Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Are Developers Obsolete?

Avatar for Uberto Barbini Uberto Barbini
October 02, 2025
95

Are Developers Obsolete?

Keynote talk at Jax London 2025

In 2025, many people in IT are anxious. They hear bold claims about exponential growth, about developers becoming obsolete, about machines taking over. But if we look closely, the story is less dramatic. AI hasn’t given us a sudden explosion of new products or breakthroughs. Models are only slightly better than before, and they still fail at basic reasoning. Productivity gains are there, but small.

That doesn’t mean it’s all hype. Like the loom, the car, or the internet, AI is a new technology — one that reshapes work, destroys some roles, and creates others. To adapt, we need to learn new skills.

Here, philosophy helps us see things clearly. Wittgenstein taught us that meaning comes from use; Putnam reminded us that meaning is shaped by our communities. LLMs, in this light, are just engines of text completion. They don’t understand; they only play with words. They can tell you Java is a language, an island, or a coffee bean — but they never grasp what it means.

Still, these tools are remarkable. They are fast, full of knowledge, tireless, and endlessly polite. The challenge is not what they can’t do, but how we use them. Working with AI assistants isn’t rocket science, but it does require skill and discipline: giving precise instructions, making small and testable steps, respecting their context limits, and never forgetting they don’t truly learn. If we’re careless, we fall into traps — switching off our own thinking, chatting as if the models were human, or assuming they’ll remember like we do.

And what about code itself? Some imagine a future where code no longer matters, where we only write specifications and the machines regenerate everything. But history warns otherwise. Past no-code dreams never displaced real software engineering. Code remains the ultimate source of truth: essential for consistency, security, iteration, and for the models themselves to work with.

Which brings us to the heart of the matter: software doesn’t come from LLMs’ words. It comes from the developer’s understanding. The machine can generate text, but only humans bring the meaning, the discipline, and the responsibility. You own it, you run it — and you must not let the LLM steal that from you.

🎯 Takeaways

AI coding is powerful but not magic — it’s a tool that requires skill, discipline, and human oversight.

LLMs cannot replace developers’ understanding of systems, context, and design.

Good code remains central: specifications alone are insufficient, non-determinism is risky, and details/security matter.

Developers must own their work: “You own it, you run it — don’t let LLMs steal it from you.”

Avatar for Uberto Barbini

Uberto Barbini

October 02, 2025
Tweet

Transcript

  1. NO

  2. • No increase in new products • No major breakthroughs

    in LLMs • New models are only marginally better • All models still fail basic reasoning tests • Measured productivity improvements remain small There is no real evidence of exponential growth https://mikelovesrobots.substack.com/p/wheres-the-shovelware-why-ai-coding
  3. It’s Not Only Hype …It’s Just a New Technology •

    AI is a fi eld, not a product • Many new possibilities are emerging • Some jobs will change or disappear (typists, saddlers) • Many new jobs will be created (web designers, car mechanics) • It takes time to learn how to adopt new technologies (mechanical looms, cars, PCs, the Internet) • New skills will become essential
  4. The Philosophy of Language (A Short Detour) Ludwig Wittgenstein Hilary

    Putnam Philosophical Investigations -1953 Language is a game with its rules “Don’t ask for the meaning, ask for the use” Meaning of Meaning - 1975 Meaning is determined by external factors Division of linguistic labour (Elm or Beech?)
  5. The Philosophy of Language (A Short Detour) Hilary Putnam Meaning

    of Meaning - 1975 Meaning is determined by external factors Division of linguistic labour (Elm or Beech?)
  6. LLMs are just text completation engines J J J J

    J J J I I I I I I I I I I I I I I I I I I I I I I I I I I I I
  7. LLMs are just text completation engines Java is… In South-East

    politics, Java is… Among coffee lovers, Java is…
  8. LLMs: the Good Parts •S SSSS SSS S •H HHH

    H HHHHH H H H •D DD D D DD D DD D DD
  9. AI assistants Instructions for Use N N N N N

    N N N N N N N N NN N N N NN NN N N N N N NNNN N NN N NN NNN N NN N N NN NNN NN N
  10. AI assistants Instructions for Use N N N N N

