If your EOS® company is not yet ready for a full agent layer with scheduled execution, the lowest-effort win in the entire AI integration story is using ChatGPT Custom GPTs or Claude Projects to operationalize parts of your V/TO™.
Neither tool is an agent in the strict sense (they wait for a human prompt). Both are dramatically more useful than typing into a blank ChatGPT or Claude window each time, because they carry the company's voice, instructions, and supporting documents into every conversation.
This post compares the two for EOS®-specific workflows and tells you which one to use for which job.
What each is
ChatGPT Custom GPTs. OpenAI's product. You define a system prompt, optionally attach files, optionally configure actions (API calls), and the resulting GPT is available to anyone in your ChatGPT Team or Enterprise workspace. Comes with built-in browsing, code interpreter, image generation, and other tools.
Claude Projects. Anthropic's product. You define standing instructions for the project, attach reference files, and every conversation in the project inherits both. Available in Claude.ai Pro, Team, and Enterprise.
Both are mature, well-supported, and credible for business use at the enterprise tier. Both work for the workflows below.
Workflow one: brand voice for marketing drafts
Goal: Anyone on the team can produce on-brand cold outreach, blog drafts, social posts, or sales follow-ups without manually pasting in voice guidelines every time.
What to put in the GPT or Project. Marketing Strategy from the V/TO™ verbatim. A short voice document (allowed phrases, forbidden phrases, tone notes). Two or three example pieces in your house voice. The Proven Process verbatim.
Verdict: Both work equally well. Pick the one your team already uses. We use both at Sneeze It for different audiences.
Workflow two: L10® prep helper
Goal: The Integrator drops in last week's Scorecard, Rocks status, and Issues List, and the assistant produces a clean meeting prep document.
What to put in the GPT or Project. The L10® agenda structure. Rules about time boxes. The IDS framework. The format for the prep doc the team is used to. The V/TO™ for context.
Verdict: Lean Claude Projects for the long-context tasks (reading a quarter of Scorecards). Lean Custom GPTs if the team is already in ChatGPT for everything else. The output quality is similar; the friction difference is what matters.
Workflow three: V/TO™ sharpener
Goal: Stress-test the V/TO™ before a quarterly. Surface fuzzy language. Propose sharper alternatives. Catch contradictions between sections.
What to put in the GPT or Project. Current V/TO™. Last quarter's Scorecard. Last quarter's Issues themes. A prompt that says "you are a loyal critic of this V/TO™. Find the weaknesses."
Verdict: Claude Projects, lightly. Anthropic's models tend to be a touch sharper on this critical-analysis work, in my testing. Custom GPTs work too. The difference is small enough that either is fine.
Workflow four: prospect research before sales calls
Goal: Before a sales call, the rep drops in the prospect's name, company, and website, and gets a one-page brief.
What to put in the GPT or Project. Your ICP definition. The Three Uniques. The Proven Process. The Guarantee. Optional: a custom action for web browsing or for hitting your enrichment APIs.
Verdict: ChatGPT Custom GPTs with actions and web browsing usually win here, because Custom GPTs have a deeper ecosystem of pre-built integrations. Claude Projects work for the analysis half but require more setup for the data-fetching half.
Workflow five: meeting notes structured for IDS
Goal: After a client or internal meeting, paste in the transcript and get back a structured "Identify, Discuss, Solve" list of any issues the meeting surfaced.
What to put in the GPT or Project. The IDS framework. Example outputs in your team's format. Rules about what counts as an Issue vs a To-Do.
Verdict: Both work. Slight lean to Claude Projects for transcripts longer than 50,000 words because the context handling is steadier in our experience.
Workflow six: scorecard definition tightening
Goal: Walk each Scorecard row and have the assistant propose tighter definitions, edge cases, and exclusion rules.
What to put in the GPT or Project. Current Scorecard. Definitions in their current state. A prompt that says "for each row, propose a sharper definition that an agent could implement deterministically."
