- « Create a chatbot with ChatGPT » covers four different realities: a Custom GPT tinkered together inside ChatGPT, an application that calls the API, a no-code editor steered by ChatGPT’s advice, or a bespoke project prepared with it. The right path depends on your channel, your data and your time budget.
- In our view, the Custom GPT is the best ally for quick prototyping: you get an assistant that answers on top of your documents, if your workspace and permissions allow it. It does not become a production chatbot though, it has no public channel, no lead capture and no conversation tracking.
- Our stance, stated openly: for a business chatbot, the simplest and most complete solution is Botnation, a no-code platform and a bespoke chatbot creation provider. ChatGPT remains an excellent doorway to explore, design and prototype, but it is one option among others, with real limits detailed in this article and in the comparison table below.
- What makes a chatbot good is not visible in the conversation: it is the design prompt, the upstream flow and the answer scope. The prompt generator in this article gives you the starting point.
- Before publishing: think AI transparency (the EU AI Act, applicable since 2 August 2026, sets in Article 50 obligations with a precise scope: flagging AI in direct interactions where it is not obvious, marking synthetic content and some public-interest texts, each with its own modalities) and personal data.
« Can I create my own chatbot with ChatGPT? » It is one of the most asked questions to OpenAI’s assistant, and the honest answer is: yes, but not the way people assume. ChatGPT does not deploy a chatbot on your site: it is an assistant that helps you design one, an engine you can plug in, or a playground where you build a prototype. Four paths, four levels of outcome.
This article is a hands-on tutorial: it details the four paths, publishes the design prompts that actually work, lists the limits to know before spending one more hour, and ships a generator that creates your starting prompt in six answers. Want the big picture of the three main ways to build a chatbot, code included? Our complete guide to developing a chatbot covers it.
Let us be upfront before diving in: we are the team behind Botnation, and this article is a ramp to our solutions, not a neutral comparison. Yes, ChatGPT can help build a chatbot. For a business chatbot, the simplest and most complete route remains Botnation: we already have everything set up, several different AIs are ready to use on the platform, and if you hand us the build, our team of experts does it. ChatGPT stays very useful upstream, to explore an idea and draft a brief; the comparison table below shows where it stops.
Creating a chatbot with ChatGPT: what we are really talking about
The same word, « create », hides three different moves. That is the first confusion to clear, because it explains why so many tutorials seem to contradict each other: one shows a « Create a GPT » button, another a platform dashboard, a third a code file.
A chatbot is a program that talks to your users, on your channel (website, WhatsApp, Messenger), from rules and data that you control. ChatGPT is a general-purpose assistant: it knows neither your customers, nor your catalogue, nor your channel. Creating a chatbot with ChatGPT therefore means either building an assistant out of ChatGPT (Custom GPT), plugging its engine into your application (API), or using it as an advisor while you build your chatbot elsewhere (no-code or bespoke).
Search engines mostly answer the first form (the Custom GPT), because it is the easiest story to tell. The ground truth is more nuanced: the Custom GPT shines as a prototype and as an internal assistant, but a production chatbot needs a public channel, an up-to-date knowledge base, data capture and a way to measure what happens. We detail the four paths below, with their real cost in time.
The 4 ways to create your chatbot with ChatGPT
Each path answers a different need. The table below is the map we will use throughout the article: compare your situation with the « Who it is for » column before reading the matching section.
