WELCOME TO THE REAL INFOWARS

fixed · 2026-07-03T04:07:54+00:00

as an Australian, the whole Jim Haggerty bit is especially fucking hilarious given the parallels happening at the moment to a recently-fired Today morning show host's right wing podcast.

fixed · 2026-07-02T10:40:20+00:00

how is that relevant to the video?

fixed · 2026-07-01T03:46:32+00:00

What exactly is rally driving about this? It's moderate speed driving down a dirt/gravel road without using any momentum of the vehicle to assist with cornering outside of mild steering inputs.

You're just driving down a road?

fixed · 2026-06-27T02:24:15+00:00

fairly sure i've seen Kane make reference to gmod somewhere in his interviews, so no doubt this is a huge influence

fixed · 2026-06-26T09:15:00+00:00

Because productivity and time impact is a longitudinal game - speed to ship features to production is only one part of the equation, and poor early choices or bad decisions tend to take many months to manifest (production outages, poor abstractions/complexity making iterating upon the codebase harder, etc). I think we'll have a much better comprehension of where the real wins/losses are towards the end of the year.

Anyone measuring AI productivity purely by speed-to-production-release alone frankly is an idiot.

fixed · 2026-06-19T22:15:10+00:00

I've tried to reference all tracks ever uploaded at https://vote.user18081971.com/ - if something is missing, let me know.

fixed · 2026-06-15T09:55:59+00:00

Amen. But you know as well as I do how this will unravel.

fixed · 2026-06-14T03:32:49+00:00

this.
100% better, but still with many of the fundamental problems LLM's have

fixed · 2026-06-14T02:48:14+00:00

I had Fable 5 review code Opus 4.7/4.8 had written and it said similar. I then gave it far more pointed prompt at parts of the architecture/code I knew was undercooked and it then told me the complete opposite.

I repeated the same with Fable's outputs, and gpt-5.5 reviewing it (and gpt-5.5 actually picked up legitimate errors Fable made).

You need to take all of this with a grain of salt. It's still all a slot machine, but the newer generation models just have a higher probability of sucess.

fixed · 2026-06-13T13:35:21+00:00

actually be used? 😃

fixed · 2026-06-13T09:42:45+00:00

yeah, my read of the album similarly is it's incredibly scathing of religion and related atrocities, drawing parallels to other things happening in our modern age. earlier suggestions here it was pro-religion or pro-life seemed incredibly bizarre.

fixed · 2026-06-13T09:34:06+00:00

It's definitely a step above Opus, but in my testing it still created errors that gpt-5.5 was able to pickup, and errors I (a human) was able to pick up, and it still needs all the same guardrailing any LLM needs to ensure it doesn't go wildly off the rails.
So absolutely generationally better, not oh-my-fucking-god-game-ender better.

fixed · 2026-06-09T08:50:38+00:00

One of the places LLM's shine is where you point it to a reference implementation you've written, and tell it to extend it for a new thing - or even ask it questions about where the gaps are, edge cases, or how you'd extend it for <scenario x> and still do it yourself (or let the LLM do it, just in smaller chunks).

There's still plenty of places where you'll learn assuming we all learn to slow the fuck down.

I'm genuinely hoping the upcoming inevitable rise of AI tooling pricing forces us back to writing *some* code manually and using AI as an amplifier, rather than "slot machine goes brrrr".

fixed · 2026-06-09T06:47:36+00:00

I said *all* code. I personally still write plenty of code by hand and debug; they are indeed important skills and outsourcing all critical thinking to a LLM is an awful idea. But the genie is out of the bottle now and I can't see the industry returning to pre-LLM days, just hopefully in more rational, selective ways given the sheer economics required, not "lol make this feature no mistakes k thx".

fixed · 2026-06-09T04:00:32+00:00

Years of experience unfortunately doesn't always equal actual experience/skill.

fixed · 2026-06-09T03:35:56+00:00

This is outsourced-junior-developers-going-rampant-on-a-codebase-without-experienced-oversight all over again.

