The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Remy Gaskill no published score: only 6 usable exchanges on raw tape, and a fair score needs 8+ · coarse estimate ≈4.5/5 from 6 raw tape exchanges record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

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Answered raw tape D 5 · C 5 · P 5 · Cm 4 4.85

Q That this is really like a new way of working, right?

A Yeah, it is. It is. It's so new, and I, and I, even this task, it's really simple, right? Just sending an email based on a call with a proposal link and stuff, but like, even if you can just do something like seven times faster without having to go into all these tools, copy the meeting notes into the page to give it context on your meeting, it really starts to compound. Then you start to fit like a week in a day, and then seven weeks, In a week. Um, and stack that up over a year, and you're gonna be miles ahead of everyone else. Uh, and when we get into skills, you're gonna see how this continues to get even better. But, um, you can see here, it's drafted the email, it's pulled in all these insights from our call in Granola, which is like where I do my meeting notes, and then it's created the Stripe payment link. Here, ready to go. That's cool. And then now I can just go, um, send this email. And it will use my Gmail integration to, to go and send it. Uh, and then.

AI assessment note: “Yeah, it is. It is. It's so new, and I, and I, even this task”

Answered raw tape D 5 · C 5 · P 5 · Cm 4 4.85

Q Ok, so wait, so, how did you create that skill?

A Ok, so, there's two ways that I find useful to create skills, is one, you can have an idea of a skill you want to create off the bat. So, like Viral Hooks for example, I had this course on Viral Hooks, which I transcribed, put it into Claude, and Claude has this by default, it has a skill creator skill added into it. Same with all of these major agent harnesses, they'll have a skill creator skill. So it's kind of like skill-ception. You use the skill creator skill, and you say, hey, take this course on viral hooks and create a viral hook skill, and it can create it like that. That's one way. Uh, and then it will package it up nicely with that skill.md. It'll do the whole thing for you.

AI assessment note: “I had this course on Viral Hooks, which I transcribed, put it into Claude”

Answered raw tape D 5 · C 5 · P 5 · Cm 4 4.85

Q I love it. And for the beginner, are you, like, did you recommend people, you know, use OpenClaw or should they be using Cowork or Manus and some of the ones you showed?

A So, great question. Uh, I would say that OpenClaw is probably, like, one of the hardest to learn and set up of these harnesses. I would say Cowork is probably the easiest. I think Perplexity Computer, you did a video on it. Um, it's pretty simple too. Same with Manus. Um, but I would definitely learn, um, and get comfortable using, like, Claude Code or, um, one of these other ones before I started to play around with OpenClaw. And I would also, uh, have all the processes built out in Claude Code first. So, for example, that executive assistant, over the next, ah, two weeks, I might build out a bunch of skills, like the Sebastian Refer skill, um, like a daily brief, meeting prep, Et cetera, et cetera. And then once I'm happy with how it's all functioning in Claw code, then I could look to migrate that into OpenClaw where it has that more autonomous nature to it. So that's kind of how I think about using OpenClaw and those other harnesses.

AI assessment note: “I would say Cowork is probably the easiest. I think Perplexity Computer... pretty simple”

Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q How should people think about security and these different products?

A I like to think of security as in just, like, scoping what they have access to. So, by default, Antigravity, Cloud Code, and Codex, they're very, very secure because they're built by these massive companies that have a lot on the line, um, to protect. And I just, you know, if you, if you're building out these agents to manage different elements of your business, like the other week I built one, um, that does, manages meta ads. And obviously that's quite a risky thing to give an agent control over managing ad budgets. So it just comes down to like what you feel comfortable giving the agent. And also you can control what privileges or you control what, um, tool permissions has access to. So that if it was compromised, for whatever reason, the worst case, like, isn't that bad. And that means, you know, just giving it, like, read-only access to certain important platforms and stuff like that. Does that make sense?

AI assessment note: “I like to think of security as in just, like, scoping what they have access to.”

Answered raw tape D 5 · C 4 · P 4 · Cm 3 4.15

Q So, so this is, this is, um, Claude Code?

A Yes. Yeah, right now we're in Claude Code, and this is just accessing it through the desktop app for Claude. Um, so I'm just gonna run that. And then I'm also going to give the same prompt to Codex here. So this is the Codex app. And you can see same concept. It says let's build. We can choose a folder on our computer to work in, like demo two. And then we're going to give that a prompt as well. And we're going to tell it to host it on a different one. And then also in anti-gravity. So you can see same concepts. We're going in, selecting a folder, and then we will Give it the prompt as well.

AI assessment note: “Yes. Yeah, right now we're in Claude Code”

Answered raw tape D 5 · C 4 · P 4 · Cm 3 4.15

Q Yeah, that makes sense, right? Because it's, and it's, it's adding, where, where's that adding it?

A Well, it's not adding it, that's the thing. So we can tell it, my favorite color is lavender, and it's gone, the user's just shared, that's that thinking step, it's like the user's just shared this, like, no, nothing needed. Good to know, I'll keep that in mind. But then if we go into a new session, same folder, and we go, what is my, Fave color. Mind my spelling. It's going to say, I have no idea what your favorite color is, even though we just told it. And that, um, is an issue, you know, because if you're working, you know, you've got like a head of sales or something, and it keeps, it signs off your emails wrong, and you tell it, you correct it, and you say, never sign off emails with cheers, say warm regards. And it will go, okay, got it. Noted. But then the next day you start working and it does the same thing again. It's like, well, like my agent's broken, but really it's not, it's running off those context files in the back. And unless you are manually updating it, it won't know to save that preference. So what I like to do is I like to add in something like this to my agents.md file. So this is just a little simple thing. You can pause the video and copy it. But I like to, I'm just going to remove that context file for now. That was just to illustrate that example of adding more, but we're just working with this one file for now. So I'm just going to open this up so I …

AI assessment note: “Well, it's not adding it, that's the thing.”

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