Jaron Collis

Co-founder @PluralAI.
Think deeply. Invent ingeniously. Tweet sparingly.

[Jaron Collis @jaroncollis]

Every year since the Big Bang of ChatGPT, I've written a longform post to capture my thoughts on the current big themes in AI. So I can look back one day and see how I saw things at the time.
This essay is about unmetered AI and sovereign intelligence...
https://t.co/rH9w7FqNa9

[Jaron Collis @jaroncollis]

The first mainstream movie to mention neural nets was Terminator 2 in 1991. Prior to that, the technology behind omniscient computers and robots was never described.

[Jaron Collis @jaroncollis]

Slot wanted to nullify risk, the philosophy of Klopp (and Iraola) is to embrace it. There's nothing safe about passivity. Not taking risks is the greatest danger of them all.

[Jaron Collis @jaroncollis]

"Running isn't the most important thing, but the enthusiastic one runs. And when he runs, his virtues come alive." -- Marcelo Bielsa

Over-coached "to control" games #lfc have lost their fire. If Andoni Iraola can rekindle it, the Kop will adore him.
Run because you want to.

[Jaron Collis @jaroncollis]

The guiding light of a startup in the AI age is to authentically care about the fate of your users. AI models care about answers and the intrinsic rewards reinforcement learning has baked into them. Only founders emotively care about their users' joy and success. That's the moat.

[Jaron Collis @jaroncollis]

These are my words, and if you know me, you’ll recognise my voice.

It's easier than ever to generate content, yet harder than ever to be heard as a human being. So I built something.

[Jaron Collis @jaroncollis]

Having AI omniscience at my fingertips makes me far less self-conscious about not knowing everything.

[Jaron Collis @jaroncollis]

I miss the days of enthusiastically casting votes for big ideas. I suspect that's because the bold technocrats are too busy building the future themselves to bother waiting to be elected to it.

[Jaron Collis @jaroncollis]

Great keynote. Genuinely inspiring.

[Pat Grady @gradypb]

Long horizon agents are functionally AGI... and there's $10 Trillion up for grabs

[Jaron Collis @jaroncollis]

"Equipped with his five senses, man explores the universe around him and calls the adventure Science." 
-- Edwin Hubble, The Exploration of Space

[Jaron Collis @jaroncollis]

"The moon is just hanging in front of us, this black orb." -- Victor Glover, Artemis 2

We could have sent robots to the moon, but only human eyes go in search of beauty. A lunar eclipse from space, with Saturn, Mars, and Mercury. What a photograph.
https://t.co/6kXTD52o6v

[Naval @naval]

Vibe coding is more addictive than any video game ever made (if you know what you want to build).

[Jaron Collis @jaroncollis]

Say the things an LLM never will.

[Ethan Mollick @emollick]

NotebookLM: Do a deep research report and make a video telling me exactly how to take over Rome if I time travelled to 66 BC with a single backpack.

Actually pretty fun to watch and gets a lot of historical details in as well.

[Michael Tanguma @MTanguma]

7/ "No entrepreneur is worried about AI taking their job."

This one is deceptively deep.

Entrepreneurs don't have jobs. They have impossible problems. Any AI that shows up is an ally, not a threat.

The thing AI is fundamentally missing is agency. It doesn't want anything. It has no survival instinct. It can't set its own direction.

Naval said the key thing that separates entrepreneurs from everyone else in the economy is extreme agency. Operating in the unknown. Making decisions nobody else will make.

That is the moat. Not skill. Not knowledge. Agency.

[Jaron Collis @jaroncollis]

"Anthropic’s culture is described by employees as 'Yes, and…' style improv. Every idea is welcomed, examined, savored, and judged by the Hive Mind. Based on vibes. No central decision-making authority. They’re finding their way like a floodfill search."
https://t.co/Cw51zSCNxq

[Jaron Collis @jaroncollis]

This is a good way to think of AGI, as a threshold that will be passed quietly, when the gap between organic and artificial minds can no longer be easily measured. Just as the Turning Test was.

[François Chollet @fchollet]

Reaching AGI won't be beating a benchmark. It will be the end of the human-AI gap. Benchmarks are simply a way to estimate the current gap, which is why we need to continually release new benchmarks (focused on the remaining gap). Benchmarking is a process, not a fixed point.

We can say we have AGI when it's no longer possible to come up with a test that evidences the gap. When it's no longer possible to point to something that regular humans can do and AI can't.

Today, it's still easy. I expect it will become nearly impossible by 2030.

[Jaron Collis @jaroncollis]

"With agents programming feels *more* fun. LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building."

Absolutely. I never enjoyed coding, but I love building. LLM coding is like being liberated from writing machine code.

[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.

[Jaron Collis @jaroncollis]

Whoever owns and controls the means of production captures the gains. Open models are shrinking rapidly, and what you can run locally may already be good enough. The M4 Mac Mini is an extraordinary means of production.

[Jaron Collis @jaroncollis]

Innovation is finding authentic value in a preposterously enormous search space. Reasoning models can explore it and produce hypotheses, but not validate them. Distinguishing almost right from actually right is the moral of The Library of Babel. Truth was always the bottleneck.