| Path | What you get | Who it is for | The limit in one sentence |
|---|---|---|---|
| 1. Custom GPT built in ChatGPT | An assistant to share by link, which answers inside the ChatGPT window | Quick prototyping, testing a need, light internal use | It lives inside ChatGPT (login required to start a conversation), not on your site or WhatsApp |
| 2. ChatGPT API integrated into your application | A chatbot inside your product, driven by your code | Technical teams, existing product | You must build, host, monitor and own the usage billing |
| 3. ChatGPT as project manager, no-code editor to build | A public, multichannel chatbot, built no-code from a brief drafted with ChatGPT | SMEs, shops, organisations that want to publish this week | You own the content, the scope and the compliance |
| 4. ChatGPT to prepare a project handed to experts | A solid specification, a dialogue base tested before negotiation | Complex projects, high volume, regulatory stakes | Bespoke work is quoted on request, with a delivery lead time |
The right reflex to choose
Three questions are enough. Does the chatbot need to be accessible without a ChatGPT account? If yes, path 1 is out. Do you have a technical team available this week? If not, path 2 is out. Is your need standard (FAQ, leads, orders) or business-critical? If standard, path 3 is the fastest; if critical, path 4 deserves a professional estimate. Note that these are not tiers: many projects start on path 1, move to path 3 for production, and keep path 2 for specific features.
ChatGPT or Botnation: the comparison table
Here is our position, line by line. Left column: what ChatGPT (Custom GPT and API) actually delivers for a business chatbot. Right column: what Botnation brings, as a no-code platform and a bespoke chatbot creation provider. Every line of the Botnation column is checked against our public pages.
| Criterion | ChatGPT (Custom GPT / API) | Botnation |
|---|---|---|
| Nature of the solution | A personalised general-purpose assistant that lives inside the ChatGPT ecosystem | Publisher of a no-code chatbot platform AND provider that builds bespoke chatbots for its customers |
| Creating a bot | Closed to personal Free, Go, Plus and Pro accounts: creating and publishing new GPTs depends on the workspace type and permissions (OpenAI help pages) | No-code editor open to everyone, from the free plan, without a line of code |
| Channels | The ChatGPT interface only: no native WhatsApp, Messenger, Instagram or WordPress channel | Website, WhatsApp, Messenger, Instagram, WordPress and more (see our channels) |
| Building the flow | Instructions in natural language, no structured flow builder | Visual editor: flows, conditions, variables, workflows, capture elements and integrations |
| AI and models | You choose and configure everything yourself | Several different AIs already configured and ready to use on the platform (the home model selector offers Gemini and ChatGPT among others) |
| Knowledge base | Documents carried by a GPT, inside ChatGPT’s interface | Your imported content (FAQ, help, procedures, product documentation) wired to the custom AI |
| Integration to your site and tools | No direct integration: you must develop an API or a third-party solution | Widgets, modules (FAQ, leads, e-commerce, customer support), webhooks to CRM, spreadsheets and ERP |
| Analytics and supervision | No analytics dashboard dedicated to your GPTs’ answers | Statistics, transcripts, team and multi-chatbot management |
| Support | No creation service, no dedicated support | Chatbot creation experts available online, dedicated account manager and personalised onboarding in the Enterprise offer |
| Bespoke creation | No | Yes: Enterprise offer with « Chatbot creation services », quoted on request |
| Data | Your exchanges travel through OpenAI’s infrastructure | French publisher, European hosting, consent and deletion tools available in the platform |
| Pricing | ChatGPT account from the free plan; API billed on usage, per token (grid dated 27 August 2026: gpt-5.6-luna at 0.20 dollars per million input tokens, 1.20 dollars output, short context) | FOR FREE 0 euro, BASIC 39 euros, PRO 59 euros per month, ENTREPRISE bespoke, according to the commercial offer verified on 27 August 2026 |
| Quote and demo | No | Free quote via our contact page, demos available on our templates page |
This article’s verdict: for a business chatbot, our recommendation is Botnation. ChatGPT is an excellent doorway to explore, write and prototype, and that is how we use it here: as raw material. But the infrastructure, the channels, the configured AI, the analytics and the support are exactly what our platform and our chatbot creation experts do. And because we already have everything set up, several different AIs are ready to use: if you hand us the build, our team does it, with real knowledge of our own tools.
