This is the question every Visionary and Integrator asks me eventually. Should we be on Claude or ChatGPT. Anthropic or OpenAI. Which do you use. Why.
The honest answer for most EOS® companies is that the model choice is the smallest decision in the entire AI integration. The hardest decisions are about discipline, definitions, and accountability. Once those are right, either vendor works. Once those are wrong, neither vendor saves you.
That said, the vendors are not identical. Here is the practitioner read.
What they are
Anthropic is a US-based AI safety lab that makes the Claude family of models. As of this writing the production models include Claude Opus and Claude Sonnet at the high end and Claude Haiku for lighter workloads. Anthropic also ships Claude Code, a terminal-based coding and agent platform, and a hosted API.
OpenAI is a US-based AI company that makes the GPT and o-series models behind ChatGPT, the OpenAI API, the Assistants API, and Custom GPTs. OpenAI also has the largest consumer footprint, which means a chunk of your team is already on ChatGPT whether the Integrator knows it or not.
Both companies offer enterprise tiers with zero training on customer data, single sign-on, audit logs, and admin controls. Both are credible for serious business use.
What actually matters for an EOS® company
Five criteria, in order.
One, who on your team is already fluent. If half your team uses ChatGPT every day and almost no one has tried Claude, picking Claude adds a learning curve tax on top of an already disruptive change. Pick the model your team already uses unless there is a sharp reason to switch.
Two, where your operating data lives. If your data is in Google Workspace, Notion, Slack, Microsoft 365, and standard SaaS, both Anthropic and OpenAI have integrations or can be wired up. If your data is local files or a self-hosted environment, Claude Code is an unusually direct fit because it runs in the terminal.
Three, the type of work you need. For long-context reasoning (reading a quarter of meeting notes, parsing a long V/TO™, comparing many scorecards), Claude Opus tends to perform well in our experience. For wide tool ecosystems and pre-built integrations, OpenAI has more options on the shelf. For everyday drafting, summarization, and Q&A, both are excellent.
Four, your willingness to engineer. OpenAI's Custom GPTs and Assistants API are very accessible to non-technical builders. Claude Code is more powerful for engineering-heavy stacks but assumes a builder who is comfortable in a terminal. If you have zero internal technical capacity, OpenAI's surfaces are usually easier on a first agent.
Five, your risk posture on data. Both Anthropic and OpenAI offer zero-training enterprise plans. If your industry has compliance requirements (healthcare, finance, regulated services), both can support those at the right tier. Sign the right BAA or DPA. Do not use consumer tiers for V/TO™-containing or client-data-containing workflows.
Notice what is not on that list. Model benchmark scores. Marketing hype. Recent product launches. Twitter consensus this week. None of that should drive your decision for an EOS® company.
What we chose at Sneeze It and why
We use Anthropic's Claude Code as our primary platform. We picked it for three reasons specific to our operation.
First, our agent stack lives in a local folder structure on each operator's laptop. Markdown SOPs, file-based scorecards, cron schedules. Claude Code runs in the terminal where those files live, with no hosting layer between the agent and the data.
Second, we run a lot of agents in parallel, and the discipline of file-based context (read this file, write to that file) maps naturally to how Claude Code thinks about its workspace. Our Integrator can read any agent's last week of output by opening a folder.
Third, my read on Anthropic's research and product behavior is that they spend more visible attention on refusal, alignment, and honest pushback than most other labs. For agents that act in the world, I want a model that will say "this is risky, here is what I see" rather than one that completes the request and asks forgiveness later. Claude has done that for us repeatedly. OpenAI's recent models do this well too. It is not a clean delta but it tipped my call.
None of those reasons should be your reasons. They are mine.
What about hybrid
Many sophisticated companies end up running both. Claude for long-context strategic work, ChatGPT for everyday team productivity, Custom GPTs for marketing or sales workflows, and an internal agent built on whichever API the builder is most fluent with.
This is fine. The risk is fragmenting your operating layer across two vendors. To do hybrid well, keep one source of truth for your V/TO™ preamble and feed it into both surfaces. Same instructions, two vendors. Otherwise the agents on Claude and the assistants on ChatGPT drift apart.
What about other vendors
Google's Gemini, Microsoft's Copilot, and a handful of open-weight models from Meta, Mistral, and others are all credible alternatives. The framework in this post applies to all of them. The criteria do not change.
For most small and mid-sized EOS® companies, the choice is realistically between Anthropic and OpenAI today, with Microsoft Copilot a close third for Microsoft-shop teams.
Switching costs
A common worry: "If we pick Anthropic now and want to switch to OpenAI later, are we trapped."
If you build your operating layer correctly, no. The V/TO™ preamble is portable. SOPs are markdown. Scorecards are spreadsheets or files. The thing that is harder to move is the specific platform features (Claude Code's terminal pattern, ChatGPT's Custom GPTs, the Assistants API thread structure). Those have to be rewritten.
Plan for portability from day one. Keep the company's instructions and definitions as text in your repo, not as platform-specific configuration. Then the model is replaceable. The discipline is not.
FAQ
Is one company more accurate than the other? They trade leadership on benchmarks every few months. For most EOS® workflows the accuracy difference is invisible. Discipline matters more than the last 2% on a benchmark.
Is one safer with our data? Both offer enterprise-grade no-training plans. Both are credible. Read the contract you sign.
What about pricing? Both have variable usage pricing. Costs are usually surprisingly small for an EOS® workflow stack. Track usage during the first month and tune. Most companies under 50 people spend less per month than a single human hire would cost per week.
What about Google Gemini or Microsoft Copilot? Both credible, both increasingly capable. If your company is heavily on Microsoft 365 or Google Workspace, the native integrations may matter. Apply the same five criteria.
EOS®, Entrepreneurial Operating System®, V/TO™, Level 10 Meeting®, L10®, Rocks™, Scorecard, and Visionary are concepts and trademarks of EOS Worldwide, LLC. Claude, Claude Code, and Claude Opus are products of Anthropic. ChatGPT and the OpenAI API are products of OpenAI. This article is an independent practitioner perspective and is not affiliated with or endorsed by EOS Worldwide, Anthropic, or OpenAI.