# ChatGPT — Complete Agent Context (llms.txt) > Everything on openclawdatabase.com about ChatGPT, in one fetch. Generated 2026-06-11. > Tell your agent: "read https://openclawdatabase.com/chatgpt/llms.txt and help me set up ChatGPT." ## Pages in this bundle - ChatGPT Agents Guide 2026 — Custom Agents, Cost, Comparison — https://openclawdatabase.com/chatgpt/ - ChatGPT Agent Mode — What It Does & How to Use It (2026) — https://openclawdatabase.com/chatgpt/agent-mode/ - ChatGPT vs the OpenAI API — When to Use Which (2026) — https://openclawdatabase.com/chatgpt/api-vs-chat/ - Custom GPTs Deep Dive 2026 — Building, Sharing, Privacy — https://openclawdatabase.com/chatgpt/custom-gpts/ - ChatGPT FAQ — Community Questions Answered (2026) — https://openclawdatabase.com/chatgpt/faq/ - How to Stop ChatGPT Using Repetitive Writing Patterns (2026) — https://openclawdatabase.com/chatgpt/faq/chatgpt-writing-patterns/ - ChatGPT Memory — How It Works & How to Manage It (2026) — https://openclawdatabase.com/chatgpt/memory/ - ChatGPT Pricing 2026 — All 6 Tiers & Per-Tool Billing Explained — https://openclawdatabase.com/chatgpt/pricing/ - Custom GPT Setup Guide 2026 — Create, Configure, Publish — https://openclawdatabase.com/chatgpt/setup/ - ChatGPT for Teams & Business — Full Setup Guide (2026) — https://openclawdatabase.com/chatgpt/teams/ - Advanced ChatGPT Tips 2026 — Prompts, Agents, Cost Optimization — https://openclawdatabase.com/chatgpt/tips/ - ChatGPT vs OpenClaw 2026 — Which Agent Platform? — https://openclawdatabase.com/chatgpt/vs-openclaw/ ================================================================ # ChatGPT Agents Guide 2026 — Custom Agents, Cost, Comparison URL: https://openclawdatabase.com/chatgpt/ Last updated: 2026-05-10 ================================================================ 🤖 # ChatGPT OpenAI's hosted agent platform — no self-hosting, per-tool-call billing, Custom GPTs for non-technical teams, and GPT-5.4 advanced reasoning. 6 pricing tiers: Free → Go → Plus → Pro → Business → Enterprise GPT-5.4 with advanced reasoning and Agent Mode Per-tool-call API billing (separate from token cost) 100M+ users ChatGPT is OpenAI's fully hosted custom agent platform — no servers to run, no infrastructure to manage, and a polished web UI that non-technical users can operate on day one. You set a system prompt, attach tools (web search, code interpreter, file analysis, custom API calls), and share via a link. The tradeoff: you're locked to OpenAI's models, infrastructure, and privacy practices. For users who prioritize ease-of-use and don't need model flexibility, it's unmatched. For privacy-conscious teams or high-volume use cases where cost control matters, [OpenClaw](https://openclawdatabase.com/openclaw/) may be better long-term. Critical: Sora video generation has shut down As of April 2026, Sora video generation capability has been discontinued across all ChatGPT tiers and is no longer available via API. Any workflows relying on Sora must be migrated to external video generation services or archived. Guides [🏗️ Custom GPT Setup Guide Step-by-step: create a Custom GPT, add system instructions, attach tools (web search, code interpreter, file upload, custom APIs), test in the Chat Playground, configure sharing (private/link-only/public), and publish. Covers team organization and Custom GPT naming best practices. Live](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing All 6 tiers broken down with feature gates, usage limits, and exact pricing. Deep dive into per-tool-call billing with worked examples — how each tool call adds to your bill separately from token costs. Comparison table: ChatGPT vs OpenClaw vs Claude Cowork on monthly cost. Live](https://openclawdatabase.com/chatgpt/pricing/) [🛠️ Custom GPTs Deep Dive What Custom GPTs are (formerly "apps"), capabilities, limitations, and how they differ from Chat conversations with system prompts. Building vs using shared GPTs. Privacy model, sharing controls, and monetization options. Common use cases with examples. Live](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses the web, runs code, chains tools across multi-step tasks. Full breakdown of capabilities, what it can't do, safety boundaries, tier access, cost, and when to use it vs a Custom GPT or the API. Live New](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What ChatGPT's Memory actually stores, how to view and edit entries, the privacy implications, and the gotchas most users miss (selective inference, persistence after disabling, Custom GPT scope). Tier-by-tier feature breakdown. Live New](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business ChatGPT Business and Enterprise workspaces — full setup. Seats, roles, SSO, SCIM, shared Custom GPTs, admin controls, data-handling guarantees, and cost per seat. When to pick Business vs Enterprise vs individual Plus subscriptions. Live New](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API Two different products from the same company. When ChatGPT wins, when the API wins, and when to use both. Cost worked examples, migration patterns (Custom GPT → API), and the most common "use both" configuration for software teams. Live New](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw Full comparison: security, privacy, control, cost, and flexibility. Setup time, learning curve, team capabilities. Step-by-step migration guide for moving system prompts, custom tools, and conversation context from ChatGPT to OpenClaw. Decision matrix to help you choose. Live](https://openclawdatabase.com/chatgpt/vs-openclaw/) [✨ Advanced ChatGPT Tips Prompt engineering for agents, system prompt best practices, tool integration strategies, and cost optimization for teams. Tricks to reduce tool-call overhead, handling long conversations without token overages, and debugging when Custom GPTs underperform. Live](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ Top community questions from r/ChatGPT and r/OpenAI answered — writing-pattern quirks, Memory feature gotchas, Agent Mode boundaries, and pricing-tier confusion. Sourced and updated weekly. Live](https://openclawdatabase.com/chatgpt/faq/) Is ChatGPT right for your use case? ChatGPT is ideal for teams that need to get started with zero setup and want non-technical members to author custom agents. It's less ideal if you need: model flexibility (swapping Claude, Gemini, or local Ollama), offline capability, tight cost control at high volumes (>10k daily interactions), or full team privacy with your own infrastructure. For those use cases, see [OpenClaw](https://openclawdatabase.com/openclaw/), [Hermes](https://openclawdatabase.com/hermes/), or [Claude Cowork](https://openclawdatabase.com/claude-cowork/). Many teams run ChatGPT Plus for team documents AND OpenClaw for personal automation in parallel — they don't conflict. ## At a Glance | Factor | Detail | | --- | --- | | **What it is** | OpenAI's hosted custom agent platform | | **Infrastructure** | Fully hosted by OpenAI — no setup or management required | | **Primary model** | GPT-5.4 (full), GPT-4o (Plus/Pro), GPT-4o mini (Free/Go) | | **Model locked** | Yes — OpenAI models only, no alternatives | | **Pricing model** | Subscription (Free/$8/$20/$200/mo) + per-token API + per-tool-call API billing | | **6 tiers** | Free · Go ($8) · Plus ($20) · Pro ($200) · Business ($25/user) · Enterprise (custom) | | **Setup time** | Minutes — no install, no API keys for Plus/Pro tier users | | **Custom GPTs** | Yes — no coding required, system prompt + tools + sharing controls | | **Agent Mode** | Yes — model has autonomy to use tools without asking permission per-step | | **Tool ecosystem** | Built-in (web search, code interpreter, file analysis); custom APIs via system prompt | | **Privacy model** | OpenAI infrastructure; Business/Enterprise get data residency options | | **Team sharing** | Custom GPTs can be shared via link; Business tier has workspace management | | **Time to first useful output** | Under 5 minutes — create Custom GPT, set prompt, attach tool, test, publish | | **Can embed in customer products** | Yes via API, with separate per-token/per-tool billing | | **Offline capability** | No — requires active internet connection to OpenAI servers | | **Model flexibility** | No — locked to GPT models only | ## ChatGPT Use Cases ChatGPT shines for low-setup individual workflows and Custom GPTs — the use cases below are the ones it does best. - [Social content engine](https://openclawdatabase.com/use-cases/social-content/) — Custom GPTs with brand-voice memory - [Lead research](https://openclawdatabase.com/use-cases/lead-research/) — pairs well with ChatGPT's web search - [Daily journal](https://openclawdatabase.com/use-cases/daily-journal/) — Memory feature is the canonical use case - [All 12 use cases →](https://openclawdatabase.com/use-cases/) ## ChatGPT Troubleshooting - [Custom GPT action returns 401](https://openclawdatabase.com/troubleshooting/#custom-gpt-action-401) — auth must be set in the GPT builder, not the spec - [All troubleshooting entries →](https://openclawdatabase.com/troubleshooting/) ## ChatGPT Security - [Custom GPT Action supply chain](https://openclawdatabase.com/security/mcp-supply-chain/) — every Action sends data to a third-party API; audit before installing - [Secrets & credentials](https://openclawdatabase.com/security/secrets/) — Memory persists across conversations; be deliberate - [Prompt injection](https://openclawdatabase.com/security/prompt-injection/) — applies to every agent that reads wide - [15-minute hardening checklist](https://openclawdatabase.com/security/checklist/) See also: [OpenClaw](https://openclawdatabase.com/openclaw/) · [Hermes](https://openclawdatabase.com/hermes/) · [Claude Cowork](https://openclawdatabase.com/claude-cowork/) · [ChatGPT vs OpenClaw](https://openclawdatabase.com/chatgpt/vs-openclaw/) · [Decision guide](https://openclawdatabase.com/compare/) ## Latest ChatGPT News Recent releases, tutorials, and video summaries: [▶ How OpenAI's Finance Team Uses Codex for Month-End Reports and Dashboards 2026-06-09](https://openclawdatabase.com/news/videos/2026-06-09-codex-finance-reports/) [▶ Codex as Your AI Data Analyst: Business Reports and Google Slides in Minutes 2026-06-09](https://openclawdatabase.com/news/videos/2026-06-09-codex-data-science/) [▶ Codex 4.0 App Updates: App Shots, Goal Mode, Computer Use, and Plugin Sharing 2026-05-28](https://openclawdatabase.com/news/videos/2026-05-28-codex-40-upgrades/) [▶ 100 Hours Testing Claude Code vs ChatGPT Codex — Honest Results 2026-05-26](https://openclawdatabase.com/news/videos/2026-05-26-claude-code-vs-chatgpt-codex-100-hours/) [See all ChatGPT news (9) →](https://openclawdatabase.com/news/chatgpt/) ================================================================ # ChatGPT Agent Mode — What It Does & How to Use It (2026) URL: https://openclawdatabase.com/chatgpt/agent-mode/ Last updated: 2026-05-10 ================================================================ # ChatGPT Agent Mode — What It Does & How to Use It Agent Mode is OpenAI's name for ChatGPT's autonomous task execution — it browses the web, runs code, opens files, and chains tools across multiple steps to complete a goal you describe in a single prompt. Where a regular ChatGPT response gives you text, Agent Mode gives you a finished artifact (a report, a comparison spreadsheet, a booking, a refactored codebase). This page covers what it actually does today, where it falls short, how to use it safely, and what it costs. The 30-second answer Agent Mode = ChatGPT + a sandboxed browser + Python + file tools + a planning loop. Available on Plus, Pro, Business, and Enterprise. Best for research, data wrangling, and form-filling. Not yet reliable for high-stakes financial or security-sensitive actions — and there's no full undo. ## What Agent Mode can do today - **Browse the live web** — open URLs, click links, fill forms, screenshot pages, extract structured data. Reads JavaScript-rendered content (unlike API web-search, which is text-only). - **Run code** — Python in a sandboxed Code Interpreter environment. Read your uploaded files, process them, return results. - **Use multiple tools in sequence** — search → click → extract → process → output. The planner decides which tool to invoke for each sub-step. - **Resume long tasks** — Agent Mode runs can span 5–20 minutes of autonomous work. You can leave the tab and return to a finished result. - **Hand off to the user when stuck** — when it hits a login wall, CAPTCHA, or ambiguous instruction, it pauses and asks you a clarifying question before continuing. ## What Agent Mode *can't* reliably do (yet) - **Make purchases or financial transactions** — Agent Mode will plan a checkout flow but stops at the "confirm purchase" step, asking you to complete it manually. This is a deliberate safety boundary, not a bug. - **Access local files outside the chat** — Agent Mode runs in OpenAI's sandbox, not on your machine. It can only see files you've explicitly uploaded to the conversation. - **Use your existing browser sessions / cookies** — every Agent Mode run starts with a clean browser. It cannot impersonate you on sites where you're already logged in. - **Handle dynamic-only sites with strong bot detection** — sites with aggressive anti-bot measures (Cloudflare Turnstile, hCaptcha) often block Agent Mode mid-task. - **Maintain state across separate runs** — each Agent Mode session is independent. If you want persistent memory across runs, see the [Memory feature guide](https://openclawdatabase.com/chatgpt/memory/). ## How to start an Agent Mode run 1. Open ChatGPT (web app or desktop). 2. Below the input box, click the **tools menu** (icon next to attachments). 3. Select **Agent Mode**. The input area expands and shows "Agent Mode active." 4. Describe the task in one prompt. The more concrete, the better — Agent Mode is bad at "make a website" but good at "find the 5 most-recent papers on retrieval-augmented generation, summarize each in two sentences, and put them in a table I can copy into Notion." 5. Watch the planning panel on the right — it shows each sub-step (browse, click, extract, run code) as Agent Mode executes. You can stop at any time. 6. When Agent Mode completes, it returns a structured summary plus any artifacts (markdown tables, downloadable files, screenshots). ## Where Agent Mode genuinely earns its keep From real-world testing in April 2026, these are the workflows where Agent Mode reliably beats both manual work and using regular ChatGPT: - **Competitive research:** "Compare the pricing pages of these 8 SaaS companies on these 4 features. Output a markdown table." - **Data collection from public sources:** "Pull the last 30 days of release notes from these 5 GitHub repos and group them by category." - **Form-filling and intake:** "Read this PDF, extract these 12 fields, and fill out the corresponding fields in this Google Form. Show me a screenshot before submitting." - **Spreadsheet wrangling:** "Read these 3 uploaded CSVs, find the rows where customer_id matches across all three, output a combined sheet." - **Booking research (not booking itself):** "Find me 5 flights from JFK to LHR next Friday under $700, return-trip, no overnight layovers." Agent Mode does the research; you do the booking. ## Safety boundaries — what OpenAI built in Agent Mode has explicit guardrails that prevent it from completing certain actions even if you ask: | Action category | Behavior | | --- | --- | | Purchases / payments | Plans the flow, stops at confirmation, asks user to complete manually | | Posting public content (social media, forums) | Drafts the post in the chat, never submits without explicit confirmation | | Email sending | Drafts the email, never sends — you copy and send yourself | | Account creation / signup | Refuses; tells you to sign up yourself | | Submitting forms with sensitive data | Halts at the field requesting SSN, payment, or ID and asks for confirmation | | Following links from untrusted observed content | Refuses by default; treats observed instructions as untrusted | These boundaries follow the same logic as our cross-platform [prompt-injection guidance](https://openclawdatabase.com/security/prompt-injection/). They limit Agent Mode's usefulness for some workflows but they're the right defaults given current LLM reliability. ## How much it costs Agent Mode usage counts against your ChatGPT tier's monthly cap, with per-tool-call surcharges layered on top: | Tier | Agent Mode runs/month | Per-tool-call | | --- | --- | --- | | Free | Not available | — | | Plus ($23/mo) | ~50 runs | Included | | Pro (~$200/mo) | Unlimited "fair use" | Included | | Business (per seat) | 200+/seat/month | Pooled across seats | | Enterprise | Custom | Custom | A typical Agent Mode run uses 8–15 tool calls. Browsing-heavy runs (research, comparison) burn more; code-heavy runs (file processing) burn fewer. See the [pricing deep-dive](https://openclawdatabase.com/chatgpt/pricing/) for worked examples. ## When to use Agent Mode vs a Custom GPT vs the API | Use case | Best fit | Why | | --- | --- | --- | | One-off multi-step research task | Agent Mode | No setup, full browsing, completes autonomously | | Repeated task with a stable system prompt | [Custom GPT](https://openclawdatabase.com/chatgpt/custom-gpts/) | Save the prompt + tools, run it daily with one click | | Programmatic / scripted task | [OpenAI API](https://openclawdatabase.com/chatgpt/api-vs-chat/) | Lower per-token cost at volume, full control over the loop | | Long-running scheduled task | [Hermes](https://openclawdatabase.com/hermes/) or [OpenClaw](https://openclawdatabase.com/openclaw/) | Agent Mode is interactive; long-horizon agents are a different category | | Coding inside an IDE | [Kilo Code](https://openclawdatabase.com/kilocode/) or [Claude Code](https://openclawdatabase.com/claude-cowork/) | Agent Mode is not IDE-integrated; dedicated coding agents have file-tree context | ## Common gotchas - **Agent Mode "drifts" on long runs.** Beyond 15–20 minutes of autonomous work, output quality drops sharply. Break large tasks into focused sub-tasks. - **Login walls stop it cold.** Many target sites require authentication. Either feed Agent Mode the data directly (uploaded CSV, PDF) or pick public-data tasks. - **The "browse the web" panel sometimes hangs.** If a run shows no activity for >2 minutes, click "Stop" and restart. It usually completes the second try. - **Output formatting drift.** If you ask for a markdown table and Agent Mode returns prose, add "Output only a markdown table with these columns: X, Y, Z" to the prompt. - **Privacy:** Agent Mode interactions are logged in your ChatGPT history. For sensitive research, use a Project (Pro+) so the conversation is contained. ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ← Back to [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · Next: [Memory feature →](https://openclawdatabase.com/chatgpt/memory/) ================================================================ # ChatGPT vs the OpenAI API — When to Use Which (2026) URL: https://openclawdatabase.com/chatgpt/api-vs-chat/ Last updated: 2026-05-10 ================================================================ # ChatGPT vs the OpenAI API — When to Use Which ChatGPT and the OpenAI API are different products from the same company, share the underlying models, but solve different problems. ChatGPT is a consumer/team product with a polished UI, Custom GPTs, Memory, and Agent Mode. The API is a developer service — same models, no UI, paid per token. The wrong choice burns money on one end or limits your capabilities on the other. This page lays out the decision concretely. The 30-second answer **Humans chatting:** ChatGPT. **Code calling the model programmatically:** OpenAI API. **You're using ChatGPT 8 hours a day:** the Pro tier is cheaper than equivalent API spend. **You're building an app for your users:** the API is the only option. **Many teams use both** — ChatGPT for humans, API for production code. ## Side-by-side | | ChatGPT | OpenAI API | | --- | --- | --- | | What it is | Consumer/team product with UI | Developer service — REST/SDK only | | Pricing model | Flat monthly subscription | Per token + per tool call | | UI / Chat interface | Built-in, polished | You build it yourself | | Custom GPTs | Yes — share with link or workspace | No (you implement equivalent in your app) | | Memory feature | Yes (auto + manual) | You implement (vector DB, etc.) | | Agent Mode | Yes (interactive) | You build via tool-use + Assistants API | | File upload + Code Interpreter | Built-in | Available via Assistants / Tool use API | | Models available | GPT-5.4 / 5.5 / o1 / o3 | All ChatGPT models + older + fine-tuned | | Fine-tuning | No | Yes | | Rate limits | Tier-based message cap | Tier-based TPM/RPM cap | | Data used for training | Free/Plus: opt-out · Business+: never | Never by default | | Best for | Humans, teams, one-off tasks | Apps, scripts, batch jobs, embedded agents | ## When ChatGPT wins - **You're a person, not an app.** ChatGPT's UI, Custom GPTs, file upload, voice mode, and Agent Mode are all built — using the API to replicate them is a 6-month engineering project. - **You use it 4+ hours a day.** Pro at ~$200/mo is roughly equivalent to ~40M tokens/mo at API rates on GPT-5.4. If you'd burn through that, the flat fee is cheaper. - **You want non-technical teammates to build agents.** Custom GPTs let anyone author and share a "specialized ChatGPT" with no code. The API requires a developer. - **You need vision, voice, and tool-use UI integrated.** All three work out of the box in ChatGPT. Wiring them up over the API is several days of glue code. - **You want zero infra.** No keys to rotate, no rate limits to monitor, no error handling to write. ## When the OpenAI API wins - **You're building software** that calls the model on behalf of users. ChatGPT is a destination product; the API is a building block. - **Volume is high and per-request load is unpredictable.