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Way 1: the Custom GPT, our pick for fast prototyping
A Custom GPT (a « custom GPT ») is an assistant you configure inside ChatGPT: you give it a name, instructions, optionally documents, and you get a specialised version of ChatGPT, shareable by link. Two conditions to know. According to OpenAI’s help pages, creating and publishing new GPTs is not open to personal Free, Go, Plus and Pro accounts: it depends on the workspace type and the permissions granted. And anyone opening your link must be logged in to ChatGPT to start a conversation, even though the public GPT page can remain visible without login. It is the most direct experience of « creating a chatbot with ChatGPT », and it is genuinely useful, provided you know what it does.
Once creation is possible in your workspace, the walkthrough fits in five steps: open ChatGPT, choose « Explore GPTs », then « Create »; describe to the assistant the role of your bot in plain language; refine the instructions to frame the answers; add your documents if the bot must lean on a document base; test, then share the link. The real work is in step 3, and that is exactly what the prompts in the next section automate.
In our view, the Custom GPT is an excellent prototype: it validates the scope, the tone and the relevance of your document base before you invest. But it does not become a production chatbot: your customers cannot reach it without an account, it does not send data to your CRM, it does not measure conversations, and it is not embedded in your website or social networks.
The limits of path 1, for a business chatbot
Here are the concrete downsides of path 1 once the prototype is validated. They are what makes most projects move to a dedicated platform.
- Closed ecosystem: the custom GPT lives inside ChatGPT, with its rules, its usage limits and its interface.
- No native channel: WhatsApp, Messenger, Instagram and WordPress are not part of a GPT’s environment; there is no integration to an external site, you would have to develop it (API or third-party solution).
- Limited knowledge base and contexts: a GPT carries documents and instructions, not a document management platform with versions, permissions and reviews.
- No structured flow builder: no visual journey with conditions, variables and workflows, no capture elements wired to your tools.
- No analytics or team supervision: nothing to measure conversations, failures or volumes per channel.
- No support: no creation service, no dedicated support, no account manager: OpenAI’s offer stops at the tool.
- Your exchanges travel through OpenAI’s infrastructure: a parameter to factor into your risk analysis, especially with customer data.
Already listed your information sources (FAQ, catalogue, procedures)? Our guide on training a chatbot from your own data explains the difference between feeding a model with documents and retraining a model, a point that path 1 makes very visible.
Way 2: the ChatGPT API, the bespoke technical chatbot
The second path consists in calling OpenAI’s API from your own application: a form, a chat widget, a business app. You write the code, the assistant generates the answer, your system does the rest (integrations, authentication, logging). It is the path of technical teams and existing products: the chatbot becomes a component of your software, not a separate page.
Two things change radically compared with path 1. First, the cost: billing is usage-based, per token, with rates that depend on the chosen model, the context length and the tools used. To anchor a figure, OpenAI’s official grid consulted on 27 August 2026 shows, in short context and per million tokens: gpt-5.6-sol at 4 dollars input for 20 dollars output, gpt-5.6-terra at 2 and 12 dollars, gpt-5.6-luna at 0.20 and 1.20 dollars. Long context is billed at higher rates, and tools add on top (web search at 10 dollars per 1,000 calls, for example). This grid changes: the official page is what counts when you quote. Second, the responsibility: you are the one who hosts, measures, protects the personal data in transit and monitors the answers.
This path makes sense when you already have an application and a team. It quickly becomes heavy otherwise: as soon as you need a WhatsApp channel, a landing page, a capture flow and an escalation to a human, the code piles up and the budget explodes. And unlike path 3, nobody supports you: it is a technical project you carry alone, with no creation service and no dedicated support. That is the natural move to path 3.
Way 3: ChatGPT as project manager, a no-code editor to construct
This is the path we recommend to most companies, and it answers the question more completely: you use ChatGPT to design the chatbot (persona, flow, tone, sample answers, edge cases), then you build it in a multichannel no-code editor, which is itself connected to your channels and your data.
