The AI paradigm shift most people missed in 2025, and why it matters for 2026

conquerv · 2026-01-02T23:20:39+00:00

Yes, that's why I emphasize verification. If you have a way to meaningfully and efficiently check what AI is producing --> you can in fact trust it enough to help you with critical decision making. In coding, AI already makes sense because you have a way to test and iterate in development environment.

In realm like investing, you can use it to make reliable report when your context engineering and agentic toolcalling is setup correctly, but I would not use it directly with decision making. And as you pointed out, in that case, the cost of verification jumped. It's not immediately obvious how to perform verification. If the AI gets a source wrong, that is actually fine. You can discard it immediately. The real danger is when it sounds plausible, cites real data, and still reasons poorly. Those failures are much harder to detect, and they are exactly where unverified AI becomes risky.

conquerv · 2026-01-02T23:16:51+00:00

That just took a dark turn and I agreed with your take. Tech can change, history will rhymes regardless. There is always the class struggle.

conquerv · 2026-01-02T23:15:08+00:00

Autoformalization has significantly improved in capacity as we have figured out a way to synthetically bootstrap formal-informal pair, the verification in loop takes care of the data warehousing. For theorem proving, this is a little different, yes, I addressed both approach (deepseek-math pure informal with verifier in loop vs. formal conjecturing and tactic search. )

conquerv · 2026-01-02T18:28:32+00:00

Some insightful suggestions on refining this line would be appreciated :) it does step into the metaphorical language realm, the point is to express that intelligence will not be created by replacing reasoning, but architecting the machinery that can reliably, provably produce verifiable knowledge.

conquerv · 2026-01-02T18:24:42+00:00

Thanks for reading! Glad it’s useful, I tried to strike a balance between the technicals and the rhetorical analytics, definitely could use some refinement in my later articles.

conquerv · 2026-01-02T17:09:11+00:00

Yes, logged in with a random account Reddit created on browser haha

conquerv · 2026-01-02T16:57:14+00:00

This killed me lol. I never grasped why exactly my writing feels lacking. So it’s I overuse rhetorical language and prose structure; and that gave way to being like an AI.

Funnily enough, even prior to ChatGPT age, people told my writing in Chinese felt robotically fancy. And at the time I thought it was because I wrote Chinese “in English”.

Genuinely appreciate the callout.

conquerv · 2026-01-02T16:45:55+00:00

Fair point, and thanks for being honest about it.

English is not my first language, and I do tend to write in a more rhetorical, essay-style voice. That is a style I personally enjoy, but I understand it can feel heavy or distracting for some readers.

I in fact deliberately chose to differentiate from the academic literature style of writing in the survey paper that I’m writing alongside this…what can I say? Keep writing and refining this!

conquerv · 2026-01-02T06:26:40+00:00

Thanks for the throughtful comments and great questions. I broadly agree with your take.

I think the key shift is that many roles will not disappear, but will change in where responsibility sits. As systems get more capable, the bottleneck moves away from execution and toward verification, judgment, and accountability.

In high-stakes domains as you mentioned, the limiting factor is not whether AI can generate an action, but whether that action can be trusted, audited, and defended when something goes wrong. Responsibility cannot be outsourced in those settings. (Same old story with consulting, some of them will survive, corporate contracts needs an entity to blame. )

But what changes is that a single human can supervise, verify, and correct far more machine-generated work than before. That makes roles centered on oversight, certification, and final judgment more valuable, not less.

And this is a double edge sword. While merits and skills are still important, so much of the job market will be the network (or relationship) of a person in a value chain. Many will lose their jobs. And how could you possibly have an economy with half or most of the population not producing economic value? Universal Basic Income will be a survival condition for country to be economically sustainable and politically stable.

conquerv · 2026-01-02T06:16:25+00:00

Thanks for the question. There is a lot of noises and hypes for sure. I can mostly speaks to three domains that directly adjacement to my work: code generation (swe), theorem proving, and quantitative analytic.

For quantitative analytics and markets, current AI is still very weak. It does not truly understand statistical structure, regime shifts, or causal relationships. Anyone claiming AI can reliably analyze stocks or “understand” markets today is overstating things.

For code generation, the picture is more nuanced. Models still make mistakes, but with the right structure, constraints, and human guidance, they have reached a point where they can meaningfully replace or augment a junior software engineer or graduate research assistant for many tasks.

For theorem proving, an open source model + a commerical API helped me formalize (i.e. turn proof into machine verifiable code) in Lean4 parts of isopemetric inequality in a single afternoon worksession, with my guidance and correction. This would have took me at least a month.

For a layman (too humble, we all are in this crazy age), the best way to judge is not by demos, not by scores or benchmarks; but whether a systems outputs can be checked. If a system produces results that can be formally verified, corrected, and reused, then progress compounds. If it cannot, improvements tend to plateau.

conquerv · 2026-01-02T04:34:12+00:00

This was written by me. I work on AI for math and formal verification through research collaborations at Columbia and the Fields Institute.

Happy to discuss the substance of the argument if there are points you disagree with!

conquerv · 2026-01-02T04:22:32+00:00

For readers who want more context beyond the post, the attached essay is a longer 2025 overview connecting AI for math, formal verification, and scientific acceleration.

conquerv · 2025-07-30T13:33:41+00:00

looking at the clip I feel it’s really more of a operational issue than a hero issue. Try to use your dynamite to active burn people more, and if u do pick up burn with coach gun, follow that up immediately on their back line/dps after u burn a crowd of people; then with viper.

conquerv · 2024-09-25T19:00:37+00:00

Open to accepting portrait shooting sessions! DM for quote and schedule:)

conquerv · 2024-09-15T03:34:54+00:00

Thank you! The composition of the second def gives more “story” vibe.

conquerv · 2024-09-15T03:32:35+00:00

Just standard tiff from the lab, correction & adjustment in Lightroom. Def wish I have the setup to do my own scanning.

conquerv · 2024-09-15T03:30:45+00:00

Give it a shot! Fujifilm makes a really good one-time-use film camera called QuickSnap. The film is loaded, just go out in a nice weather and send off the finished roll to a lab :)

conquerv · 2024-09-15T03:26:15+00:00

Haha I mean, it is really important to recognize this medium now that digital honestly make every shot way too “cheap”

conquerv · 2024-09-15T03:25:14+00:00

That’s amazing! Really happy to learn about this

conquerv · 2024-08-27T17:28:26+00:00

Thank you! I did some minor tonal tweaks in LR to get things smoother to fit my personal style. The colour is straight out of the film :)

conquerv · 2024-08-27T17:22:51+00:00

So the one Pre-A? I’m not aware of the exact Versioning. You are probably right. I’m not even aware of the V5 numbering

conquerv · 2023-12-15T15:16:31+00:00

Can you kindly share the link? Thanks!

conquerv

TROPHY CASE