Claude vs. ChatGPT for consulting work: why we default to Claude

Revised October 10, 2026. An earlier version of this article was written as a first-person account of running both tools side by side. We've rewritten it as what it should have been: our reasons for defaulting to Claude, and a way to test the choice on your own work.

There are plenty of articles comparing Claude and ChatGPT, and most of them end in the same place: both are good, each has strengths, it depends on your use case. That's true and not very useful.

So here's a clear recommendation and the reasoning behind it. For the work this catalog is built around (proposals, deliverables, meeting debriefs, case studies, retrospectives), we default to Claude, and every product here is written for it first. The prompt-based products also work in ChatGPT, and each carries a note on any adjustment.

A recommendation only goes so far, though. Both tools ship new versions every few months, and the right answer for your practice depends on how each one handles your material. The useful part of this article is the test at the end.

If you're earlier in the AI-for-consulting journey, start with the three categories of consulting work. The choice of tool only matters once you've decided a task should go to AI at all.

Why we default to Claude

It commits when asked. Much consulting work ends in a verdict: propose or don't, GREEN or RED, option A or B. Our prompts ask for one explicitly, and Claude follows that instruction well. A model that hedges by default costs you a follow-up message on every run, and over a year that adds up.

It flags what it can't support. Our prompts tell the model to mark gaps with a placeholder such as [TK note] rather than invent a plausible fact. For consulting work, where the line between "in the data" and "plausible-sounding" can matter legally, that instruction is the most important one in the prompt, and Claude handles it well.

It handles long inputs. Current Claude models work with very large context windows on paid plans, so an hour-long transcript or a forty-page RFP fits comfortably in one conversation. That matters for the meeting debrief, where the middle of the transcript is often where the decisions were made.

It matches a voice from a sample. Both tools can imitate a writing sample you paste in. The section-expander workflow depends on that, and it's one of the things worth testing directly, below.

Skills. Claude lets you package a reusable set of instructions as a skill: a folder with a Markdown file that you upload in the Claude app (under Customize → Skills) or drop into ~/.claude/skills/ for Claude Code. Claude uses the right skill when your request matches its description. ChatGPT's nearest equivalent, the Custom GPT, lives inside ChatGPT, while a skill is a plain folder of files you keep. The Proposal-Closer Prompt Pack ships a skill for that reason (installing one is covered here).

The task to test before deciding: live research

If one workflow could go either way, it's live web research: the pre-call dossier, where the model has to find a prospect's recent funding, hires and announcements and cite where it found them.

Both tools now search the web, and Claude also has a Research mode for longer investigations. How well each one finds recent, specific facts about the companies you actually pitch is something only a test on your own prospects will tell you. Judge three things: how many of the facts you can verify from the cited sources, how recent the newest one is, and how easy the citations are to check.

How to test it on your own work

Pick three tasks from a normal week and run each in both tools with identical inputs:

1. A discovery dossier on your next prospect. Check every number against its source.
2. A meeting debrief from a long transcript. Check whether the decisions in the middle of the call made it into the summary.
3. A section expansion from your own bullets and a two-paragraph sample of your writing. Read both drafts cold and ask which needs less editing to sound like you.

Score each run by the time it takes you to get to something you'd send. That's the only comparison that matters for your practice, and it takes under an hour.

What this means for your subscription

If you only want one subscription, we'd pick Claude Pro ($20 a month, billed monthly). It has web search built in, and the drafting workflows, which you'll run far more often than research, are where the choice matters most.

If you can afford both, run the test above before keeping both. If one tool clearly wins on your research, use it for that and the other for everything else. At consulting rates, a second subscription pays for itself quickly if it does a job better. The workflows themselves are in The Solo Consultant's AI Playbook.

If you already have ChatGPT and don't want a second subscription, that's a reasonable choice. The prompts in this catalog work there too.

Going deeper

Appendix B of The Solo Consultant's AI Playbook goes chapter by chapter through when to reach for Claude and when ChatGPT is the closer fit, across the eight workflows.

Which tool you pick is the smaller decision. What decides the output is how much the model can see without being told, and that's a question of setup, not vendor. On the Claude side, the Claude Workspace Kit is our answer: the context files, the written standards, and the six briefs a folder carries.

Everything we make for setting Claude up to do client work is on one page: Claude for Solo Consultants.

— Digital Kreative