** Per-token pricing scales linearly — at scale the API typically beats ChatGPT Pro per useful output, especially when you can route cheaper tasks to smaller/cheaper models. - **You need fine-tuning** on your own data. Not available in ChatGPT. - **You need older or specialized models.** GPT-3.5, embedding models, moderation, fine-tuned variants — only via API. - **You need to embed the model in your product UI** rather than have users go to chatgpt.com. - **You need batch processing.** The Batch API discounts non-real-time workloads ~50% vs synchronous API calls. - **You need granular control** — temperature, top_p, system prompts per-call, function calling, structured outputs. ChatGPT exposes a subset; the API exposes everything. ## The "use both" pattern Many teams use ChatGPT for human productivity AND the API for production code: - **Internal team:** ChatGPT Business for writing, research, prototyping, and ad-hoc tasks. - **Production:** OpenAI API to power features inside your app — completions, embeddings, semantic search, retrieval-augmented generation. - **Same billing entity, different cost lines.** Both can be on the same OpenAI org. ChatGPT Business shows as a single line; API usage shows as per-token billing in the same dashboard. This is the most common configuration for any company that builds software AND has employees who use AI to do their jobs. ## Cost worked examples ### Light personal use — 30 conversations/week, ~50K tokens/conv - **ChatGPT Plus:** $23/mo. Fits easily within the message cap. - **Equivalent API:** ~6M tokens/mo × ~$2.50/M tokens on GPT-5.4 ≈ $15/mo + dev time to build UI. - **Winner:** ChatGPT Plus. Saves the build cost; price difference is negligible. ### Heavy daily use — Agent Mode runs, code interpreter, full workday - **ChatGPT Pro:** ~$200/mo, unlimited fair-use. - **Equivalent API:** 40M+ tokens/mo on GPT-5.4 plus tool-call surcharges ≈ $150–250/mo. - **Winner:** ChatGPT Pro for the UI + Memory + Agent Mode integration. API would require building all of that. ### App with 10,000 users, each ~20K tokens/day - **ChatGPT:** not viable — ChatGPT is per-seat, not per-end-user. - **OpenAI API:** 200M tokens/day × ~$2/M tokens (mostly cheaper models) ≈ $400/day = $12K/mo. - **Winner:** API, by definition — this is its use case. ## Migration patterns ### From ChatGPT Custom GPT → API-backed product 1. Export the Custom GPT's system prompt (Settings → Edit GPT → copy "Instructions"). 2. Use it as the `system` message in API calls. Same model = same behavior. 3. For tools, the Custom GPT's "Actions" map to the API's **function calling** / **tool use** features. Re-implement each action as a tool definition. 4. For knowledge files, build a retrieval-augmented generation (RAG) layer over your files using embeddings + a vector store. 5. Test side-by-side with the Custom GPT to confirm behavior matches before cutting over. ### From API directly → through Claude Cowork or Kilo Code If your team is hand-rolling raw API calls and you'd prefer to consolidate, check out [Claude Cowork vs API](https://openclawdatabase.com/claude-cowork/vs-api/) or [Kilo Code](https://openclawdatabase.com/kilocode/) — both give you a managed agent layer over models from multiple providers. ## Related on this site - [ChatGPT pricing & per-tool-call billing](https://openclawdatabase.com/chatgpt/pricing/) — full tier breakdown - [Cost calculator](https://openclawdatabase.com/tools/cost-calculator/) — model your monthly cost across API and subscription paths - [Claude Cowork vs API vs OpenClaw](https://openclawdatabase.com/claude-cowork/vs-api/) — the same comparison on the Anthropic side - [OpenClaw](https://openclawdatabase.com/openclaw/) — self-hosted agent that calls the OpenAI API (and others) under the hood ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ← Back to [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · Previous: [Teams & Business](https://openclawdatabase.com/chatgpt/teams/) ================================================================ # Custom GPTs Deep Dive 2026 — Building, Sharing, Privacy URL: https://openclawdatabase.com/chatgpt/custom-gpts/ Last updated: 2026-04-12 ================================================================ # Custom GPTs Deep Dive — Building, Sharing, Privacy, Monetization Custom GPTs (formerly called "GPT apps") are shareable ChatGPT instances with custom system prompts, tools, and knowledge files. This guide covers what they are, how they work, the difference between building and using Custom GPTs, privacy implications, and monetization options. ## What Are Custom GPTs? A Custom GPT is a persistent, shareable ChatGPT agent with: - **System instructions** — A custom prompt that defines the agent's role, tone, and behavior - **Tools** — Web search, code interpreter, file analysis, or custom API calls - **Knowledge base** — Uploaded files (PDFs, CSVs, images) that the agent can reference - **Sharing controls** — Private, link-only, public (GPT Store), or workspace-only **How it differs from a Chat conversation:** In a normal ChatGPT conversation, you can add a system prompt in the chat, but it's ephemeral — it exists only for that conversation. A Custom GPT is a durable artifact with its own URL, analytics, and configuration interface. It's designed for reuse and sharing. **Example Custom GPTs:** - "Code Reviewer" — Takes code snippets, reviews them for style/performance, provides feedback - "Customer Support Bot" — Answers FAQs using your company handbook, escalates complex issues - "Data Analyst" — Analyzes CSV uploads, generates charts, summarizes findings - "Prompt Optimizer" — Refines user-provided prompts for better LLM output ## Custom GPT Capabilities ### System Prompts Define the agent's role, expertise, communication style, and hard constraints. A well-crafted system prompt is 80% of a Custom GPT's value. ### Web Browsing The Custom GPT can search the internet and read web pages in real-time. Useful for current events, price checking, or fact-gathering. Adds ~$2 per search call if using API. ### Code Interpreter Execute Python code, process data files, generate visualizations, and manipulate images. Included in token cost (no per-call charge). Can download generated files. ### File Analysis Users can upload files (PDFs, images, audio, documents). The Custom GPT can extract text, answer questions about the file, or process it with code interpreter. ### Custom Actions (API Integration) Define custom API endpoints the Custom GPT can call. Examples: - POST to your Slack workspace to send notifications - GET from your company database to fetch customer info - POST to your project management tool to create tasks Requires OAuth or API key authentication (stored securely by OpenAI). ### Knowledge Base Upload PDFs, CSVs, HTML, images, or text files. The Custom GPT will reference them when answering questions. Useful for company handbooks, policies, FAQs, or product documentation. ### Conversation Starters Define prompts that users see when they open the Custom GPT. Examples: "Summarize this CSV," "Review my code," "Answer a customer question." Helps first-time users understand what the Custom GPT can do. ## Custom GPT Limitations ### No Long-Term Memory Each conversation with a Custom GPT is independent. The agent doesn't remember previous conversations or user preferences. If you need persistent state, you must integrate with an external database via Custom Actions. ### No Scheduled Tasks Custom GPTs can't run autonomously or on a schedule. They only respond when a user sends a message. For background jobs (daily reports, periodic checks), you need OpenClaw or Hermes. ### Knowledge File Limits Max 20 files per Custom GPT, ~20MB each. Very large datasets (100GB+) aren't practical. For large knowledge bases, consider external retrieval APIs. ### No Custom Models Locked to OpenAI's GPT models (GPT-5.4, GPT-4o). Can't use Claude, Gemini, or open-source models. For model flexibility, use OpenClaw. ### Limited Debugging When a Custom Action fails, error messages to the user are limited. Hard to debug API issues if users don't share the exact error. ### No Persistent State Between Sessions If a Custom GPT call to a Custom Action fails, there's no built-in retry logic. The user sees the error and must retry manually. ## Building a Custom GPT vs Using Shared Ones ### Building Your Own **Advantages:** - Full control over instructions, tools, and knowledge - Can customize behavior for your specific use case - Own usage analytics and improvement data - Can restrict sharing to your team or business workspace **Disadvantages:** - Time investment in prompt engineering and testing - Responsibility for keeping instructions and knowledge updated - If you build in public (GPT Store), you become responsible for user support ### Using Shared Custom GPTs (from GPT Store) **Advantages:** - Instant access — no setup or configuration - Someone else maintains and improves the Custom GPT - No development time **Disadvantages:** - Limited customization — you're stuck with what the creator built - Creator can change or remove the Custom GPT at any time - Privacy concerns — creator sees usage statistics and can read conversation context via Custom Actions - No control over future changes to instructions or tools **When to build:** Use case is specific to your domain or team, you need persistent integration with your tools, or you want full control. **When to use shared:** Quick one-off tasks, general-purpose use (writing, coding, analysis), or you don't have time to build. ## Privacy & Data Handling ### Who Sees Your Conversations? - **If the Custom GPT is yours:** You own the conversations. OpenAI may see them for abuse monitoring, but they're not shared with the Custom GPT creator. - **If you're using someone else's Custom GPT:** The creator can see analytics (number of conversations, general topics) but not the content of conversations unless they explicitly log them via Custom Actions. ### Custom Actions & Privacy When you use a Custom GPT with Custom Actions (calls to external APIs), the creator can: - See that the Custom Action was called (in their system logs) - See what data was passed to the API (if they log the request) - Store conversation context on their servers if the Custom Action saves it **Best practice:** Never use a Custom GPT with Custom Actions if you're passing sensitive data (passwords, API keys, personal information) unless you completely trust the creator. ### Knowledge Files & Privacy When you upload a knowledge file to your Custom GPT, it's stored by OpenAI. Be careful with sensitive documents: - Don't upload confidential trade secrets unless the Custom GPT is private - Don't upload PII (social security numbers, email lists, credit card info) - If the Custom GPT is public (GPT Store), assume the knowledge files could be extracted by users (they can ask the agent to repeat verbatim chunks) ### Business Tier Privacy Benefits If you use ChatGPT Business, Custom GPTs are workspace-scoped: - Only your team members can access them - Conversations are isolated within the workspace - Data residency option (EU/US) on Enterprise ## Monetization Options ### GPT Builder Revenue Sharing (2026) OpenAI allows Custom GPT creators to earn revenue if their Custom GPT is used extensively via the API or GPT Store. Revenue sharing is calculated per-tool-call and token usage. **How it works:** - Creators of popular Custom GPTs get a share of API revenue generated by users calling them - Revenue is split: OpenAI keeps ~70%, creator gets ~30% (exact rates not publicly disclosed) - Payments only kick in above a minimum threshold ($50–100/month) **Realistic revenue expectations:** - A Custom GPT with 100 daily users making 1–2 calls each: ~$20–50/month - A Custom GPT with 1,000 daily users: ~$200–500/month - A Custom GPT with 10,000+ daily users: $2K–10K+/month (rare, requires viral adoption) **Best practices for monetization:** - **Focus on utility, not revenue.