Concretely, the split of roles is clear. ChatGPT does the consultant job: it turns your brief into a structured flow, it drafts answer variants, it lists the questions the bot must not answer, it rewrites your FAQ as conversation questions. The no-code editor does the production job: it hosts the conversation, connects it to your website or WhatsApp, applies the flow, captures leads, and gives you an admin interface to fix what is off.
With a no-code editor, your documents become the bot’s foundation thanks to a custom AI: the flow stays hand-written for the paths you control, and the answers lean on your content (FAQ, help, procedures, product documentation), imported into the platform. That is the difference between a bot that « talks » and a bot that « knows ». Our deep dive into generative AI chatbot architectures shows the gap on one and the same question.
At Botnation, this path is the Self-Service Offer: according to the current commercial offer, verified on 27 August 2026 on the pricing page, the no-code platform is available from a FOR FREE 0 euro plan, and an editor lets you manage flows, channels and custom AI without a line of code. And if your project needs more muscle, Botnation also builds bespoke chatbots through its Enterprise offer, handled by its chatbot creation experts, quoted on request: the team that builds is the team that publishes the platform, which avoids the middleman and lets you keep control after handover.
It is also a question of knowing our own tools: on the platform, several different AIs are already configured and ready to use (the home model selector offers Gemini and ChatGPT among others). If you choose the Enterprise offer, our team does the build, with real knowledge of our own tools, rather than a provider discovering the platform. That is a service positioning, not the promise of a measured result: you approve every step.
Pick an LLM after defining the need, not before: our comparison of chatbot types and the platform’s FAQ modules help you choose the architecture that fits your volume and your sector.
The 5 prompts that save hours of design
Here is the practical core of the article: five prompts, copied as-is into ChatGPT, each aimed at a precise design step. They must be sent in order, and you must answer the questions ChatGPT asks you before moving to the next one: that back-and-forth is what makes the result.
You are a chatbot consultant. I will give you my business, my customers and the problem to solve. Ask me at most five questions to complete, then write a ten-line brief: objective, audience, target channel, three expected conversation scenarios, and the criterion that will tell whether the bot is a success. Avoid any unnecessary jargon and do not promise any measured result.
Why it works: it forces clarification before construction. Failing projects are almost always the ones that started with the flow without defining success.
From this brief, write a chatbot flow in eight steps at most. For each step: the question asked, the two or three possible user answers, the reaction to each answer, and the next step. Add a fallback path when the user is not understood, and an escalation to a human. Keep sentences short, like speech.
Why it works: it is exactly the format you will reproduce in a no-code editor. Prompt 2 turns an idea into a decision tree you can copy block by block.
Write ten sample answers for this chatbot, in my tone: warm and professional, no unnecessary anglicism, no emoji unless I ask. For each answer, give a short variant, a detailed variant, and a version for someone coming back after a mistake. Finish by giving me the tone rule in three lines, so I can reuse it with another tool.
Why it works: tone is not fixed afterwards, it is specified upfront. The ten answers then serve as a testing reference.
List the twenty trick questions this chatbot could face: sarcasm, insults, threats, off-topic questions, urgent requests, famous people, legal issues, third-party personal data. For each case, give the answer the bot must give, the one it must never give, and the point where it must hand over to a human.
Why it works: it is the difference between a demo bot and a published bot. Edge cases are where the brand’s reputation is at stake, and you cannot see them in a demo.
Here are extracts from my documents. Turn them into chatbot Q&A: for each customer question, the answer to give, the exact source, and the neighbouring questions pointing to the same answer. Flag missing or contradictory data rather than inventing it. Format the result as a three-column table.
Why it works: it prepares the content the platform will import next, and it quickly surfaces the documentation gaps. Important: always have a human review the answers, it is the only reliable protection against misinterpretation.
