In this post, Gergely Orosz is the one talking in the Pragmatic Engineer newsletter.
This winter break was an opportunity for devs to step back from day-to-day work and play around with side projects – including using AI agents to juice up those half-baked or incomplete ideas. At least, that’s what I did with a few features I’d meant to build for months, but didn’t get around to during 2025 : related to self-service group subscriptions for larger companies, and my custom-built admin panel for The Pragmatic Engineer.
Unexpectedly, LLMs like Opus 4.5 and GPT 5.2 did amazing jobs on the mid-sized tasks I assigned them : I ended up pushing a few hundred lines of code to production simply by prompting the LLM, reviewing the output, making sure the tests passed, then prompting it a bit more.
To add to the magical feeling, I then managed to build production software on my phone : I set up Claude Code for Web by connecting it to my GitHub, which let me instruct the Claude mobile app to make changes to my code and to add/run tests. Claude duly created PRs that triggered GitHub actions (which ran the tests Claude couldn’t) and I found myself reviewing and merging PRs with new functionality purely from my mobile device while travelling. Admittedly, it was low-risk work and all the business logic was covered by automated tests, but I hadn’t previously felt the thrill of “creating” code and pushing it to prod from my phone.
This experience, also shared by many others, suggests to me that a step change is underway in software engineering tooling. In this article – the first of 2026 for this publication – we explore where we are, and what a monumental change like AI writing the lion’s share of code could mean for us developers.
Today ( 06 January 2026), we cover :
a) Latest models create “a-ha” moments.
It’s not just devs working at AI vendors who noticed much more capable models, but also independent software engineers.
b) Why now ?
Model releases in November and December seem to have been the tipping point : Opus 4.5, GPT-5.2 and Gemini 3.
1. Latest models create “a-ha” moments
Over the past few weeks, some experienced software engineers have shared personal “a-ha” moments about how AI tooling has become good enough to use for generating most of the code they write.
Jaana Dogan, principal engineer at Google, was very impressed by how far Claude Code has come :
“I’m not joking and this isn’t funny. We have been trying to build distributed agent orchestrators at Google since last year. There are various options, not everyone is aligned, etc. I gave Claude Code a description of the problem, it generated what we built last year in an hour.
It’s not perfect and I’m iterating on it, but this is where we are right now. If you are skeptical of coding agents, try it on a domain you are already an expert in. Build something complex from scratch where you can be the judge of the artifacts”.
Thorsten Ball, software engineer at Amp reflected (emphasis mine) :
“For more than 15 years, I thought I loved writing code, loved typing out code by hand, and loved the “cadence of typing”, as Gary Bernhardt once called it ; sitting in front of my editor with my fingers click-clacking on my keyboard.
Now, I’m not so sure.
2025 was the year in which I deeply reconsidered my relationship to programming. In previous years, I had the occasional “should I become a Lisp guy ?”, for sure ; but not the question “do I even like typing out code ?”
What I learned over the course of the year is that typing out code by hand now frustrates me”.
Malte Ubl, CTO at Vercel :
“It’s been a crazy holiday period : I built 2 major open-source projects (one unreleased, and the other a full implementation of a bash environment in TypeScript for use by AI agents).
I started writing a book
I fixed a bunch of other things
It’s a very different world now that we’re in Opus 4.5 world, and these would absolutely not have been possible without it. Opus + Claude Code now behaves like a senior software engineer whom you can just tell what to do, and it’ll do it. Supervision is still needed for difficult tasks, but it is extremely responsive to feedback and then gets it right.
I don’t want to be too dramatic, but y’all have to throw away your priors. The cost of software production is trending towards zero”.
Longtime readers may recall Malte from his reflections on 20 years in software engineering, including 11 at Google.
One could claim that the voices above have an interest in this topic given they work at companies selling AI dev tools. But engineers with no pull towards any vendor also made similar observations :
David Heinemeier Hansson (DHH), creator of Ruby on Rails, described how his stance on AI has flipped due to the improved models :
“You can’t let the slop and cringe deny you the wonder of AI. This is the most exciting thing we’ve made computers do since we connected them to the internet. If you spent 2025 being pessimistic or skeptical about AI, why not start 2026 with optimism and curiosity ?
Just last summer, I spoke with Lex Fridman about not letting AI write any code directly, but it turns out part of this resistance was simply based on the models not being good enough at the time ! I spent more time rewriting what it wrote, than if I’d done it from scratch. That has now flipped.”
Adam Wathan, creator of Tailwind CSS, reflected :
“Any time I have to type precise syntax by hand now [instead of using AI] feels like such a tedious chore. Surprisingly and thankfully, programming is still fun, probably more fun [with LLMs].
My biggest problem now is coming up with enough worthwhile ideas to fully leverage the productivity boost.”
2) Why now ?
Model releases in November and December 2025 seem like the tipping point where AI got really good at generating code :
A) Gemini 3 by Google (17 November 2025) : Google’s best coding model to date (2026)
B) Opus 4.5 by Anthropic (24 November 2025) : the best coding model from the company, which has become the default model for Claude Code
C) GPT-5.2 by OpenAI (11 December 2025) : powering Codex, it’s similarly impressive as Claude Code with Opus
I’ve used both Opus 4.5 and GPT-5.2 and they seem very competent at coding, which isn’t a niche opinion. Here’s Peter Steinberger, a software engineer with ~20 years’ experience and the creator of PSPDFkit, gave his impression of GPT-5.2 :
“The step from GPT 5/5.1 to 5.2 was massive. Now that GPT 5.2 is out, I have far fewer situations where I need [a custom-built CLI agent called ‘oracle’ to get the agent unstuck]. I do use [GPT 5] Pro myself sometimes for research, but the cases where I asked the model to “ask the oracle” went from multiple times per day to a few times per week.
I’m not mad about this ; building ‘oracle’ was super fun and I learned lots about browser automation, Windows, and finally took time to look into skills, having dismissed the idea for quite some time. What it does show is how much better 5.2 got at many real-life coding tasks : it one-shots almost anything I throw at it”.
Simon Willison is an independent software engineering expert in LLMs whom I pay attention to, and he pointed out the same :
“It genuinely feels to me like GPT-5.2 and Opus 4.5 in November represent an inflection point – one of those moments when the models get incrementally better in a way that tips over an invisible capability line. Suddenly, a whole bunch of much harder coding problems open up.
It’s possible Gemini 3 Pro should be included in that group as well, but I’m not seeing quite the same level of astonished buzz from hardened software engineers around that model that I am for the other two”.
The creator of Claude Code, Boris Cherny, responded, sharing that all of his committed contributions last month ( December 2025) were AI-written :
“The last month (December 2025) was my first as an engineer when I didn’t open an IDE at all. Opus 4.5 wrote around 200 PRs, every single line. Software engineering is radically changing, and the hardest part even for early adopters and practitioners like us is to continue to re-adjust our expectations. And this is *still* just the beginning”.
In conclusion, software engineers are more valuable than before. Tech lead traits in more demand, being more “product-minded” to be a baseline at startups, and being a solid software engineer and not just a “coder” will be more sought-after than before. Furthermore, There is Always some uncomfortable outcomes. More code generated will lead to more problems, “coders” who aren’t software engineers could be in less demand, and perhaps a tougher work-life balance for professional software engineers.
Product managers can now generate software easier – needing fewer engineers to realize their goals – but software engineers also need less product management. Both professions are set to overlap with another more than before. AI is a very nice innovation.
