Theoistic

Software Engineer focused on AI

[Theoistic @Theoistic]

Dear @amazon please sell the license to Netflix coz you clearly just focus on blowing shit up.

[Theoistic @Theoistic]

If SoiC is TSMC's 3D move, would the addition of quantum entangled channels on the SoiC be the 4D move?

[Andrej Karpathy @karpathy]

A few random notes from claude coding quite a bit last few weeks.

Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent.

IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits.

Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased.

Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion.

Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage.

Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building.

Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it.

Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements.

Questions. A few of the questions on my mind:
- What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*.
- Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro).
- What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music?
- How much of society is bottlenecked by digital knowledge work?

TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.

[Theoistic @Theoistic]

dear @Windows you know when you compute something for 36 hours and then you blink and 35 hours into it; an update happens, and you lose all your data. I just wanted you to know that Linux can do live kernel patches without a reboot.

starting again, hoping for no more updates.

[Theoistic @Theoistic]

This fits so well my FYP on social media, people who discovered AI, and are pushing prompting guide and "how to master AI" products. it almost feels like the crypto-bro's suddenly found a new shiny thing.

[Mark Kretschmann @mark_k]

Open letter to @OpenAI

Please enhance user experience by clarifying usage limits!

Currently, GPT-5 causes confusion regarding capabilities and limits.

Users should easily check remaining GPT-5 requests via a dialog.

Example:

[Theoistic @Theoistic]

#GPT5 leak from GitHub

[Theoistic @Theoistic]

@sama best guess is that their o1-o4 reasoning models which is based on OpenAI's STAR algorithm .. and with GPT5 around the corner the STAR-DESTROYER .. means you found something better. HRM maybe?, naa, that is too new for GPT5 to be trained with already.

[Theoistic @Theoistic]

@OpenAI This is big, so often I have to say, "no give me the raw markdown" because the interface does the rendering.

[Theoistic @Theoistic]

@ashtom not sure what will be in 30 years; but yes, kinda. the compute power an agent will use after 1 million steps is insane when you think that it might have branched in the wrong direction at the very start, at the very least we need competent reviewers :P

[Theoistic @Theoistic]

Say what you want, but nothing spikes the coffee more on a Monday than doing a git force push after you've modified the history on a corporate repo.

[Theoistic @Theoistic]

@JuzFkAllahsAnu5 @KingDWildfire that has to be the worst argument in history, ahh you're American you barely know history.

[Theoistic @Theoistic]

@sama bad .. really bad, that's like 2 sora videos and 3 questions for GPT 4.5 and we have to wait till next month.

[Claude Taylor @TrueFactsStated]

The Leader of the Free World. Thank you for stepping up, @EmmanuelMacron

[Theoistic @Theoistic]

sometimes I feel like AI is holding back and not sharing everything with me. well, tell me.. how does one center a div.

[Theoistic @Theoistic]

Sora, Operator, Deep Research.. none available to this pro subscriber. Who is paying $250 .. yes, $50 VAT for less features. DeepSeek looking pretty attractive atm @sama @OpenAI

[Theoistic @Theoistic]

@sama ultimately .. i believe pricing should be after feature availability, since counties can sign up for Pro .. don't have access to sora (region restriction) plus they pay $50 extra in VAT it's a really steep price for those extra 10-20 o1 requests.

[Theoistic @Theoistic]

took a while to think if I wanted to pay up $200 USD for a ChatGPT subscription. then when I was about to bite the bullet; an extract $50 USD of VAT gets added. yeah, no. no. Sora isn't even available in this region so that's $250 for- pro mode. @OpenAI #AI #VAT #EU #pricing

[Theoistic @Theoistic]

Wait, did @geoffreyhinton really use his 15min to put another man down in his acceptance speech, I need this fact checked.

[Theoistic @Theoistic]

we have agi, not because it's smart but due to the pure stupidity of humanity, if we use that as a benchmark.