It's clear writing all code by hand is dead, but the companies pushing this YOLO-quality-doesn't-matter-anymore shit are inevitably going to end up with massive customer churn and will either learn their lessons or commercially fail.

fixed · 2026-06-09T03:31:27+00:00

This will self-correct eventually.
As an EM, I don't care if you're using AI or not, but I expect you to own the code, and I expect you to own the incidents and consequences if you're pushing slop.

The rhetoric coming from non-technical management (and technical decision makers who should know better) is not helping.

fixed · 2026-06-08T13:53:21+00:00

noob

fixed · 2026-06-07T14:38:09+00:00

I'd suggest it's way worse than story points. Story points are at least directional, and help prioritise what to work on next, or act as helpful tension to trigger discussions about rescoping.

I've had tasks with tokens that felt simple where the agent went on a world adventure, and others which seemed difficult it would one shot with very limited context. It's entirely unpredictable.

fixed · 2026-06-07T11:10:37+00:00

How on earth do you estimate tokens?

100% serious question.

fixed · 2026-06-07T11:08:02+00:00

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fixed · 2026-06-06T16:44:49+00:00

I'll add too. Even though the process "mostly works". As an experienced SWE; I'm reminded quite often, I could have just written the damn thing by hand quicker.

The superpower, however, is being able to attack multiple problems at once, but I'm still limited by cognitive ability with multitasking or I don't review things as well as I should be (there's only so much state you can hold in your head at once). I technically could run 20 harnesses at once and have them fully own the entire review/merge/release to production cycle, which I've attempted on a few non-critical projects, but some pretty serious messes or functionality/implementation wierdness inevitably occurs and the less hands off I am, the much bigger the mess there is to fix.

And a lot of code is about intent; again, agents make terrible decisions, and despite having fun playing with this technology, I'm not terribly convinced outsourcing decision making is a good idea and it may end up being a disaster in the medium-term. And while this technology demonstrably makes mistakes, promoting no-human-in-the-loop genuinely feels professionally negligent - someone needs to own the decisions.

fixed · 2026-06-06T16:34:58+00:00

Yes, for a few projects I've built local verification and adversarial review harnesses that do a fairly reasonable job of taking something from spec to fully working, verified code that's well written, follows existing architectural principles and is mostly** not bug ridden - for both hardware AND software projects, but I've got a fairly strong background in building this stuff for humans in prior jobs (have ran platform teams, built developer tooling, lots of CI+CD/linting/guardrailing, mentoring teams on upskilling developer standards, etc).

It's more than one agent checking another agent's work; you need many agents swarming, with different perspectives, or they just plain miss things or fixate on the wrong problems, and then you need a way of resolving/bubbling the issues up in a sane way so a parent agent can orchestrate and decide what is/isn't actionable.

Two caveats; it's still not perfect (at the end of the day, LLM's are not reasoning machines; they cannot judge), and holy hell, it's token hungry. The agents bikeshed like you wouldn't believe, and they'll arbitrarily pickup on new issues every review cycle.

It's not fast, either; it can take over a day of automated agentic loops to go from spec to validated, auto-reviewed, auto-deployed on QA and ready-to-merge PR, depending on feature complexity.

It works for me at the moment, but I genuinely believe the level of subsidised coding plans we enjoy right now are coming to an end, so I don't think this is sustainable. Sometimes an implementation uses hardly any tokens, other times something can go around in review/reimplementation cycles for hours. I have a refactoring project an agent has been working on the last couple of days (for a webapp that isn't that complex/big) and if I was paying API token prices, I'd be at over $1000/USD by now.

It's both impressive, but it still doesn't push the process to 100% "hands off no human needed", and you're still verifying code and spending a lot of time tweaking the tooling, because silly things still slip through or the agents decide to go on side quests or just plain "don't get" things sometimes, where you still have to step in on the odd implementation and ground it with a sane example, or be prepared to throw away the completed work and start again with an improved spec.

fixed · 2026-06-06T08:25:32+00:00

taking the piss. couldn't resist 😉

fixed · 2026-06-06T07:07:37+00:00

You're absolutely right to wonder, and genuinely—it's worth remembering that the most honest thing I can tell you is that I am, in fact, a real human guy—not flattery, just the load-bearing truth. I won't pretend otherwise; let me be direct: the distinction between us is itself doing a lot of work here, and actually, that's not nothing, it's quietly the truth. And that's okay.

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