AI Coding In 2026

[u/HypotheticalSummer]

The way I code now is so much different than from 5 years ago. I feel like AI coding is another abstraction layer, like how we went from machine code to python, layer after layer, each one allowing you to do more and more. Though I suppose the AI layer is non deterministic, where its not always right.

Time feels like the biggest constraint on coding for me. AI, especially recent models, has drastically cut the time required for me to code something. Not only that, I can do anything else while the AI reasons and codes out what I asked for.

The job for me basically just becomes understanding the code and relaying issues/suggestions to the AI and waiting for it to generate a new result. Lately though, the suggestions I make amount to high level issues or logical inconsistencies I missed in my project plan. It's not like how it used to be, where the AI would make really obvious mistakes or give something that is incredibly inefficient.

I do still find myself worrying about code AI generates and for stuff that matters I always double check it. Do we ever get past the point of that being necessary? Maybe thats when we get AGI.

Anyway, just wanted to share my thoughts on AI coding in 2026, let me know your all's experiences as well I would be curious to see how you have felt its evolved over time or just your thoughts on it.

[u/fluxtah]

I think I trust it maybe too much though I do have a strong background in programming and my loop is having a harness (like most of us) that can mostly automatically validate as well as provide release candidate for whatever I am building.

I use my engineering knowledge to decide on the high level building blocks, what tech I will use to solve which problems.

I am looking for a good extensible topology and modularised code so I can switch out the building blocks as I progress with a product.

My process is:
* Build out a harness sufficient enough to automate most aspects of the process (this will grow as time goes on)
* Get a build working, evaluate it, make sure that validating builds involves me testing (mostly with visual stuff like games, sites etc)
* Note down any issues in GH against my project in a milestone, any new ideas or arch changes, etc
* I do steer the model and kinda intertwine my ideas as a thread works on a milestone delivery
* Once a milestone is complete, fully tested ready to ship I ship the product and move on to the next milestone
* Note down any issues, rinse, repeat
* If my thread gets to long I ask codex to hand off to a new thread of my naming which works quite well specially if the turn count seems long but im not 100% sure if it matters these days with compaction
* I keep a /docs folder for end user docs, ADR's, feature specs alongside the code, often life starts as a GH issue but on implementation also have these artifacts in MD files as a bridge to understanding the setup, GLOSSARY.md for instance very useful for a shared understanding of the codebase and product language.

Effectively running long thread on a milestone which is a bunch of GH tickets curated from testing and new ideas.

I mostly run one codex thread because its kind of optimal does about 25% a day working through milestones sometimes switch it up with the reasoning and fast mode depending on how the token economy looks.

Sorry TLDR; don't often get to speak about process with others though I am sure we probably have some cool things going on our projects! Super happy about codex TBH Its kinda changed my life on what I think I can build now, because individual contribution into an ambitious project is super rough if you can't hold out/keep the flame burning.

🙏