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 →

Adel El Hallak no published score: only 1 usable exchange on raw tape, and a fair score needs 8+ 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.

clear all ✕
1exchanges match
1on raw tape
0redirected or not addressed
Answered raw tape D 5 · C 5 · P 5 · Cm 4 4.85

Q But if you think about the brand names, people say Claude Code, Cowork, um, they don't say a combination or a medley of your favorite models working together, so is that a specific instance with ServiceNow or is that just the way these things are being built?

A Um, well, you're just interfacing with one UI when you're dealing with a cloud code or an open work. You actually don't know the orchestration that's happening behind the scenes, and I'm not going to speculate on, on what they're doing, but I could talk about some of the stuff we're doing between us. Uh, we build, you know, today they were talking about blueprints, right? How to, how to, the blueprint for Agenda KI. One blueprint that we have is, we call IQ, that does deep research, right? And so, Sometimes, you know, it's not when you just need to ask her a quick question. You want to go deep to understand what does it take to resolve this issue? What is the context behind it? What are different data sources I got to look at, synthesize, and understand? Um, that deep research blueprint or, or agent is actually made up of, of no less than seven agents, and bear with me. There's an orchestrator or agent that is kind of like the team leader that's there, right? Um, we've seen some of the best results with using either Opus from Anthropic or GPT for OpenAI for the orchestrator. Next to the orchestrator is also a planner. Um, so this is almost like an assistant that sits next to the team leader whose sole job Is to maintain tasks and to-do lists and to cross those off, right, as those tasks are accomplished. Underneath those layers, you have a whole bunch of sub-research, sub-resea…

AI assessment note: “you're just interfacing with one UI... You actually don't know the orchestration”

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