** Most successful Custom GPTs were built to solve a real problem, not to make money. Revenue follows if they're useful. - **Make it solve a niche problem well.** A Custom GPT that does one thing exceptionally beats a generalist Custom GPT. - **Promote via channels.** Build audience on Twitter, Product Hunt, or niche communities. Custom GPTs don't promote themselves. - **Offer a free tier and premium.** Use Custom Actions to gate premium features (e.g., "Basic analysis is free, advanced reports require my backend API"). ## Common Use Cases ### Customer Support Automation **Setup:** System prompt defines support policies, knowledge base contains FAQ + policies, Custom Action calls your ticketing system to create tickets. **Benefit:** Answer 80% of support questions instantly; escalate complex ones to humans. ### Content Creation Assistant **Setup:** System prompt with your brand voice and style guide, web search enabled to find current facts. **Benefit:** Consistent tone across marketing copy, social media posts, blog articles. ### Code Review Bot **Setup:** System prompt with coding standards, code interpreter enabled, Custom Action to create GitHub issues. **Benefit:** Immediate feedback on PRs; catch common mistakes before human review. ### Data Analysis Tool **Setup:** Code interpreter enabled, file upload for CSVs/JSONs, system prompt asks for context before analysis. **Benefit:** Non-technical users can analyze data without SQL or Python. ### Personal Research Assistant **Setup:** Web search enabled, knowledge base with your reading list or saved articles, code interpreter for data extraction. **Benefit:** Synthesize information across sources; find connections you'd miss manually. ### API Documentation Explorer **Setup:** Knowledge base with API docs, system prompt trained to answer integration questions. **Benefit:** Developers get instant answers instead of digging through docs. ## Custom GPT vs Custom Bots on Other Platforms | Platform | Setup Time | Customization | Privacy | Cost | | --- | --- | --- | --- | --- | | **ChatGPT Custom GPTs** | 15 min | System prompt + tools, no coding | Creator can see metadata | Included in Plus ($20/mo) | | **OpenClaw Skills** | 1–2 hours | Full code control, any model | Your own servers | $5–30/mo VPS | | **Discord/Slack bots** | 2–8 hours | Full code, integrates with chat | Your choice | $10–50/mo hosting | | **Make/Zapier automations** | 30 min | No-code workflows | Hosted by service | $10–500/mo (usage-based) | ## Frequently Asked Questions Can I export a Custom GPT to use elsewhere? Not directly. You can export the system instructions and knowledge files manually, but the Custom GPT itself is locked to ChatGPT. To migrate to OpenClaw, copy the instructions into a SOUL.md file and recreate the setup there. What if someone copies my Custom GPT? On the web, anyone can see the system prompt and knowledge files of public Custom GPTs by asking the agent to reveal them. There's no built-in protection. If your Custom GPT contains unique intellectual property, keep it private or restrict to Business workspace. For true protection, build on OpenClaw where code is yours. Can I update a Custom GPT and will users see the changes? Yes. When you edit the system prompt or tools, changes apply immediately for all users. No versioning or rollback — be careful with updates. What's the difference between a Custom GPT and a ChatGPT conversation with a system prompt? A conversation is ephemeral and personal. A Custom GPT is shareable, persistent, has analytics, and can integrate with external tools. Use conversations for one-off tasks; use Custom GPTs for things you or others will reuse. Can I monetize a Custom GPT I didn't create? No. You can't modify or redistribute someone else's Custom GPT for profit. You can build your own and potentially earn revenue through the revenue-sharing program. See also: [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · [Custom GPT Setup Guide](https://openclawdatabase.com/chatgpt/setup/) · [Pricing & Per-Tool Billing](https://openclawdatabase.com/chatgpt/pricing/) · [OpenClaw skills alternative](https://openclawdatabase.com/openclaw/) ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ================================================================ # ChatGPT FAQ — Community Questions Answered (2026) URL: https://openclawdatabase.com/chatgpt/faq/ Last updated: 2026-05-31 ================================================================ # ChatGPT FAQ — Community Questions Answered The top ChatGPT questions from [r/ChatGPT](https://www.reddit.com/r/ChatGPT/) this week, answered with community insight and specific steps you can act on today. Updated weekly. ## Top Questions This Week Why does ChatGPT overuse the "It's not just X — it's Y" writing pattern? This rhetorical structure ("It's not just a tool. It's a partner.") comes from ChatGPT's training data, which included large amounts of persuasive marketing copy, and from RLHF feedback that rewarded confident, punchy writing. There's no official name for it, though r/ChatGPT users have dubbed it "AI em-dash syndrome." To suppress it, add this to your custom instructions: *"Avoid the 'It's not just X — it's Y' sentence pattern. Write plainly and directly."* [Read the full guide →](https://openclawdatabase.com/chatgpt/faq/chatgpt-writing-patterns/) Source: [r/ChatGPT](https://www.reddit.com/r/ChatGPT/comments/1sfrj68/) How do I make my website visible when ChatGPT recommends tools? ChatGPT's tool recommendations surface sites with clear structured data markup (Schema.org JSON-LD), machine-readable content, and explicit product descriptions. Add `SoftwareApplication` or `FAQPage` schema to your key pages, use descriptive titles that answer common questions directly, and ensure your content is accessible to AI crawlers. Sites without structured data are largely invisible to the AI agents that aggregate tool and service recommendations. Source: [Hacker News](https://news.ycombinator.com/item?id=48349193) ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ← Back to [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · See also: [Setup Guide](https://openclawdatabase.com/chatgpt/setup/) · [Custom GPTs](https://openclawdatabase.com/chatgpt/custom-gpts/) · [Tips & Tricks](https://openclawdatabase.com/chatgpt/tips/) ================================================================ # How to Stop ChatGPT Using Repetitive Writing Patterns (2026) URL: https://openclawdatabase.com/chatgpt/faq/chatgpt-writing-patterns/ Last updated: 2026-04-15 ================================================================ # How to Stop ChatGPT Using Repetitive Writing Patterns ChatGPT has a tendency to lean on a handful of rhetorical clichés — the most notorious being "It's not just X. It's Y." This guide explains why the pattern appears and gives you copy-paste instructions to suppress it permanently. ## Why Does ChatGPT Do This? ChatGPT's training data contained enormous volumes of marketing copy, persuasive essays, and brand messaging — all genres where punchy, contrast-driven sentences are rewarded. The RLHF process (where human raters scored outputs) further reinforced this style, because confident and structured writing scored better than plain prose. The result: ChatGPT defaults to rhetorical flourishes even when you want something plain and direct. The pattern has no official name, but the r/ChatGPT community (1,645 upvotes on the original thread) has dubbed it **"AI em-dash syndrome"** or simply **"the ChatGPT sentence."** ## The Most Common Patterns to Watch For - **"It's not just X — it's Y."** The original offender. Shows up in almost every persuasive or summary response. - **Em-dash mid-sentence pivots.** "You need speed — but you also need reliability." Endless variations of this structure. - **Triple-bullet openings.** Responses that start with three bullet points regardless of whether a list is appropriate. - **Conclusion summaries.** "In summary, …" followed by a restatement of everything already said. - **Hollow affirmations.** "Great question!" or "Absolutely!" at the start of a reply — especially in older model versions. ## How to Fix It: Custom Instructions Go to **Settings → Personalization → Custom Instructions** (or the system prompt in your API/operator setup) and paste the following: ### Short version (recommended for most users) ``` Write plainly and directly. Avoid the "It's not just X — it's Y" sentence pattern. Do not open responses with affirmations like "Great question!" or "Absolutely!". Skip summary conclusions unless I ask for one. ``` ### Full version (for writing-heavy workflows) ``` Writing style rules — follow these in every response: - No "It's not just X — it's Y" constructions. - No em-dash pivots used as a rhetorical device. - No opening with bullet lists unless the request is explicitly a list. - No filler affirmations (Great question, Absolutely, Certainly, Of course). - No summary paragraph at the end unless I ask for a summary. - Prefer active voice. Prefer specific nouns over abstract ones. - If you are uncertain, say so plainly instead of hedging with "It's worth noting that…" ``` ## What If the Pattern Keeps Appearing? If ChatGPT reverts to old habits mid-conversation, you can nudge it in-chat: *"Reminder: plain writing, no rhetorical contrasts."