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In a head-to-head planning test across Fable, GPT-5.5, Opus 4.8, and Kimi 2.7, Fable stood out as far more agentic — it went beyond the prompt to actively research and reverse-engineer an external API rather than just producing a plan, though at a much higher usage/credit cost.

CJ compares planning the same project across four models and finds Fable uniquely proactive, digging in to reverse-engineer an API on its own instead of just returning a plan, at the cost of burning through usage credits much faster. ✦ AI generated

CJ Reynolds · Syntax · 2026-07-06 · original ↗

starts at this moment · 47:27

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did you get a chance to use it?

Fable just went just started researching. It was like okay this is what you want to build but I see you also want to talk to the Amazon API and so it started reverse engineering the Amazon music API and like it was just tool call after tool call. So it definitely is more agentic basically the way that they've trained it is it it will try and try and try more before it's done.

verbatim transcript · starts at 47:27

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47:27like the the one piece of it that made it feel better was it went really deep. So, for the plans that were generated by GPT 5.5, Opus 4.8, and Kimmy 2.7, it basically took the prompt that I wrote, uh, maybe did a few documentation lookups and was like, "Okay, this is the plan that I'm going to present to you." But Fable just went just started researching. It was like okay this is

47:51what you want to build but I see you also want to talk to the Amazon API and so it started reverse engineering the Amazon music API and like it was just tool call after tool call. So it definitely is more agentic basically the way that they've trained it is it it will try and try and try more before it's done and so that's really the only thing that I could see before I

48:10completely ran out of usage credits on on GitHub Copilot. Um, but I will say comparing comparing the four models, that was the main difference. Like it it took the prompt and also rolled with it. Like it basically did things that I had to later prompt the other models for, but it just went ahead and started doing it. >> Um, so I could I could see myself planning with Fable 5 and then maybe

48:31implementing with GPD55 or or Opus 48. Um, but yeah, that was my experience with it. And like I said, I ran completely out of credits. Um, if we're talking about AI usage, I actually found that it's cheaper costwise to pay $100 a month for codeex, which gives you access to GPT 5.5 >> because I' I' I've been running some some Agentic Flows, building out that music app over the weekend, and it

48:57barely touches that that usage for codecs. Whereas I was able to code for like maybe two hours, and then it completely ate through all the usage of my GitHub copilot. Yeah, co-pilot man that usage even without even without uh using Fable is not that much. So that's not that surprising. I I do like I said, yeah, I I agree with you. I think it does a really good job of having a wide

49:23view of projects just like it said it does. Uh in my experience, it's it does way better when you have a big project and you want to plan and make big changes across that project. And I feel like uh when I asked it to do something that was more likely to affect many things other than one localized spot, I found it personally to be much more reliable in the end result. So, uh that

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