to everyone else, you inadvertently position yourself to feel inferior as well. The essence, I believe, is to trust that, like everyone else, you have a valuable contribution to make!

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Rock Star Engineers

Rock-star software engineers are not necessarily the best engineers. They might be engineers who have plateaued in their growth or gatekeepers hindering the progress of your software. Truly impactful software is developed within a communityโ€”a community that thrives on innovation, standardized practices, clear code with comprehensive comments, and meticulous planning followed by execution. Such communities require effective leadersโ€”leaders who amplify the strengths of their members, address their weaknesses, and clear hurdles to enable them to contribute optimally. The ‘rock-star’ archetype doesn’t typically offer these qualities. Instead, we should be lauding the collaborators who possess a clear vision and the capability to realize itโ€”the unsung heroes who drive progress.

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Building a Strong Foundation for AI and Innovation: How to Herd Genius Cats

Companies seeking to build ethical and robust AI systems face immense challenges. Key among them is establishing an effective framework to guide development and deployment. This requires laying a strong foundation that promotes responsible innovation from the ground up.

According to industry thought leaders, a critical first step is assembling diverse, multidisciplinary teams. Different perspectives are crucial for identifying potential pitfalls and unintended consequences early on. Fostering a collaborative “herd genius” environment allows teams to tap into collective intelligence. It enables them to approach AI with nuance, foresight and care.

Structuring teams and workflows in an intentional way establishes the right cultural tone. This empowers teams to build human-centric AI systems that earn public trust. With a robust foundation in place, companies can innovate responsibly and help realize AI’s immense potential for good.

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Innovation has always been resisted: here is what to do about it

Throughout history, innovative new technologies have often been met with fear and scepticism. AI is no different. Many worry it will displace jobs, infringe on privacy, or otherwise disrupt the status quo.

But as author Ben Waymark argues, resistance is not wholly unfounded. Past innovations, from the printing press to electricity, did in fact radically transform societies. The key is channeling that apprehension into productive discussion and responsible policies.

Rather than reflexively rejecting AI, we must proactively shape its development. This requires engaging diverse voices, considering ethical implications, and establishing sensible safeguards. With care and foresight, we can maximize AI’s benefits while minimizing risks.

Dismissing concerns outright will only breed mistrust. But working collectively to address valid critiques will lead to wiser innovations. If we learn from the past, AI can positively transform our world and improve life for all.

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