Verdict: Either. This is straightforward analysis work. Use whichever tool the Integrator is already in.
Workflow seven: V/TO™ rewriter for stakeholder audiences
Goal: Take the same V/TO™ and produce derivative versions for different audiences. Internal team. New hire recruiting. Investor deck. Customer-facing summary.
What to put in the GPT or Project. Current V/TO™. Voice document. Templates for each derivative.
Verdict: Both work. Custom GPTs slightly easier to share with non-technical team members. Claude Projects produce slightly better long-form writing in my experience.
What neither one is good for
Three things both products struggle with as of writing.
Scheduled execution. Neither Custom GPTs nor Claude Projects run on a schedule by default. If you want the L10® brief produced every Tuesday at 7 a.m. without a human pressing a button, you need a true agent layer. Both vendors offer APIs for this. The Custom GPT or Project itself does not run autonomously.
Multi-step tool use with branching logic. Both products are improving here but neither is yet the right tool for complex multi-step workflows. For "read this CRM, filter these prospects, validate emails, draft personalized outreach, queue for send," you want the API-level Claude Code or OpenAI Assistants API.
Persistent memory across conversations. Both products have improving memory features but the granular control needed for agent-style work is better served by storing context in your own files and including them in each run.
The recommendation if you are just starting
Pick one. The differences are smaller than the marketing makes them sound. The bigger lever is using either one for two or three of the workflows above, consistently, for 30 days.
If your team is heavy on Microsoft 365 and uses ChatGPT Enterprise, lean Custom GPTs. The integration ecosystem is wider and the team is already there.
If your team uses Slack and prefers terminal-style or markdown-style work, lean Claude Projects. The model handles longer context cleanly and the project structure maps to file-based workflows.
If you have both subscriptions, run them in parallel for different jobs and let the team's preference settle naturally. Both are fine.
What you put in either matters more than which you pick
The V/TO™ section in either tool is the same V/TO™. The brand voice document in either tool is the same document. The IDS framework in either tool is the same framework.
The work that makes Custom GPTs and Claude Projects useful is the work of writing the standing instructions sharply and curating the reference documents well. That work is portable between vendors. Do it once, paste it into both if you want.
The reason most teams' Custom GPTs and Claude Projects underperform is that the standing instructions are vague and the reference documents are stale. Sharpen the V/TO™. Tighten the voice document. Update the example outputs. The tool gets sharper without changing vendors.
FAQ
Should non-leadership team members have access to Custom GPTs or Claude Projects with the V/TO™? Yes. The V/TO™ is internal but should be visible to the whole team. Locking it down defeats the point of the framework.
What about data privacy on Custom GPTs and Claude Projects? Use the enterprise tier. Both vendors offer zero training on customer data and SSO controls at that level. Do not use free or prosumer tiers for V/TO™-bearing or client-data-bearing work.
Can we move from Custom GPTs to Claude Projects later? Easily. The content (instructions and reference files) is portable. The actions or browser tools may need rebuilding on the new platform.
Are these going to be replaced by real agents in our company? Some will. The Custom GPT or Project version is the on-ramp. Once you know which workflows are most valuable, those graduate to full API-based agents with scheduled execution. The Custom GPT remains useful for ad hoc work that does not need to run automatically.
EOS®, Entrepreneurial Operating System®, V/TO™, Vision/Traction Organizer™, Marketing Strategy, Level 10 Meeting®, L10®, Rocks™, Scorecard, Issues List, IDS, Three Uniques, Proven Process, and Integrator are concepts and trademarks of EOS Worldwide, LLC. Custom GPTs, ChatGPT, and the OpenAI API are products of OpenAI. Claude Projects, Claude, and the Anthropic API are products of Anthropic. This article is an independent practitioner perspective and is not affiliated with or endorsed by EOS Worldwide, OpenAI, or Anthropic.