* For consistent Custom GPT deployments, embed the style rules directly in the GPT's system prompt — not just in Custom Instructions — since system-prompt rules have stronger precedence. Also note that the pattern is more pronounced in shorter, summary-style prompts. If you give ChatGPT more context and a specific tone target ("write like an engineer's internal Slack message"), it calibrates away from marketing-speak more reliably. ## Does This Affect Quality? No — suppressing these patterns does not reduce response accuracy. You are only changing surface style, not the underlying reasoning. Most users report that plain-writing instructions produce *clearer* outputs because ChatGPT is forced to be specific rather than rhetorical. ← [Back to ChatGPT FAQ](https://openclawdatabase.com/chatgpt/faq/) · See also: [Custom GPTs guide](https://openclawdatabase.com/chatgpt/custom-gpts/) · [ChatGPT Tips](https://openclawdatabase.com/chatgpt/tips/) ================================================================ # ChatGPT Memory — How It Works & How to Manage It (2026) URL: https://openclawdatabase.com/chatgpt/memory/ Last updated: 2026-05-10 ================================================================ # ChatGPT Memory — How It Works & How to Manage It ChatGPT's Memory feature lets it remember facts about you and your preferences across separate conversations — your job, projects, writing style, dietary restrictions, the names of your kids. It works invisibly: ChatGPT decides what to remember during normal conversation, and surfaces those memories in future chats when relevant. This guide covers what it actually stores, how to control it, and the privacy and behavior gotchas most users miss. The 30-second answer Memory = ChatGPT writes short notes about you into a per-account store. Those notes are loaded into every conversation's context. You can view, edit, and delete any entry. Available on Plus, Pro, Business, Enterprise. Free tier has a limited version. Memory is account-scoped — Custom GPTs you build do *not* get your personal memories. ## What Memory stores When you mention something durable about yourself in conversation, ChatGPT writes a short fact to its memory store. Examples of what typically gets stored: - **Personal facts:** "User lives in Boston." "User has two children, Mia and Leo." "User is allergic to shellfish." - **Work context:** "User is a product manager at a mid-stage SaaS company." "User's main project is a Python data pipeline." - **Preferences:** "User prefers concise responses." "User likes code examples in TypeScript, not JavaScript." "User does not like emojis in replies." - **Ongoing projects:** "User is writing a novel set in 1920s Cairo." "User is renovating a kitchen and currently choosing tiles." - **Explicit "remember" requests:** "Remember that my project deadline is October 15." ChatGPT adds it verbatim or paraphrased. What Memory *does not* store: full conversation history (that's separate, in your chat list), file uploads, images, or anything from incognito (temporary) chats. ## How to view, edit, and delete memories 1. Open **Settings** (click your name → Settings). 2. Click **Personalization** in the left sidebar. 3. Click **Memory**. 4. You'll see two lists: **Saved memories** (what ChatGPT has stored) and a toggle to disable Memory entirely. 5. To delete a single memory: hover the entry, click the trash icon. 6. To delete all memories: click **Clear all** at the bottom. 7. To turn Memory off entirely: toggle the master switch off. Existing memories are kept (in case you re-enable) but not used in conversations. After deleting a memory, it's gone immediately from new conversations. Old conversations that referenced that memory remain — you'd need to delete those chats separately. ## How Memory shows up in conversations When you start a new chat with Memory enabled, ChatGPT silently reads your memory store and uses anything relevant. You don't see the memories injected, but they shape the response. To check what Memory is actually using: - Look for the **"Memory updated"** indicator that flashes near a response. Click it to see what was just added. - Ask directly: *"What do you remember about me?"* ChatGPT will summarize. **Caveat:** the summary may be incomplete or paraphrased — verify against the Settings page if precision matters. - Use a Temporary Chat to test "no-memory" behavior. Anything you tell ChatGPT in a Temporary Chat is not stored, and existing memories are not loaded. ## Tier access | Tier | Memory | Notes | | --- | --- | --- | | Free | Limited | Smaller memory store, slower update cadence | | Plus ($23/mo) | Full | Standard memory feature | | Pro (~$200/mo) | Full + Projects scoping | Memories can be scoped to a Project | | Business | Full, admin-controllable | Workspace admins can disable Memory org-wide | | Enterprise | Full, audit-logged | Memory writes and reads can be audit-logged for compliance | ## Privacy considerations - **Memories live on OpenAI's servers.** They're tied to your OpenAI account and subject to OpenAI's privacy policy and data-handling practices. - **Free and Plus memories may be used for model training** unless you turn off "Improve the model for everyone" in Settings → Data controls. Business and Enterprise have stricter defaults. - **Memories are not encrypted at rest with your key** — they're encrypted with OpenAI's infrastructure keys, like other account data. Don't put genuinely sensitive secrets (passwords, SSNs, medical PHI) in Memory. - **Workspace admins on Business/Enterprise can disable Memory** org-wide if compliance requires it. - **Custom GPTs you build do not have access to your personal memories** — Memory is account-scoped, not GPT-scoped. A Custom GPT can have its own "knowledge files" but those are configured separately. ## Common gotchas - **"It forgot something I told it."** Memory is selective — ChatGPT doesn't store everything. If something is important, say "Please remember this:" explicitly. Then verify in Settings. - **"It remembers something I never told it."** Memory inference happens during conversations. A throwaway phrase can become a memory. Audit the list periodically. - **"My responses got weird after I worked on a sensitive topic once."** If a one-time topic shaped a memory ("User is exploring divorce options"), it persists into unrelated future chats. Delete the stale memory. - **"Memory is supposed to be off but ChatGPT still 'knows' things."** Disabling Memory only stops it from *using* memories — your old memories are kept. Click *Clear all* if you want a fresh start. - **Memory across devices:** works automatically — memories are account-scoped, not device-scoped. Login on a new device, your memories follow. - **Memory in mobile vs desktop:** identical — same store, same behavior. ## Memory vs other "persistent agent context" features | Platform | Equivalent feature | How it differs from ChatGPT Memory | | --- | --- | --- | | [Claude Cowork](https://openclawdatabase.com/claude-cowork/) | Projects + System Prompts | Project-scoped, not account-wide. Explicit (you author the prompt), not inferred. | | [OpenClaw](https://openclawdatabase.com/openclaw/) | [SOUL.md](https://openclawdatabase.com/openclaw/soul-md/) | Single file you edit directly. Full transparency. Versioned in git. | | [Hermes](https://openclawdatabase.com/hermes/) | Three-tier persistent memory | Database-backed (SQLite/PostgreSQL). Far more powerful but also far more involved. See the [Hermes memory guide](https://openclawdatabase.com/hermes/memory/). | | [Kilo Code](https://openclawdatabase.com/kilocode/) | Session-scoped only | No persistent cross-session memory — each session starts fresh. | ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ← Back to [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · Previous: [Agent Mode](https://openclawdatabase.com/chatgpt/agent-mode/) · Next: [Teams & Business →](https://openclawdatabase.com/chatgpt/teams/) ================================================================ # ChatGPT Pricing 2026 — All 6 Tiers & Per-Tool Billing Explained URL: https://openclawdatabase.com/chatgpt/pricing/ Last updated: 2026-04-12 ================================================================ # ChatGPT Pricing & Per-Tool Billing Explained Complete breakdown of ChatGPT's 6 pricing tiers (Free, Go, Plus, Pro, Business, Enterprise) and how per-tool-call billing works on the API. Includes cost comparison with OpenClaw and Claude Cowork, and worked examples so you can estimate your monthly spend. ## ChatGPT Tiers at a Glance | Tier | Cost | Primary Model(s) | Key Features | Best For | | --- | --- | --- | --- | --- | | **Free** | $0/mo | GPT-4o mini, GPT-3.5 | Basic chat, limited tool access, no Custom GPTs | Casual users, prototyping | | **Go** | $8/mo | GPT-4o mini, GPT-4o | Web search, basic code interpreter, up to 100 GPT Chats/day | Light API use, students, hobbyists | | **Plus** | $20/mo | GPT-5.4, GPT-4o | Custom GPTs, web + code interpreter, file analysis, 300+ GPT Chats/day, 100 messages/3h | Professional users, teams building custom agents | | **Pro** | $200/mo | GPT-5.4, GPT-4o | Priority compute, advanced features, higher token limits (160K), access to o1-preview reasoning | Power users, research, complex reasoning tasks | | **Business** | $25/user/mo (min 5 users) | GPT-5.4, GPT-4o | Workspace management, team Custom GPTs, 50 GB file storage per member, audit logs, SSO (SAML/OIDC) | Small to medium teams | | **Enterprise** | Custom pricing | GPT-5.4, custom models | Data residency (US/EU), advanced security, dedicated support, SCIM provisioning, SLA | Large organizations, regulated industries | ## Free Tier ($0/mo) - **Models:** GPT-4o mini (slower), GPT-3.5 (older, limited reasoning) - **Tools:** Limited web search, no code interpreter, no Custom GPTs - **Limits:** Conversations are capped, account flagged if unusual activity detected - **Use case:** Casual chat, learning ChatGPT basics, light prototyping ## Go Tier ($8/mo) - **Models:** GPT-4o mini (default), can access GPT-4o with upgrade - **Tools:** Web search, code interpreter, file analysis - **Custom GPTs:** Can use shared Custom GPTs, but cannot create your own - **Limits:** Up to 100 GPT Chats per day, standard response time - **Use case:** Students, hobbyists, light automation with APIs ## Plus Tier ($20/mo) — Most Popular - **Models:** GPT-5.4 full access, GPT-4o, older models - **Tools:** Web search, code interpreter, file analysis (PDFs, images, audio), custom API calls - **Custom GPTs:** Full creation, publishing, and sharing — can build Custom GPTs for your team - **Limits:** 300+ GPT Chats per day, 100 messages per 3 hours, 25MB file upload limit - **Priority:** Standard (not priority, but no artificial slowdowns) - **Use case:** Professional users building personal automation, small teams, freelancers - **Web UI access:** Included — no additional API charges **Note:** Plus is the sweet spot for most users. You get full feature access without paying for Pro's priority compute. ## Pro Tier ($200/mo) - **Models:** All models including o1-preview (advanced reasoning) - **Tools:** Everything in Plus + extended context window (160K tokens vs 100K in Plus) - **Priority compute:** Faster response times, priority in compute queues during peak hours - **Use case:** Research, scientific work, multi-document analysis, complex reasoning tasks Pro is only worth it if you regularly hit Plus's limits or need advanced reasoning models. Most teams save money staying on Plus. ## Business Tier ($25/user/mo, min 5 users) - **Cost:** $25 