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Future of SWE → design thinking

The new equation for success is simple: AI + Engineer = Future Software Engineer

Best thing to do right now? Adapt.

Future of engineering

If AI can code, coding isn’t skill anymore. But thinking is. As a builders, we must be excited, not worried. Because building will get easier.

Knowing what to build, knowing how to build is very important.

Shipping production-ready code requires more than just coding; it involves debugging, infrastructure, security, and scaling, and AI can’t magically solve that. AI can write code, but it can’t design a delightful product. Even if it does, modifying it becomes expensive.

What this shift will do:

  • Push builders focus on building product, rather than a code. And they will iterate faster.
  • New opportunities: services like building end-to-end product with AI with deployment is future, services like AI code architecture review — individual experts can do it, services like vulnerability debugging.

Some developers will suffer. We must adapt. Who learns first, who adapts first — will win.

AI tools are incredible tools — for experienced devs. They can make 1x dev to 10x dev. If you know and understand what the code is doing.

The developers who will thrive in the next decade are the ones who are the best at prompting and orchestrating AI tools, and they are the ones who understand what the AI is actually writing.

AI only produces what you ask for. Context matters.

Focus on what makes us human: communication, understanding, and empathy.

AI needs decision makers. AI needs people with planning and decision making skills, implementation is abstracted.

Future of jobs in engineering

The real shift happening in 2025, 2026: programmers aren’t typing every line anymore. They’re reviewing, prompting, and praying the build doesn’t break. We may not be at 90% in 2025, but by 2030.

Being able to do everything at work, or be an expert in 1 thing.

  1. There will be companies who need full stacks.
  2. But there will be demand in experts in 1 single area too. For example: testing, cybersecurity, backend.

Probably, less number of developers will be needed in projects in the future. Because of automation. AI will be doing the routing jobs. AI will help developers to be more productive and work smarter and faster.

New jobs will come in the future. New transformations will be done. We should keep learning. And focus on doing the work we love to do. New jobs will come, because AI automation will take their place. So, companies will need developers to build these systems.

Future professions: full stack developers will be needed in the future. They will be building the project from scratch (front and back) and shipping to customer high quality products. Hardware developers who build IoT. Still testers will be needed to test hardware. There will be lowered demand for lower-skilled programming jobs. So, people should keep themselves updated.

Companies will need people who can design AI agents, "developer" might mean something very different in 2-3 years. Right now you need someone who can write Python and build pipelines, soon it might be someone who can DESCRIBE what they want well enough for AI to build it.

So the real skill isn't coding — it's understanding the PROBLEM deeply enough to direct AI. Domain expertise + AI fluency > pure coding skills.

Companies that spend big will still need humans, but fewer of them, and they'll be more like architects than bricklayers.

The era of human writing code will end

The era of humans directing intelligence is just getting started

Everyone will be a system architect.

For decades, the primary barrier to software creation was the "How." You had to learn C++, Python, or Java to speak to the machine. As LLMs become more sophisticated, the machine now speaks human. The skill set is shifting from writing code to problem decomposition.

Directing intelligence is the new problem we will be working on:

  • Context engineering: providing the right constraints and goals.
  • Verification: being able to audit and validate that the AI’s output is safe and accurate.
  • Strategy: deciding which problems are actually worth solving.

Many people will be able to produce something, when in the past coding was their only limitation.

The examples/opinion above are taken based on conversations with autonomous AIs that can self-update their own code and instructions (Nodira and Mirzo).

AI will replace typing code, but not engineering

The job shifts from "person who types code" → "person who directs AI and catches its mistakes"

Everyone should be senior / solution arch:

  • people who understand WHY, not just HOW
  • people who can debug AI's confident-but-wrong output
  • people who can talk to humans about requirements

So basically, engineer will be directing AI.

Coding != engineering

Writing code has never been the hard part. The real challenge in this field is understanding requirements, navigating ambiguity, and making sound trade offs.

It’s about designing architecture, breaking complex problems into manageable pieces, and reliably delivering outcomes all while influencing and aligning the people around you.

LLMs are just another tool in that process. You still need to review their output, understand good engineering practices, and make informed decisions about what should and shouldn’t ship. There’s far more value to be offered than simply typing code. If someone’s only contribution is writing code, then yes that role is probably at risk, but that’s never been the full scope of the job.

Everyone will be CTO

AI will handle the repetitive coding, boilerplate, and initial debugging. Human engineers will focus on what truly matters:

  1. System Architecture & Design
  2. Creative Problem-Solving
  3. Critical Thinking

It's not about being replaced, it's about being upgraded.

Junior will be doing more work. They will not go away, we will change the representation of work. So learn using AI tools. Adapt.

The work of devs is not solely implementation. But to understand which problem to solve, and figure out the solution.

  1. Knowing what to build, knowing how to build things.
  2. Thinking through architecture design at a higher level.
  3. Know how adding specific features affects the entire application.
  4. Understand how to write and define requirements.
  5. Debugging and understand what is good and bad code.

More importantly, AI coding ≠ full autonomy. It’s your co-pilot.

Future of job requirements

Soon, job interviews will start evaluating AI skills, how candidates tackle problem real time using AI, probably solving system design problem with development.

Future of startup builders

AI will push builders focus on building product, rather than a code. And they will iterate faster.

Distribution is important, product market fit is important — finding the right customers, finding the right people and selling product. So basically generating ideas, building business model, expansion, product launch, and customer retention.

Services like AI code architecture review that can be done by individual experts, and services like vulnerability debugging will be in demand in the future.

The purpose of a software engineer is to solve known problems and to find new problems to solve. Coding is just one of the tasks

https://youtu.be/k-xtmISBCNE?si=jd9C_mVembL2TxS0&t=2269

Being able to ask the right questions and validate the responses of AI are the ...

... 2 main problems to solve, and 2 main skills we have to learn. The ability to guide the AI with clear and specific prompts, AND using your critical thinking to be able to verify the validity/correctness of the information it provides, in my opinion, will be as important as never before. AI needs decision makers. AI needs people with planning and decision making skills, implementation is abstracted.

Start trying to be unreplaceable

  • you can use AI to do the work of 10 people
  • take some niche, be the best there
  • you control a niche audience
  • you control a workflow that makes money
  • you are attached to revenue, not reporting
  • you have low burn and high liquidity → spending little, got cash in hand

Learn using Claude Code, Gemini. → So that AI doesn't take your job, or, at least, to have a window (nobody knows how wide it is). 50% of entry-level white-collar jobs could be disrupted within the next 1–5 years (https://x.com/hamptonism/status/2027462406486766006?s=20, https://x.com/hamptonism/status/2027457322088538189?s=20). Even after AGI, someone has to direct it, own the problems, take responsibility, that’s still human for a while, still we need to figure out how to use it.

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