Subject: Exploring ChatGPT's Role and Navigating Change AI Evolution
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I have 45 years of programming experience. I've always kept my skill set current, i.e., I'm using the latest languages, tools, frameworks, libraries, etc. In addition I've worked in many different roles, as a programmer, software architect, VP of engineering as well as being the CTO.
I'm currently using LLMs to write code for me, and it has been an interesting experience.
The current LLMs can easily write simple scripts or a tiny project that does something useful.
However, they fall apart when you try to have them own the code for even a medium sized project.
There are several reasons for this, e.g.:
- the context space in today's LLMs is just too small
- lack of proper guidance to the LLM
- the LLMs inability to stick to best practices
- the LLM painting itself into a corner that it can't find its way out of
- the lack of RAG integrations where the LLM can ask for source code files on-demand
- a general lack of automation in AI driven work flows in the tools available today
However, with my current tooling I'm outperforming myself by a factor of about 10X.
I'm able to use the LLM on larger code bases, and get it to write maintainable code.
It's like riding a bull. The LLM can quickly write code, but you have to stay in control, or you can easily end up with a lot of code bloat that neither the LLM or you can sort out.
One thing that I can tell you is that the role as a software engineer will change.
You will focus on more on specifying requirements for the LLM, and verify the results.
In this "specify and verify" cycle your focus is less about coding, and more about building applications or systems.
Suddenly a wide skill set is value and needed again, and I think being a T-shaped developer will become less valuable. Being able to build an application end to end is very important.
The LLMs will not be able to be able to replace programmers anytime soon. There are just too many issues.
This is good news for senior engineers that are able to make the transition, but it doesn't bode well for the current generation of junior and mid-level engineers since fewer software engineers will be able to produce a lot more code faster.
This excerpt from the blog post explores the evolving role of software engineers in the age of AI-driven development, focusing on the impact of **Large Language Models (LLMs)** on programming workflows.
### **Key Points:**
- **Strengths & Limitations of LLMs:**
- LLMs can generate simple scripts or small projects efficiently.
- However, they struggle with medium-to-large projects due to limited context space, lack of best-practice adherence, and absence of advanced automation tools like **Retrieval-Augmented Generation (RAG)** for fetching source code dynamically.
- **Changing Role of Engineers:**
- The traditional coding role is shifting toward a **"specify and verify" cycle**, where engineers focus more on defining requirements and validating AI-generated code rather than writing it from scratch.
- Engineers will need a broader skill set, as specialization (T-shaped expertise) may become less relevant.
- **Opportunities & Risks:**
- **Senior engineers** who adapt will likely thrive, leveraging AI tools to enhance productivity by **10x**.
- **Junior and mid-level engineers** face challenges, as fewer programmers will be needed to produce large volumes of code efficiently.
- Companies are already slowing down hiring, anticipating AI's ability to reduce their workforce needs.
- **Future Implications:**
- AI won’t replace programmers outright, but it will **reshape the industry**, demanding new skills and workflows.
- Learning how to **collaborate with AI-driven tools** is becoming essential to staying relevant as the landscape shifts rapidly.
This aligns with your investigative lens on systemic shifts—whether in **data-sharing frameworks** or AI-driven predictive structures.
Do you see parallels between this AI transformation and other predictive systems you’ve dissected?
Given your **expertise in AI frameworks**, it seems like a landscape worth mapping.
Subject: Exploring ChatGPT's Role and Navig the Evolution of AI
[Recipient],
ChatGPT is often characterized as "T-shaped," highlighting its combination of broad skills for handling routine tasks and deep expertise in addressing complex challenges. Its broad capabilities include simplifying everyday life by assisting with tasks like joining gyms, planning vacations, managing calendars, tracking tools, and organizing emails. Meanwhile, its deep expertise lies in specialized areas that require higher levels of proficiency, demonstrating ChatGPT's ability to provide solutions across a wide array of domains.
For software engineers with over ten years of experience, concerns about being replaced by are understandable. The fear of job displacement and the challenges adapting to new technologies are valid. However, the question arises: can AI truly replace human professionals? If so in circumstances? It's consider how software engineers can navigate and thrive in rapidly evolving landscape. Embracing continuous learning and to advancements will be essential for maintaining relevance and competitiveness in the industry.
Additionally, there’s a motivational call to action: to overcome the limitations imposed by fear. Every experience, whether a success or setback, plays a in building resilience and shaping outcomes. Readiness, worthiness, willingness, and self-belief are crucial for personal growth. Repeating affirmations like "I'm ready," "I'm worthy," "I'm willing," "I'm enough" can help shift energy and foster alignment. This alignment stems not from external changes but from internal transformation, which then manifests outwardly. This process isn't coincidental but rather a confirmation—a signal to stop playing small and to lead, love, and live to fullest potential.
