Parker retweeted
Feeling vindicated today in my decision to never learn anything about ruby and/or/on rails 😌
Parker retweeted
A Warlock wields power that wasn't earned.
Kaatri's grimoire of spells are a toolbox she can wield across combat and exploration. These are just a taste of the full power she can harness.
Wishlist today: warlock.game/9wr
Prime example of why expertise is needed to guide AI:
Claude suggested that we build a bus to ensure that cache busts work across all backend processes.
I pointed out that it would be simpler to remove our in-memory L1 cache and rely on Redis for all cache items.
Less code.
.@ElevenLabs walked me through deleting my account so I could separate from a shared company account. Now they say the same email can't be reused, so my prod systems are down. Apology issued. Nothing was fixed.
Parker retweeted
After many months of work, I'm thrilled to announce the first draft of the Mistborn screenplay is DONE! Just in time to celebrate the book's original publication, twenty years ago this month. Do please remember that this is just an early step in a very long process, but I'm terribly excited by how it turned out!
Parker retweeted
The problem with this style of programming where you have no idea what's going on and cut corners on all the details is that you cannot have new ideas worth anything at all without a deep understanding of those details. LLMs have been catnip for a certain kind of overconfident "ideas guy" who thinks he can just rattle off "big ideas" and the particulars will take care of themselves. These are the guys who have been putting garbage slop apps non-stop in my face since the advent of LLMs.
Every time in my career I've made a great decision regarding technical direction has been preceded by a fair amount of time understanding the minutiae of how the existing stack worked. Without that deep grasp of the logic of relevant components I haven't had the expertise to know which actions matter and which ones don't.
(As an aside, spending time ensuring you do the right things and don't do the wrong things is a good example of value added that often doesn't show up on bogus productivity measures.)
Truth is hard to accept, but here it is:
- LLMs can output a lot of code quickly if you don't care about quality
- LLMs can marginally speed up the process of writing quality code but you have to be very specific with your prompts and validate every line
- LLMs sometimes could be used to recreate something that was already created, that's basically what they are designed for. It's still hard to find a way to explain an LLM what you are recreating
- LLMs can give you a sizable speedup for outputting boilerplate code. You have to have a lot of tooling and ceremony to validate that this boilerplate is still making sense
A lot of "AI discourse" is basically people overprescribing solutions that work for one category to everyone else. "Oh, just use loops" or "just prompt harder". Or I guess the one that I'm guilty of is: just use a better framework :)
And also unless you are working in an outsource slop factory your job is rarely just one category of this and _your whole job would never be replaced by AI_ (it's kind of like saying an automatic door replaces the whole job of a doorman). No one works at a company that constantly keeps rewriting GCC using the GCC test suite. No one works as a "guy who rewrites software from zig to rust with 90% success rate". Neither does anyone work where their whole job is just to add endpoints to the crud app --- you still need to design it and talk to customers and plan for v2 and so on.
Parker retweeted
📣 The moment is here. 📣
TypeScript 7 is officially released! 7️⃣
devblogs.microsoft.com/types…
Hidden gem game: Tchia
I bought this for my kids, but I got hooked in the first hour. It's like Windwaker + BotW, with some extra magic, all wrapped up in a game appropriate for young kids.
Parker retweeted
More AI-generated code doesn't make your team faster. It might actually slow you down.
Parker retweeted
Today I was part of the 22% reduced by a San Diego startup.
The business is the strongest it’s ever been. So I think it’s important to be direct about what I’m seeing and why.
First, they made this decision and they own it. I was let go because the way to operate at the highest level of productivity is changing, and to win the future, I needed to change with it.
Second, this wasn’t about cutting costs. I was told most savings from this change will flow directly back into the people who stay. Apparently they’ll be introducing million-dollar salary bands. If you create outsized impact using AI, you’ll be paid outside of traditional bands.
Unfortunately, I only had 90x impact.
And in the new world, 90x doesn’t cut it.
THE 100X ORGANIZATION
The primary change is that we’re restructuring around what they call the 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago.
Incremental improvements to my existing workflows weren’t enough. I was still looking at the PRs I merged, instead of having an army of agents reviewing them.
I was still talking to other engineers, instead of my agents talking to their agents.
Sometimes I even deleted code and features, which means my output was technically negative.
The common narrative is that AI makes everyone more productive. It doesn’t. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems.
I was one of those workflows.
THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS
— THE BUILDERS: 90X ENGINEERS
I don’t think most employees have internalized what’s actually happening with AI in engineering.
The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level, that is the farthest thing from reality.
Here’s what we validated recently at this San Diego startup: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers.
They’re not writing code. They’re directing agents that write code.
The skill is judgment.
Unfortunately, I was still occasionally using mine manually.
AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down.
Think about it. The bottlenecks are orchestration and reviewing. Everything else is leapfrogged and no longer needed.
So who do you want orchestrating and reviewing code?
Apparently not me.
The new world is about enabling your 10x engineers to become 100x.
I was only at 90x, which is basically a performance issue now.
The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don’t match the volume of code being generated.
I actually made this worse by sometimes deleting code.
Less code is technically less output.
In hindsight, this was not aligned with the 100x org.
— THE SYSTEM MANAGERS
Ironically, the people who automate their jobs with AI will always have a job.
They become owners of the AI systems. Agent managers.
I, regrettably, was still a person.
I had agents, but not enough agents. My agents had tasks, but not managers. My managers did not have agents. And my agents were not yet talking to other agents’ agents.
The underlying systems in which we operate are absolutely critical to get right. I now understand most companies are delusional to think they can iterate on existing humans and compete in this new world.
You must create enough disruption so old systems are deprecated entirely.
In this case, I was the old system.
— THE FRONT-LINERS
In a world that will become saturated with AI communication, the human touch will matter more than anything to customers.
This is a bottleneck that you shouldn’t replace.
I was not customer-facing, so unfortunately I was replaceable.
REWARDING 100X IMPACT
In a world where companies are able to do so much more with less, where does that excess money go?
In their case, much of the savings in this new operating model will flow directly back to those who enabled it.
Not me, because again, 90x.
We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can’t afford to lose them.
You can, however, afford to lose the 90x people.
Compensation bands of today should be thrown out the door. They’re introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems.
I was apparently ten x short.
THE FUTURE
Nearly every company will make changes like these. The ones that do it proactively will define what comes next.
The future is not fewer people. It’s different work, new roles, and better rewards for those who embrace it.
We’re already seeing entirely new roles emerge, like Agent Managers, that didn’t exist a year ago.
And we’re seeing old roles disappear.
Like “engineer who personally reads his own PRs.”
I’ve never been more certain about where we’re headed.
Parker retweeted
We’re excited to announce that Order of the Sinking Star will be available on @Nintendo #Switch2 later this year! 🎮
Watch our new Overview Trailer where @Jonathan_Blow reveals more details about the characters, worlds, and story! 🎬
Join us > bit.ly/m/SinkingStarGame