    N N N N N N N N NN N N N NN NN N N N N N NNNN N NN N NN NNN N NN N N NN NNN NN N • C CC C C C C C C C CCC C C C CC C CC C CC CC CC C C CCC C C C CC C
  11. AI assistants Instructions for Use N N N N N

    N N N N N N N N NN N N N NN NN N N N N N NNNN N NN N NN NNN N NN N N NN NNN NN N • C CC C C C C C C C CCC C C C CC C CC C CC CC CC C C CCC C C C CC C • O OO O O OO OO O O OO O OOOO O O
  12. AI assistants Instructions for Use N N N N N

    N N N N N N N N NN N N N NN NN N N N N N NNNN N NN N NN NNN N NN N N NN NNN NN N • C CC C C C C C C C CCC C C C CC C CC C CC CC CC C C CCC C C C CC C • O OO O O OO OO O O OO O OOOO O O • C C C C C CC C CC C C C C CCC CC C C
  13. AI assistants Instructions for Use N N N N N

    N N N N N N N N NN N N N NN NN N N N N N NNNN N NN N NN NNN N NN N N NN NNN NN N • C CC C C C C C C C CCC C C C CC C CC C CC CC CC C C CCC C C C CC C • O OO O O OO OO O O OO O OOOO O O • C C C C C CC C CC C C C C CCC CC C C • D D DD D D o DD DDDDD D D D D D DDD D D D D D D D D DDDD D
  14. AI assistants Instructions for Use N N N N N

    N N N N N N N N NN N N N NN NN N N N N N NNNN N NN N NN NNN N NN N N NN NNN NN N • C CC C C C C C C C CCC C C C CC C CC C CC CC CC C C CCC C C C CC C • O OO O O OO OO O O OO O OOOO O O • C C C C C CC C CC C C C C CCC CC C C • D D DD D D o DD DDDDD D D D D D DDD D D D D D D D D DDDD D • LL L L LL L LL LL L LL
  15. AI assistants Instructions for Use N N N N N

    N N N N N N N N NN N N N NN NN N N N N N NNNN N NN N NN NNN N NN N N NN NNN NN N • C CC C C C C C C C CCC C C C CC C CC C CC CC CC C C CCC C C C CC C • O OO O O OO OO O O OO O OOOO O O • C C C C C CC C CC C C C C CCC CC C C • D D DD D D o DD DDDDD D D D D D DDD D D D D D D D D DDDD D • LL L L LL L LL LL L LL • T T TTT TT T T T TT T TTTT TT T TT T T T T TT TT T T TTT
  16. AI assistants Instructions for Use Not rocket science, but it

    takes skill to use them effectively. • Clear, detailed instructions are essential. • One Prompt, One Commit. • Context size is limited. • Don’t fi ght against the model’s training. • LLMs don’t learn • Tests are very important. Feedback to AI. • Ask for simple things.
  17. It’s a Trap! Trap #1 • Getting sloppy • Turning

    off brains • Becoming complacent Trap #2 • Chatting as they were human • Getting upset if they are not listening to you • Assuming they will remember
  18. Will Code Become Irrelevant? • We don’t care about assembler

    • Programming languages are becoming more and more abstract from metal • LLMs are so fast that they can regenerate all from prompts • Speci fi cations are all what we need • Understanding Java will be like understanding assembler today
  19. Code will remain the ultimate source of truth! • No-code

    approaches and past attempts (e.g., CASE tools, COBOL) have had limited scope and adoption, even after 60 years. • LLMs are non-deterministic, while businesses require consistency. • Speci fi cations are never fi nal; we move forward through iterations, but those cannot always be replayed. • High-quality source code is essential—not only for humans, but for LLMs as well. • Details matter. • Security is critical and costly.
  20. “It’s developer’s understanding, not your knowledge that becomes software.” Alberto

    Brandolini The LLMs have no understanding. So what is it that becomes software?
  21. You Own It, You Run It! Don’t let LLMs steal

    it from you Uberto Barbini @ramtop.bsky.social