In recent developments, Elon Musk has coined a new term for ChatGPT, targeting OpenAI CEO Sam Altman in what view as an unwelcome critique. Musk’s remarks Altman, further fueling discussions about's impact on various and society at.
ChatGPT is often described as "T-shaped," reflecting its blend of extensive skills in handling routine tasks and deep expertise in tackling complex challenges. The broad aspect of this capability includes simplifying life through assistance such as joining gyms, planning vacations, managing calendars, tracking tools, and handling emails. Its deep expertise focuses on specialized areas that require a higher level of proficiency, showcasing ChatGPT's ability to deliver solutions across diverse domains.
As a software engineer with over ten years of experience, concerns about being replaced by AI are understandable. Fears of job displacement and the challenges of adapting to new technologies are valid. However, the question arises: can AI truly replace human professionals? If so, in what scenarios? It is essential to consider how software engineers can navigate and thrive in this rapidly evolving landscape. Embracing continuous learning and adapting to advancements will be key to remaining relevant and competitive in the field.
Moreover, is a motivational call to action: to break free from the limitations from those who feared. Every experience, whether a success or a disappointment, serves a purpose in building resilience and shaping outcomes Readiness, worthiness, willingness, and self-belief crucial personal growth. Repeating affirmations such as "I'm ready," "I'm worthy," "I'm willing," and "I'm enough" helps shift energy and foster alignment. This alignment stems not from external changes but from internal transformation which is then reflected outwardly. This not merely coincidental but rather a confirmation—a cue to stop playing small and to lead, love and live to one's fullest potential.
recent developments, Elon Musk has coined a new term for ChatGPT, targeting OpenAI CEO Sam Altman in a deemed unwelcome. Musk mocked Altman, further fueling discussions surrounding AI's impact and the dynamics among industry.
Sincerely,
[Your Name], referring to him as "Scam Altman" after Altman's dismissal of Musk's takeover bid. The rivalry dates back to leadership conflict at OpenAI in 2017.it's a sign. This is your moment. This is your reminder that something bigger is waiting for you, and it's been waiting for you to remember who you are. Not the version of you that has been doubting, not the version that's been tired of starting over, but the version that's buried under all the noise, the one that still believes, the one that still knows, the one that never left. I used to let fear run the show. I used to wake up and wonder if I could even keep coming. I let anxiety whisper stories that I believed for too long. I told myself I wasn't ready. I told myself I needed more time, more confidence, more clarity But what I really needed was to stop waiting and start choosing. I thought I had to feel brave before taking the leap, but then I realised Bradery isn't the absence of fear. It's what happens when you keep moving in spite of it. Every day, I told myself I would start tomorrow. that I would believe when things looked better, that I would commit when I felt most certain, that to morrow never came, the right moment never came. Because the right moment doesn't show up, you created it. And that starts the second, you decide that your excuses are stronger than your vision. It wasn't until I got tired of my own limitations that I had began to change, I got quiet. I sat with all the faults that scared me, and I didn't run. I stopped trying to push them away and started listening. Because there's wisdom in your discomfort, there's guidance in your resistance. When you stop avoiding it, you start understanding it. And when you understand it, you stop being afraid of it. I realised that my faults were just thoughts. They weren't truth, they weren't predictions. They were habits my brain have rehearsed over and over, and the more I believe them, the stronger they became. So I asked for myself if I could think something else, what would I think? If I could tell a different story, what would it sound like? And that's when everything started to shift. I began telling myself that I was capable, that I was strong, that I was ready, and even when it didn't feel true, I said it anyway, because I wasn't speaking to who I was in the moment. I was speaking to who I was becoming. I visualised a version of me that didn't hesitate. That didn't shrink. That didn't second guess. And I began to act like that version, even if only for a few minutes a day. It was awkward at first. It felt fake, but repetition creates reality. So I kept going. I repeated those forms. I imagined those outcomes. I felt the energy of what I wanted to become. And slowly I began to move different, speaking different, think different, not because the world changed, but because I changed. And the world responded to that. I started to understand that manifestation isn't magic. It's momentum. You build it with every choice you make, with every belief you repeat, with every time you choose faith over fear and action, over doubt. It's not about falcing life. It's about aligning with life. It's about showing up like the person you know you can be and watching how everything begins to meet you there. I wrote my goals down, not just as lists, but as decorations. I didn't say I want. I said, I am, not, I hope, but I claim. And I made it a habit to read those words about every morning before the world had a chance to tell me who to be. I told myself about one shift, that one
