A lot of output doesn’t stall because of missing ideas. It stalls because of small, repeat tasks that keep breaking focus.

Customer questions popping up mid-task.

Documents that need cleaning before they’re usable.

Notes, transcripts, and drafts that take longer than they should to turn into something finished.

This week’s issue is about replacing those friction points with a few simple agents that handle the repeat work quietly in the background.

👇 Let’s get into it.

Tidio is useful when customer questions start interrupting real work.

For most small businesses, support doesn’t arrive in a neat ticketing system. It comes in as website chats, contact forms, follow-up emails, and “quick questions” that turn into long back-and-forths.

That’s where Tidio fits.

At a basic level, it’s a live chat tool for your website. Where it becomes interesting is how easily it handles the first layer of support automatically, without feeling robotic or adding complexity.

Without a system, support usually looks like this:

Tidio replaces that reactive loop with a simple front-line system that handles common questions and routes the rest properly.

The real value comes from treating Tidio as part of a wider workflow.

For example:

Instead of support being something you constantly monitor, it becomes a background system that only surfaces what matters.

Most people use ChatGPT in short bursts. They open a chat, explain what they need, clean up the result, and move on. The next day, they repeat the same process for a very similar task.

That works, but over time it creates a quiet workload of re-explaining, reformatting, and fixing the same things again and again. This post is about replacing that pattern with a few simple systems that handle those tasks consistently.

Just reusable setups that sit alongside your work and take care of common jobs.

Instead of writing one-off prompts, you create small, repeatable instruction sets inside ChatGPT. Each one is designed to handle a specific type of work the same way every time.

For example:

Once a setup is defined, you reuse it whenever that task comes up. You paste in the input and let the system do the rest.

This approach fits well for solo operators and small teams who want fewer decisions during the day, not more tools to manage.

The quality of the setup comes down to one thing: the input you give it.

If you keep the instructions vague, you’ll keep getting generic output. If you give it real context and clear rules, it starts behaving like a reliable system instead of a guessing machine.

A simple method that works well:

The goal is to write the instructions once, then reuse them without thinking.

This is where most people go wrong.

Saying “write like me” doesn’t help much. ChatGPT needs examples it can actually learn from.

If you’re building a writing setup, paste:

Then ask ChatGPT to analyse those examples first and summarise the patterns it sees. After that, it can turn those patterns into a reusable instruction set.

This is faster than tweaking outputs forever.

Before finalising your setup, have ChatGPT interview you.

Use this:

“Ask me 30–50 questions so you can build the best possible version of this setup. Keep them practical, not theoretical.”

Answering those questions once saves you from constantly correcting the output later.

One of the first setups worth building is a brand voice system.

You define how your writing should sound, who it’s for, and what to avoid. You include real examples so ChatGPT can learn from them. From there, you reuse that setup whenever you write.

Prompt:

Once this is set up, it becomes part of how you write, not something you think about each time.

Another common task is cleaning up text so it’s ready to share. Notes, drafts, or guides often need formatting before they’re usable.

A simple document-to-PDF setup handles that in one step.

Prompt:

This replaces a lot of small manual steps and keeps output consistent.

Long documents, articles, or transcripts are another place where time disappears. Reading everything again just to find the important parts is inefficient.

A summariser setup helps here.

Prompt:

This gives you something usable quickly, without losing context.

Meetings generate a lot of text that rarely gets revisited. Cleaning transcripts manually is slow, so it often doesn’t happen.

A transcript cleaner setup fixes that.

Prompt:

This turns raw transcripts into something you can actually reference later.

Each setup replaces one recurring task. None of them are complex on their own, but together they reduce the amount of manual cleanup that fills a workday.

You don’t need all of them. Even one or two can make a noticeable difference if they match work you already do often.

If you build one of these this week, you’ll feel the benefit quickly. If you build a few over time, they become part of how you run your work day to day.

New traffic data shows that ChatGPT’s share of overall AI traffic has dipped while Google’s Gemini is gaining ground. For the first time in years, OpenAI’s lead is noticeably smaller as alternatives become more widely adopted. For anyone building workflows around specific AI platforms, this is a reminder that the landscape remains competitive and that being platform-agnostic can be an advantage as capabilities and user adoption evolve.

🔗 Read more: ChatGPT's lead shrinks as Gemini surges in AI traffic war

New figures from the Organisation for Economic Co-operation and Development (OECD) show that more than one-third of people across member countries used generative AI in 2025, with uptake continuing to grow. This expansion in everyday use matters because it means AI is no longer a niche tool for tech teams, it’s part of how professionals and consumers handle tasks, research, creative work, and problem solving. Tools and automations will increasingly need to fit into that context, not sit alongside it.

🔗 Read more: AI use by individuals surges across the OECD as adoption by firms continues to expand

OpenAI has confirmed plans to begin testing advertisements inside ChatGPT for free and ChatGPT Go users in the U.S. The ads will be clearly separated from the chatbot’s responses, and OpenAI says they won’t influence the answers themselves. Paid tiers like Pro and Enterprise won’t include ads. This marks a notable shift in how AI tools are monetised and it could open up new ways for businesses to reach users directly inside the chat experience, but it also raises questions about trust and how these models stay useful without distraction.

🔗 Read more: Our approach to advertising and expanding access to ChatGPT

Tidio handles the first layer of customer questions so support doesn’t constantly interrupt real work.

Reusable ChatGPT setups take care of writing, formatting, summarising, and cleanup tasks that normally get done manually.

The prompts turn repeat jobs into something closer to a process than a decision you have to rethink each time.

Pick one thing that keeps coming up during your week: Support questions, documents, transcripts, writing and replace just that. Once it’s running, it frees up more space than you expect.

If you try any of the systems or prompts from this issue, reply and let me know how it went. I read every response, and it helps shape what I cover next.

Thanks for tuning in this week!