These five prompts are the raw material: the brief, the flow, the tone, the edge cases and the knowledge base. They do not replace the infrastructure, the channels, the maintenance or the supervision: that is exactly what our platform and our chatbot creation experts bring, no-code from the free plan and bespoke through the Enterprise offer.
The tool: generate your starting prompt
Six answers are enough to get a complete brief prompt, ready to paste into ChatGPT. The generator below assembles the brief from your choices, then gives you the final prompt: just paste it as Prompt 1 and let ChatGPT ask its questions.
1. Where should your chatbot live?
2. What is its main purpose?
3. What tone for the answers?
4. Which language does it answer in?
5. Which sources should it rely on?
6. What do you want first?
Answer the six questions above: your starting prompt will appear here, ready to copy into ChatGPT.
The prompt to paste into ChatGPT
Prompt copied!
Remember to complete the brief with your business and your customers before sending it: the prompt above is the skeleton, your answers to ChatGPT are the flesh.
The generator gives you the raw material: the brief and the prompt, ready to paste into ChatGPT. The rest is Botnation’s craft: the infrastructure, the channels, the configured AI, the maintenance and the supervision. Our chatbot creation experts are available online, and the quote is free, without commitment.
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The limits of ChatGPT to know before you go
A « create your chatbot with ChatGPT » tutorial without limits would be incomplete. Here are seven, measured in the field, with the workaround for each one. They explain why the technical question is never the first difficulty, and why a dedicated platform with experts answers each one more simply.
| Limit | What happens in the field | The workaround |
|---|---|---|
| Hallucination | The bot invents a price, a date, a procedure, with perfect aplomb | Restrict the scope, ground the answers in your documents, have them reviewed, test thirty real questions |
| No channel | An assistant living inside ChatGPT is invisible to your customers | Choose a platform that publishes on website, WhatsApp, Messenger, Instagram |
| The knowledge base | Heterogeneous, outdated or contradictory documents give inconsistent answers | Audit the documents, add a validity date, plan a quarterly review |
| Personal data | Conversations contain customer data, and the law applies | Limit collection to what is needed, inform the user, check where data is hosted |
| AI transparency | The user must know when they are talking to a machine | Apply the real scope of Article 50 of the EU AI Act (in force since 2 August 2026): direct interactions where the AI is not obvious, synthetic content (including deepfakes) and certain public-interest texts, each with its modalities, deadlines and exceptions |
| Monitoring and fixes | Who looks at the missed conversations? Nothing is measured, nothing is fixed | Ask for statistics and transcripts from day one: it is a selection criterion |
| Support | With ChatGPT, nobody builds, deploys or runs it for you | At Botnation: chatbot creation experts available online, dedicated account manager and personalised onboarding (Enterprise offer), from importing your base to going live |
The biggest risk is not technical: it is the 10 classic mistakes that return in every project, from the wrong scope to unreviewed answers. Our checklist of chatbot creation mistakes walks through them before your first test.
The method in 6 steps, from brief to published chatbot
Here is the full sequence, whichever path you choose. Count half a day for steps 1 to 4 with ChatGPT and a no-code editor; path 1, for its part, requires no development, as long as your workspace allows creating GPTs.
- Define successWrite one sentence: « The bot is successful when it handles X of the Y-type requests without human intervention. » Without that sentence, everything else is decorative.
- Draft the brief with ChatGPTSend Prompt 1, answer the questions, validate the brief. It is your blueprint.
- Produce the flowSend Prompts 2, 3 and 4: decision tree, tone, edge cases. Edit until you can roll it out from memory.
- Prepare the knowledge baseSend Prompt 5 with your documents, then have a human review the Q&A. Import the result into the platform afterwards.
- Build and test for realReproduce the flow in the no-code editor, then test on thirty real conversations, not on the ideal path: that is where the blind spots show up.
- Publish, measure, fixGo live on your channel, label the bot as an AI, then read the untended conversations every week and adjust the flow.