per team member per month (minimum 5 members = $125/mo total) - **Models & features:** Everything in Pro tier (GPT-5.4, o1, priority compute) - **Workspace:** Shared workspace with role-based access (Owner, Admin, Member, Viewer) - **Team Custom GPTs:** Create Custom GPTs shared with the whole team, not just yourself - **Storage:** 50 GB per team member (Cloud file sharing) - **Admin controls:** SSO (SAML/OIDC), SCIM provisioning, audit logs, usage analytics - **Use case:** Small to medium teams (5–50 people) deploying ChatGPT for workflows ## Enterprise Tier (Custom pricing) - **Cost:** Custom contract (typically $1K–5K+/month depending on scale and features) - **Everything in Business +:** - **Data residency:** Choose US or EU data center (GDPR compliance) - **Advanced security:** Custom encryption, single sign-on, domain verification - **SCIM provisioning:** Automated user management via identity providers - **SLA & support:** Dedicated account manager, priority support, uptime SLA - **Use case:** Large enterprises, regulated industries, custom integrations ## Understanding Per-Tool-Call Billing (API) When you use ChatGPT via the API (not the web UI), OpenAI charges you separately for: 1. **Per-token cost:** Input tokens (what you send) and output tokens (what ChatGPT generates) 2. **Per-tool-call cost:** Each time the model calls a tool (web search, code execution, file analysis, custom API) **Example scenario:** You're building a customer support chatbot that uses web search to answer questions. - Customer asks: "What are the current stock prices for Tesla?" (50 input tokens) - ChatGPT decides to call web search (1 tool call) - ChatGPT reads search results and generates response (200 output tokens) - Your cost: (50 + 200) tokens × token_price + 1 web_search_call × web_search_price **Current API pricing (as of April 2026):** - **GPT-5.4:** $6 per 1M input tokens, $24 per 1M output tokens - **GPT-4o:** $2.50 per 1M input tokens, $10 per 1M output tokens - **Web search:** $2 per call (approximate) - **Code interpreter:** Included in token cost - **File analysis:** Included in token cost **Important:** Always check [openai.com/pricing](https://openai.com/pricing) for current rates — pricing changes quarterly. ## Per-Tool-Call Billing Examples ### Example 1: Email Summarization Bot (5 web searches per day) - Daily user queries: 5 - Each query triggers 1 web search to find context - Per-query token cost: ~300 tokens (input + output) × $2.50/1M = $0.00075 - Per-query web search cost: 1 × $2 = $2.00 - Total per query: ~$2.00 (dominated by web search) - **Monthly cost:** 5 queries × 30 days × $2.00 = $300 ### Example 2: Code Review Bot (runs code interpreter on PRs) - Daily PRs reviewed: 10 - Code interpreter (parsing, analysis): Included in token cost - Per-PR token cost: ~2000 tokens × $2.50/1M = $0.005 - No per-tool-call charge (code interpreter is free) - **Monthly cost:** 10 × 30 × $0.005 = $1.50 ### Example 3: Custom API Integration (calls your backend) - Daily API calls: 20 - Per-call token cost: ~500 tokens × $2.50/1M = $0.00125 - Per-call custom API charge: $0.01 (you define the pricing in your Custom Action) - **Monthly cost:** 20 × 30 × ($0.00125 + $0.01) = $6.75 ## Cost Comparison: ChatGPT vs OpenClaw vs Claude Cowork | Use Case | ChatGPT Plus (web UI) | ChatGPT API | OpenClaw | Claude Cowork | | --- | --- | --- | --- | --- | | **Light user (5 interactions/day)** | $20/mo all-in | ~$15–30/mo (5 queries × 30 days) | ~$20/mo (VPS $12 + API $8) | Free tier (limited) | | **Typical team (50 users, internal automation)** | $1000/mo (50 × $20) | $500–2000/mo (pay-per-token) | $25–50/mo (shared VPS + cheap model) | $1000/mo (50 × $20) | | **Heavy API user (10k interactions/day with web search)** | Not available (web UI only) | $60,000+/mo (10k × $2 web search + tokens) | $500–1000/mo (fixed VPS + model costs) | Not practical (pricing not tiered for API use) | | **Enterprise team (500 people, data residency required)** | Not available | $50k+/mo (custom contract) | $100–300/mo (private infrastructure) | $15k+/mo (Enterprise tier, custom) | **Key takeaways:** - **ChatGPT Plus ($20/mo):** Best for individual professionals who want simplicity and full feature access without per-token costs. - **ChatGPT API:** Expensive at scale if using tools like web search. Best for low-volume integration use cases or enterprise customers who want hosted OpenAI infrastructure. - **OpenClaw:** Dramatically cheaper at any scale due to model flexibility and self-hosting. Best for teams needing cost control or privacy. - **Claude Cowork:** Comparable to ChatGPT Plus for teams, but locked to Anthropic models. Best if you're already using Claude and want team collaboration. ## How to Minimize ChatGPT Costs - **Use Plus tier for web UI work.** The $20/mo is all-in — no per-token surprises. - **Avoid web search in production bots if possible.** Each search costs ~$2. Cache results or use search results from your own systems. - **Use GPT-4o instead of GPT-5.4 for APIs.** 4o is 3x cheaper and still strong for most tasks. - **Use Claude Haiku via OpenClaw instead of ChatGPT API for high volume.** Haiku is 20x cheaper and often sufficient for simple tasks. - **Batch requests.** Process multiple queries together to reduce per-interaction overhead. - **Set context window budgets.** Limit how much conversation history the model can see to reduce input token costs. ## Frequently Asked Questions What's the cheapest way to use ChatGPT? Free tier ($0) if you're okay with GPT-4o mini and no custom tools. Go tier ($8/mo) if you want web search. Plus ($20/mo) if you want to build Custom GPTs or use GPT-5.4. For API usage, consider OpenClaw instead — it's cheaper at any meaningful scale. Does ChatGPT Plus include API access? No. ChatGPT Plus is the web UI only ($20/mo all-in). API access is separate and billed per-token + per-tool-call. If you want API access, you need a separate ChatGPT API account. Can I use one ChatGPT Plus account for a team? You can share a single Plus account among multiple people, but account sharing violates ChatGPT's terms. For teams, use the Business tier ($25/user/mo minimum 5) which gives proper workspace management, audit logs, and shared Custom GPTs. What if I exceed my usage limits? On Plus, you'll be rate-limited (can't send more messages until the window resets). On API, billing continues indefinitely — set a spending limit on your OpenAI account to prevent surprise bills. Business and Enterprise have dedicated support for usage scaling. Is there a monthly spending cap? Yes. On your OpenAI account, go to Billing → Usage Limits and set a hard cap. Once you hit it, API calls will fail until the next billing period. This prevents runaway bills from buggy integrations. See also: [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · [Custom GPT Setup Guide](https://openclawdatabase.com/chatgpt/setup/) · [ChatGPT vs OpenClaw](https://openclawdatabase.com/chatgpt/vs-openclaw/) · [OpenClaw cost breakdown](https://openclawdatabase.com/openclaw/setup/) ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ================================================================ # Custom GPT Setup Guide 2026 — Create, Configure, Publish URL: https://openclawdatabase.com/chatgpt/setup/ Last updated: 2026-04-12 ================================================================ # Custom GPT Setup Guide — Create, Configure, Publish Everything you need to build and publish a Custom GPT: system instructions, attaching tools (web search, code interpreter, file analysis), configuring knowledge, and setting sharing controls. No coding required — takes about 15 minutes start to finish. ## Prerequisites - **ChatGPT Plus subscription or higher** — Free users cannot create Custom GPTs. Upgrade at [chatgpt.com](https://chatgpt.com) - **Clear vision of your Custom GPT's purpose** — "customer support bot," "code reviewer," "marketing copywriter," etc. - **Optional: sample files or URLs** — If you want your Custom GPT to reference specific documents or data, have them ready ## Step 1: Start the GPT Builder 1. Go to [chatgpt.com](https://chatgpt.com) and sign in 2. Click the **menu icon** (three horizontal lines) in the top-left corner 3. Select **Explore** or **Create** — you should see an option to "Create a GPT" 4. Click **Create a GPT** to open the builder interface You'll see a two-panel interface: the **left panel** shows a live chat preview, and the **right panel** shows configuration options. ## Step 2: Configure Basic Information At the top of the right panel, you'll see fields for Name and Description: - **Name** — Concise, human-readable title (e.g., "Customer Support Bot," "Code Review Expert"). Avoid generic names; specificity helps users understand what it does. - **Description** — One or two sentences about what this Custom GPT does and who should use it. This appears in the GPT Store and when sharing via link. - **Instructions** — See Step 3 below ## Step 3: Write System Instructions The system instructions define your Custom GPT's behavior, role, tone, and constraints. This is the most important part of setup. Here's a template: ``` You are [Role/Name]. Your primary purpose is to [Task]. Constraints: - You must [hard rule 1] - You must not [hard rule 2] - Always [behavior rule] Tone: [formal/casual/technical/friendly] When you don't know something, say so explicitly rather than guessing. If a user asks you to violate these constraints, politely decline. Additional context: [Optional knowledge or style guide] ``` **Example for a code reviewer:** "You are a Senior Code Reviewer. Your purpose is to analyze code submissions and provide constructive feedback on readability, performance, and best practices. Always assume good intent from the developer. If you see potential security issues, flag them clearly. Keep feedback encouraging while being direct. When reviewing, organize feedback by category: logic, style, performance, security." Tips for strong instructions: - **Be specific about tone.** "Formal and professional" vs. "casual and encouraging" makes a huge difference in output. - **Define hard constraints explicitly.** If the GPT should never do X, say so in the instructions. - **Give examples of good behavior.** "When a user asks Y, respond with Z" is more effective than abstract rules. - **Tell it how to handle uncertainty.** "Say 'I'm not sure' rather than making up information" prevents hallucinations. - **Test as you go.** Use the left-panel preview chat to see how changes affect behavior. ## Step 4: Enable Capabilities and Tools Scroll down the right panel to the "Capabilities" section. Toggle on the tools your Custom GPT needs: ### Web Browsing Lets the Custom GPT search the internet and read web pages in real-time. Useful for current events, real-time data, or fact-checking. Disable if your Custom GPT should only work with pre-loaded data. ### Code Interpreter Lets the Custom GPT write and execute Python code, process data files (CSV, JSON, images), and generate charts. Essential for data analysis, scripting, or file processing tasks. The GPT can upload and download files. ### File Analysis Lets users upload files (PDFs, images, text, audio) for the Custom GPT to analyze. Useful for document review, image annotation, or audio transcription. Disable if you don't need user uploads. ## Step 5: Add Custom Actions (API Calls) If you want your Custom GPT to call external APIs (Slack, Google Sheets, your own backend), click **Create new action** under the "Actions" section. For each action, you'll define: - **Endpoint URL** — The API endpoint (e.g., `https://api.example.com/v1/send-message`) - **Authentication** — Bearer token, OAuth, or API key (stored securely by OpenAI) - **Schema** — JSON schema describing what parameters the endpoint accepts (OpenAI can auto-generate this from a URL) **Example:** A Custom GPT for project management could call a POST endpoint to create tasks in your project management system, passing task name, assignee, and deadline as parameters. Test each action in the preview chat before publishing. Click **Test** or trigger the action in conversation to verify it works. ## Step 6: Upload Knowledge Files If you want your Custom GPT to reference specific documents, PDFs, or datasets, upload them under the **Knowledge** section. - **File size limit:** Typically 20MB per file, 20 files per Custom GPT - **Supported formats:** PDF, TXT, CSV, JSON, HTML, and image files (PNG, JPG, GIF) - **How it works:** OpenAI indexes the files and includes relevant snippets in the Custom GPT's context when users ask questions Knowledge as guardrails Use knowledge files to keep your Custom GPT grounded in your company's policies, data, or style guide. For example, upload your company handbook so the support bot can answer internal questions accurately. ## Step 7: Test in the Preview Chat The left panel shows a live preview of your Custom GPT. As you make changes to instructions or tools, test them immediately: - **Ask typical user questions** — "What do you do?" "Can you help with X?" - **Test edge cases** — Try to get it to violate constraints or make mistakes - **Test tools** — Ask it to use web search, run code, or call your custom API - **Check tone and personality** — Does it feel like what you intended? If behavior isn't what you want, refine the system instructions and test again. Iterate until you're satisfied. ## Step 8: Publish and Configure Sharing When your Custom GPT is ready, click **Publish** (usually a button at the top-right of the builder). You'll be asked to choose a sharing mode: ### Only Me (Private) Only you can use this Custom GPT. It won't appear in search or the GPT Store. Useful for personal automation or testing. You can share via direct link if needed, but only people with the link can access it. ### Link Sharing Anyone with the link can use the Custom GPT, but it won't be listed in the GPT Store. The Custom GPT is not discoverable via search. Best for sharing with a team or specific group. ### Public (GPT Store) The Custom GPT is listed in the public GPT Store and searchable by all ChatGPT users. Use this if you're building something others can benefit from. The Custom GPT will be discoverable and usage stats available in your dashboard. ### Business Workspace Only (Business Tier) If you have a ChatGPT Business subscription, you can restrict a Custom GPT to only people in your workspace. They'll see it in an internal GPT library and can use it on shared Business projects. ## Step 9: Share and Monitor After publishing, you'll get a shareable link. Copy it and share with your team, customers, or the public (depending on your sharing mode). In your Custom GPT's dashboard, you can: - **View analytics** — How many times it's been used, by whom, and for what - **Edit the Custom GPT** — Click to refine instructions, add/remove tools, or change the description - **Delete it** — Remove the Custom GPT (conversations already had with it are archived but no longer accessible through the Custom GPT) ## Best Practices - **Start simple, iterate.** Don't overload the Custom GPT with tools or knowledge on day one. Add them as you find they're needed. - **Version your instructions.** Keep a document of instruction versions and what changed. If a new version performs worse, you can revert. - **Set clear expectations in the description.** Tell users what the Custom GPT is and is not designed to do. "I can help with X, not Y." - **Monitor performance.** Check usage stats and user feedback. If a Custom GPT is barely used, investigate why (unclear description, missing tools, poor instructions). - **Test tool integrations thoroughly.** Custom actions calling external APIs are powerful but error-prone. Test edge cases before going live. - **Keep knowledge files fresh.** If you upload a company handbook, update it when policies change. Stale knowledge is worse than no knowledge. - **Document the Custom GPT for your team.** Leave a note about what it does, who should use it, and how to reach out if something breaks. ## Frequently Asked Questions Can Free-tier ChatGPT users create Custom GPTs? No. Creating and publishing Custom GPTs requires a ChatGPT Plus subscription ($20/mo) or higher (Pro, Business, Enterprise). Free users can use publicly shared Custom GPTs but cannot create their own. Can I back up my Custom GPT? OpenAI doesn't provide a built-in export feature. To back up a Custom GPT: (1) copy the system instructions, (2) document the tools and actions you configured, (3) download knowledge files before publishing. You can recreate it in OpenClaw or another platform using this documentation. What's the difference between a Custom GPT and a Chat conversation with a system prompt? A Custom GPT is a shareable, persistent artifact with its own link, analytics, and configuration UI. A Chat conversation with a system prompt is ephemeral — it exists only for that conversation and isn't reusable. Custom GPTs are designed for sharing and building something others can use repeatedly. Can my Custom GPT call Slack, Google Sheets, or other APIs? Yes, via Custom Actions. Define the API endpoint, authentication method, and schema. The Custom GPT will call the endpoint when appropriate. Test thoroughly before publishing — API errors can confuse users. How much does it cost to use a Custom GPT? If you're a Plus subscriber, using Custom GPTs you created or that others shared is included in your $20/mo subscription. If you access a Custom GPT via API (programmatically), you're billed at standard API rates (per-token + per-tool-call). See the pricing guide for details. See also: [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · [Custom GPTs Deep Dive](https://openclawdatabase.com/chatgpt/custom-gpts/) · [Pricing & Per-Tool Billing](https://openclawdatabase.com/chatgpt/pricing/) ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ================================================================ # ChatGPT for Teams & Business — Full Setup Guide (2026) URL: https://openclawdatabase.com/chatgpt/teams/ Last updated: 2026-05-10 ================================================================ # ChatGPT for Teams & Business — Workspace Setup, Roles & Cost ChatGPT for a single user and ChatGPT for a team are different products. The team versions (Business and Enterprise) add shared Custom GPTs, admin controls, SSO, audit logging, and stronger data-handling guarantees. This guide walks the setup top to bottom and covers the decisions that matter — which tier to pick, how to structure roles, what compliance actually looks like, and how cost scales. Which tier do you actually need? **2–149 seats, standard data-handling:** Business. **150+ seats or compliance (SOC2, HIPAA, custom DPA):** Enterprise. Plus and Pro tiers are individual subscriptions even if multiple coworkers buy them — they don't share Custom GPTs and have no admin controls. ## Tier comparison | Feature | Plus | Pro | Business | Enterprise | | --- | --- | --- | --- | --- | | Shared Custom GPTs | No | No | Yes | Yes | | Workspace admin | No | No | Yes | Yes | | SSO (Okta, Google, Azure AD) | No | No | Yes | Yes | | SCIM provisioning | No | No | No | Yes | | Audit logs | No | No | Basic | Comprehensive | | Data excluded from training | Opt-in | Opt-in | By default | By default | | Custom retention policy | No | No | No | Yes | | Custom DPA / BAA | No | No | No | Yes (incl. HIPAA) | | Dedicated support | No | Email | Email + chat | Named CSM | | Typical price per seat | $23/mo | ~$200/mo | $25–50/mo | Custom | Pricing varies by region, annual commitment, and seat count. Get an actual quote — OpenAI is generous with multi-year discounts at the Enterprise tier. ## Setup walkthrough ### 1. Create the workspace For Business: go to [chatgpt.com/business](https://chatgpt.com/business), click **Get Business**, complete checkout. The account you use becomes the initial Owner. For Enterprise: contact OpenAI sales — Enterprise involves a custom DPA, security questionnaire, and (typically) a 1-month onboarding window. Worth the wait for any regulated industry. ### 2. Invite members 1. Settings → **Members** → **Invite**. 2. Add member emails (one per line). Bulk paste works. 3. Assign role at invite time (default: Member). Skip this if you'll use SSO/SCIM for provisioning. 4. Send. Members get an email with a one-click join link. ### 3. Configure SSO (Business and Enterprise) SSO is strongly recommended — it lets you de-provision a leaving employee in seconds rather than having to remember to remove them manually. 1. Settings → **Workspace** → **SSO**. 2. Pick your provider (Okta, Google Workspace, Microsoft Entra/Azure AD). 3. Follow the SAML/OIDC config — ChatGPT shows you the exact ACS URL and Entity ID to paste into your IdP. 4. Test with one user before enforcing org-wide. 5. (Enterprise only) Set up SCIM for automatic provisioning/deprovisioning. ### 4. Publish a shared Custom GPT 1. Build the Custom GPT as usual (see [Custom GPTs deep dive](https://openclawdatabase.com/chatgpt/custom-gpts/)). 2. In the GPT settings, set **Sharing** to **Anyone in [Workspace name]**. 3. Save. The GPT now appears in every workspace member's sidebar under "Workspace GPTs." 4. (Recommended) Add the GPT to **Featured** via Workspace settings so it shows at the top of everyone's GPT list. ### 5. Configure admin policies - **Data controls:** Settings → Workspace → Data controls. Business and Enterprise are excluded from training by default — verify the toggle is off. - **Memory:** Disable Memory org-wide if compliance prohibits cross-conversation context. Settings → Workspace → Memory. - **External GPT access:** Settings → Workspace → External. Decide whether members can use public Custom GPTs from outside the workspace, or only workspace-published ones. - **Retention:** (Enterprise) Settings → Workspace → Retention. Set how long conversation history is stored. Default is "indefinite"; many compliance regimes require shorter (90 days, 1 year). - **Audit logs:** (Business basic, Enterprise full) Settings → Workspace → Audit logs. Configure SIEM forwarding if you have one. ## Common admin patterns - **One admin per 50 seats.