Frequently asked questions
How do I create a chatbot with ChatGPT for free?
The most affordable route depends on your workspace: creating a Custom GPT is not open to OpenAI’s personal Free, Go, Plus and Pro accounts, and a GPT is tested inside ChatGPT’s interface, not on your channel. For a public chatbot, no-code platforms offer a free plan to test building a flow, depending on each provider’s commercial offer, then a paid plan once the bot is actually used.
Is ChatGPT a chatbot?
ChatGPT is a conversational assistant, so in a broad sense a general-purpose chatbot. But it is not your company’s chatbot: it does not know your customers, is not connected to your channels and does not speak for your brand. The common use is to employ it to design your chatbot, or as the engine of it via its API.
What is the difference between a custom GPT and a real chatbot?
The custom GPT lives inside ChatGPT’s interface, shareable by link when public (being logged in to ChatGPT is required to start a conversation, even though the page remains visible), and its usage, knowledge base and visibility remain those of the platform. A real chatbot is deployed on your channel, with your branding, your capture, your statistics and your control over the data. The custom GPT is ideal to validate the need; the production chatbot is built on a dedicated platform.
Do I need to know how to code to create a chatbot with ChatGPT?
No for paths 1 and 3. Creating a custom GPT requires no programming, and a no-code editor lets you assemble flows, integrations and custom AI with a mouse. Path 2 (API) however requires development, at least for the interface and the maintenance.
Can I create a WhatsApp chatbot with ChatGPT?
Not directly: a custom GPT cannot be plugged into WhatsApp. However, you can use ChatGPT to design the WhatsApp chatbot flow, then deploy it on a multichannel platform that handles the channel, the number and the usage rules. That is exactly the recommended order.
Why choose Botnation over ChatGPT for a business chatbot?
Because a production chatbot is not just a prompt: it needs an infrastructure, channels (website, WhatsApp, Messenger, Instagram, WordPress), a configured AI wired to your content, analytics, maintenance and someone who supports you. That is Botnation’s craft, a no-code platform available from a free plan, with chatbot creation experts and a bespoke Enterprise offer. ChatGPT remains a great tool to explore and design: that is our recommended angle, not the complete solution.
Can I see a Botnation demo before committing?
Yes. Botnation’s templates page shows examples of configured chatbots, and our chatbot creation experts are available online on the contact page to walk you through the platform and answer your questions. The quote itself is free and without commitment via our contact page.
How much does a chatbot created with ChatGPT cost?
Creating a Custom GPT is not possible on OpenAI’s personal Free, Go, Plus and Pro accounts; the basic access to ChatGPT, for its part, remains free. The API is billed on usage, per token, according to OpenAI’s dated official grid: for example, gpt-5.6-luna was displayed on 27 August 2026 at 0.20 dollars per million input tokens and 1.20 dollars per million output tokens (short context), and the grid changes. A no-code platform is rented according to the provider’s commercial offer: at Botnation, the offer verified on 27 August 2026 announces a FOR FREE 0 euro plan, plans at 39 and 59 euros per month (indicative prices, excluding tax) and an Enterprise offer quoted on request, plus AI credit packs. For a bespoke project, Botnation’s pricing page states a market order of magnitude of 5,000 to 30,000 euros, and makes clear that each project is quoted on request.
Where to start this week
The keyword of the question is « start », and the shortest route depends on what you want: explore an idea with ChatGPT, or get a business chatbot into production with as little friction as possible. For the first, the five prompts above and the generator do the job. For the second, our recommendation is clear: hand the project to Botnation, no-code from the free plan or bespoke through the Enterprise offer, with experts who know their tools and several AIs ready to use. ChatGPT is a good doorway; Botnation is the complete solution.
Create your chatbot, on your own or with our experts
According to Botnation’s current commercial offer, the no-code platform is available from a free plan, and our chatbot creation experts also build bespoke bots through the Enterprise offer.