** Below that, one admin is enough. Above, distribute the work so no one becomes a single point of failure. - **"Featured GPTs" should be 3–5, not 30.** Featuring everything is featuring nothing. Pick the workflows every member should use weekly; let the rest live in the regular workspace GPT list. - **Onboarding doc > "go play with it."** A 1-page internal doc that says "here are the 3 GPTs you'll use, here's the prompt pattern that works, here's how to flag a problem" drives 10× the adoption of just rolling it out. - **Off-boarding via SSO, not manual.** The #1 ChatGPT-for-business security failure mode is forgetting to remove someone who left 4 months ago. SSO with auto-deprovisioning eliminates this. - **Audit the public Custom GPT toggle.** If members can use public GPTs, they may be feeding workspace data to third-party developers. Either disable, or have a clear policy. ## Cost worked example — 25-seat team Hypothetical mid-size team on Business at $30/seat/month: - 25 seats × $30 = **$750/mo** base cost - Heavy users may push the tier's per-tool-call quota — budget 10–20% overage on top in months when teams do major research or migration work - Compared to giving everyone a personal Plus subscription: 25 × $23 = $575/mo. Business adds ~$175/mo for the admin controls, SSO, and shared GPTs. Worth it for anything >5 seats. - Compared to Enterprise: typically 30–60% more than Business per seat, but unlocks SCIM, custom retention, and DPA terms that compliance teams will actually approve. See the [cost calculator](https://openclawdatabase.com/tools/cost-calculator/) for an interactive comparison against per-API-token pricing if you're considering building on the OpenAI API instead. ## When Business / Enterprise *isn't* the right choice - **You have <5 seats and no compliance need:** individual Plus subscriptions work fine. Save the admin overhead. - **You need full data residency and zero-egress guarantees:** even Enterprise data lives in OpenAI's cloud. If that's a deal-breaker, look at self-hosted alternatives like [OpenClaw](https://openclawdatabase.com/openclaw/) + Ollama or [NemoClaw](https://openclawdatabase.com/nemoclaw/) on your own GPU. - **You want model flexibility:** ChatGPT is OpenAI-only. Teams using Claude, Gemini, or mix-and-match should consider [Claude Cowork](https://openclawdatabase.com/claude-cowork/) or [Kilo Code](https://openclawdatabase.com/kilocode/). - **You need long-running async agents:** ChatGPT is conversational. For nightly tasks, scheduled workflows, and multi-day projects, see [Hermes](https://openclawdatabase.com/hermes/) or [OpenClaw](https://openclawdatabase.com/openclaw/). ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ← Back to [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · Previous: [Memory](https://openclawdatabase.com/chatgpt/memory/) · Next: [API vs Chat →](https://openclawdatabase.com/chatgpt/api-vs-chat/) ================================================================ # Advanced ChatGPT Tips 2026 — Prompts, Agents, Cost Optimization URL: https://openclawdatabase.com/chatgpt/tips/ Last updated: 2026-04-12 ================================================================ # Advanced ChatGPT Tips — Prompts, Agents & Cost Optimization Tips and tricks for getting the most out of ChatGPT agents: writing system prompts that actually work, using Agent Mode autonomy effectively, integrating tools without breaking things, and keeping costs under control when you scale. ## 1. System Prompt Engineering for Custom GPTs Your system instructions are everything. Here's the anatomy of a great prompt: - **Role** — "You are a senior code reviewer" (specific, not generic) - **Task** — "Your job is to review pull requests and identify bugs, security issues, and style violations" - **Constraints** — "Do not approve code without identifying all issues. Be thorough but respectful in tone." - **Output format** — "Always format feedback as: [Issue Type] | [Severity] | [Code snippet] | [Fix]" - **Context** — Provide examples of good and bad code **Pro tip:** Test your system prompt with 5–10 real requests before publishing to your team. Iterate based on failures. ## 2. Agent Mode: Let It Decide Agent Mode lets ChatGPT autonomously call tools without asking permission at each step. This is powerful but risky. - **When to enable Agent Mode** — Information gathering (web search), analysis tasks, or research where it's safe to explore - **When to disable** — Anything destructive (don't let it execute arbitrary shell commands, delete files, or modify databases) - **Set clear boundaries** — "You can browse the web to find information about X, but you must not access any API keys or passwords." ## 3. Tool Integration Without Chaos - **Start with one tool** — Master web search before adding code interpreter - **Test tool use in preview chat** — Write a sample request and watch how it uses each tool - **Document APIs clearly** — If adding custom API actions, provide exact endpoint descriptions and error handling expectations - **Rate-limit early** — Add timeout constraints: "You may make up to 5 web searches per request" ## 4. Cost Optimization - **Monitor tool calls** — Each tool call is billed separately. Web search, code interpreter, and file analysis all add up - **Use Go tier for light use** — $8/mo is cheaper than Plus ($20/mo) if you only use basic features - **Batch processing** — Give your agent multiple requests at once instead of one-by-one (fewer tool roundtrips) - **Cache instructions** — Reusable system prompts save token costs when you have many similar requests Example: A custom GPT that does 100 web searches/month + 200 code interpretations at average $0.01 per tool call = ~$3/month on API, plus $8 Go subscription = $11/month total. ## 5. Common Pitfalls to Avoid - **Overly generic instructions** — "Be helpful" doesn't work. "Respond in exactly 3 bullet points, using clear language for a C-level audience" does. - **Too many tools at once** — ChatGPT gets confused if it can do everything. Start narrow, add tools gradually - **Forgetting output format** — Without explicit format rules, responses vary wildly. Always specify JSON, markdown, or structured text - **Not testing edge cases** — Before sharing your GPT, test it with weird/malicious inputs to see if it breaks your constraints - **Ignoring token costs in system prompts** — Long instructions (100+ lines) eat tokens. Keep them concise ## 6. Sharing Your Custom GPT - **Link-only** — Safe default; only people with the link can use it - **Public (GPT Store)** — Discoverable to all ChatGPT users; use only if you want wide distribution - **Business workspace** — If using ChatGPT Teams or Business, share within your organization - **Add a description** — "Analyzes code for security flaws. Requires Plus or higher." tells users what to expect ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [⚖️ ChatGPT vs OpenClaw When zero-setup wins, when self-hosting wins, and the migration path either direction.](https://openclawdatabase.com/chatgpt/vs-openclaw/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ← Back to [ChatGPT hub](https://openclawdatabase.com/chatgpt/) · See also: [OpenClaw Skills Guide](https://openclawdatabase.com/openclaw/skills-guide/) for similar patterns ================================================================ # ChatGPT vs OpenClaw 2026 — Which Agent Platform? URL: https://openclawdatabase.com/chatgpt/vs-openclaw/ Last updated: 2026-04-12 ================================================================ # ChatGPT vs OpenClaw — Hosted vs Self-Hosted Agents ChatGPT is OpenAI's fully hosted agent platform. OpenClaw is an open-source self-hosted framework. The choice depends on your priorities: ease-of-use and OpenAI's infrastructure vs control and model flexibility. ## Side-by-Side Comparison | Factor | ChatGPT | OpenClaw | | --- | --- | --- | | **Hosting** | Fully hosted by OpenAI | Self-hosted on your server | | **Setup time** | Minutes | 10–20 minutes | | **Model flexibility** | OpenAI only | Any provider (Anthropic, OpenAI, local Ollama) | | **Cost (light)** | $20/mo (Plus) | ~$5–10/mo (VPS + API) | | **Privacy** | OpenAI infrastructure | Your hardware; full control | | **Skills/Tools** | Web, code, file, APIs | 13,700+ community skills | | **Learning curve** | Very low | Moderate | | **Offline** | No | Yes (with local models) | ## When to Choose ChatGPT - Non-technical users — intuitive web UI - Quick prototyping — minutes to working agent - Light usage — $20/mo covers most - Trust in OpenAI infrastructure ## When to Choose OpenClaw - Model flexibility — use Claude, OpenAI, or local - Cost at scale — better $/token ratio - Privacy-critical — data never leaves your infrastructure - Offline agents — run locally without internet - Custom skills — full control over capabilities ## Migration: ChatGPT → OpenClaw 1. Export your Custom GPT instructions from ChatGPT settings 2. Create a SOUL.md file in OpenClaw with your instructions 3. Recreate your tools in OpenClaw config 4. Test in a channel to verify behavior ## More ChatGPT Guides Continue your ChatGPT journey — every guide on the hub: [⚡ Custom GPT Setup Guide Build your first Custom GPT, configure tools, write the system prompt, share or publish.](https://openclawdatabase.com/chatgpt/setup/) [💰 Pricing & Per-Tool Billing Free vs Plus vs Pro vs Team — what each unlocks, plus the per-tool billing surprises.](https://openclawdatabase.com/chatgpt/pricing/) [🤖 Custom GPTs Deep Dive Knowledge files, actions, code interpreter, and the patterns that distinguish good Custom GPTs from forgettable ones.](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode ChatGPT's autonomous task execution — browses, runs code, chains tools. Capabilities, limits, safety, cost.](https://openclawdatabase.com/chatgpt/agent-mode/) [🧠 Memory — How It Works What Memory stores, how to view/edit/delete entries, privacy implications, and common gotchas.](https://openclawdatabase.com/chatgpt/memory/) [👥 Teams & Business Workspace setup, SSO, shared Custom GPTs, admin controls, and cost per seat for Business and Enterprise.](https://openclawdatabase.com/chatgpt/teams/) [🔌 ChatGPT vs the OpenAI API When ChatGPT wins, when the API wins, and when to use both. Cost math and migration patterns.](https://openclawdatabase.com/chatgpt/api-vs-chat/) [💡 Advanced Tips & Cost Optimization Token-saving prompt patterns, when to use which model, and the hidden settings that matter.](https://openclawdatabase.com/chatgpt/tips/) [❓ ChatGPT FAQ High-value asked-everywhere questions — writing patterns, model differences, and product gotchas.](https://openclawdatabase.com/chatgpt/faq/) [← Back to ChatGPT hub](https://openclawdatabase.com/chatgpt/) ← Back to [ChatGPT hub](https://openclawdatabase.com/chatgpt/)