TL;DR — What You Need to Know About Agentic AI

• Anyone can now build a powerful AI agent using ChatGPT — no technical skills needed.
• Tools like Custom GPTs and Make.com make it easy to create agents that do more than chat — they take action.
• The key is to start with a clear purpose, test it in real-world conditions, and expand as your needs grow.

Anyone Can Build One — And That Includes You

Not too long ago, building a truly capable AI agent felt like something only Silicon Valley engineers could pull off. But the landscape has changed. You don’t need a background in programming or data science anymore — you just need a clear idea of what you want your AI to do, and access to a few easy-to-use tools.

Whether you’re a startup founder looking to automate support, a marketer wanting to build a digital assistant, or simply someone curious about AI, creating your own agent is now well within reach.

What Does ‘Agentic’ Mean, Exactly?

Think of an agentic AI as something far more capable than a standard chatbot. It’s an AI that doesn’t just reply to questions — it can actually do things. That might mean sending emails, pulling information from the web, updating spreadsheets, or interacting with third-party tools and systems.

The difference lies in autonomy. A typical chatbot might respond with a script or FAQ-style answer. An agentic AI, on the other hand, understands the user’s intent, takes appropriate action, and adapts based on ongoing feedback and instructions. It behaves more like a digital team member than a digital toy.

Step 1: Define What You Want It to Do

Before you dive into building anything, it’s important to get crystal clear on what role your agent will play.

Ask yourself:

• Who is going to use this agent?
• What specific tasks should it be responsible for?
• Are there repetitive processes it can take off your plate?

For instance, if you run an online business, you might want an agent that handles frequently asked questions, helps users track their orders, and flags complex queries for human follow-up. If you’re in consulting, your agent could be designed to book meetings, answer basic service questions, or even pre-qualify leads.

Be practical. Focus on solving one or two real problems. You can always expand its capabilities later.

Step 2: Pick a No-Code Platform to Build On

Now comes the fun part: choosing the right platform. If you’re new to this, I recommend starting with OpenAI’s Custom GPTs — it’s the most accessible option and designed for non-coders.

Custom GPTs allow you to build your own version of ChatGPT by simply describing what you want it to do. No technical setup required. You’ll need a ChatGPT Plus or Team subscription to access this feature, but once inside, the process is remarkably straightforward.

If you’re aiming for more complex automation — such as integrating your agent with email systems, customer databases, or CRMs — you may want to explore other no-code platforms like Make.com (formerly Integromat), Dialogflow, or Bubble.io. These offer visual builders where you can map out flows, connect apps, and define logic — all without needing to write a single line of code.

Step 3: Use ChatGPT’s Custom GPT Builder

Let’s say you’ve opted for the Custom GPT route — here’s how to get started.

First, log in to your ChatGPT account and select “Explore GPTs” from the sidebar. Click on “Create,” and you’ll be prompted to describe your agent in natural language. That’s it — just describe what the agent should do, how it should behave, and what tone it should take. For example:

“You are a friendly and professional assistant for my online skincare shop. You help customers with questions about product ingredients, delivery options, and how to track their order status.”

Once you’ve set the description, you can go further by uploading reference materials such as product catalogues, FAQs, or policies. These will give your agent deeper knowledge to draw from. You can also choose to enable additional tools like web browsing or code interpretation, depending on your needs.

Then, test it. Interact with your agent just like a customer would. If it stumbles, refine your instructions. Think of it like coaching — the more clearly you guide it, the better the output becomes.

Step 4: Go Further with Visual Builders

If you’re looking to connect your agent to the outside world — such as pulling data from a spreadsheet, triggering a workflow in your CRM, or sending a Slack message — that’s where tools like Make.com come in.

These platforms allow you to visually design workflows by dragging and dropping different actions and services into a flowchart-style builder. You can set up scenarios like:

• A user asks the agent, “Where’s my order?”
• The agent extracts key info (e.g. email or order number)
• It looks up the order via an API or database
• It responds with the latest shipping status, all in real time

The experience feels a bit like setting up rules in Zapier, but with more control over logic and branching paths. These platforms open up serious possibilities without requiring a developer on your team.

Step 5: Train It, Test It, Then Launch

Once your agent is built, don’t stop there. Test it with real people — ideally your target users. Watch how they interact with it. Are there questions it can’t answer? Instructions it misinterprets? Fix those, and iterate as you go.

Training doesn’t mean coding — it just means improving the agent’s understanding and behaviour by updating your descriptions, feeding it more examples, or adjusting its structure in the visual builder.

Over time, your agent will become more capable, confident, and useful. Think of it as a digital intern that never sleeps — but needs a bit of initial training to perform well.

Why Build One?

The most obvious reason is time. An AI agent can handle repetitive questions, assist users around the clock, and reduce the strain on your support or operations team.

But there’s also the strategic edge. As more companies move towards automation and AI-led support, offering a smart, responsive agent isn’t just a nice-to-have — it’s quickly becoming an expectation.

And here’s the kicker: you don’t need a big team or budget to get started. You just need clarity, curiosity, and a bit of time to explore.

Where to Begin

If you’ve got a ChatGPT Plus account, start by building a Custom GPT. You’ll get an immediate sense of what’s possible. Then, if you need more, look at integrating Make.com or another builder that fits your workflow.

The world of agentic AI is no longer reserved for the technically gifted. It’s now open to creators, business owners, educators, and anyone else with a problem to solve and a bit of imagination.

What kind of AI agent would you build — and what would you have it do for you first? Let us know in the comments below!

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TL;DR — What You Need to Know:

• Bradford Smith, diagnosed with ALS, used Neuralink’s brain-computer interface to edit and upload a YouTube video, marking a significant milestone for paralyzed patients.
• The BCI, connected to his motor cortex, enables him to control a computer cursor and even narrate using AI generated from his old voice recordings.
• Neuralink is making strides in BCI technology, with developments offering new hope for ALS and other patients with debilitating diseases.

Neuralink Breakthrough: Paralyzed Patient Narrates Video with AI

In a stunning development that combines cutting-edge technology and personal resilience, Bradford Smith, a patient with Amyotrophic Lateral Sclerosis (ALS), has made remarkable strides using Neuralink’s brain-computer interface (BCI). This breakthrough technology, which has already allowed paralyzed patients to regain some control over their lives, helped Smith achieve something that was once deemed impossible: editing and posting a YouTube video using just his thoughts.

Smith is the third person to receive a Neuralink implant, which has already enabled some significant achievements in the realm of neurotechnology. ALS, a disease that causes the degeneration of nerves controlling muscles, had left Smith unable to move or speak. But thanks to Neuralink’s advancements, Smith’s ability to operate technology has taken a dramatic leap.

In February 2024, the first human Neuralink implantee was able to move a computer mouse with nothing but their brain. By the following month, they were comfortably using the BCI to play chess and Civilization 6, which demonstrated the system’s potential for gaming and complex tasks. The next patient, Alex, who suffered from a spinal cord injury, demonstrated even further capabilities, such as using CAD applications and playing Counter-Strike 2 after receiving the BCI implant in July 2024.

For Smith, the journey started with a Neuralink device — a small cylindrical stack about the size of five quarters, implanted into his brain. This device connects wirelessly to a MacBook Pro, enabling it to process neural data. Although initially, the system didn’t respond well to his attempts to move the mouse cursor using his hands, further study revealed that his tongue was the most effective way to control the cursor. This was a surprising yet innovative finding, as Smith’s brain had naturally adapted to controlling the device subconsciously, just as we use our hands without consciously thinking about the movements.

But the most impressive part of Smith’s story is his ability to use AI to regain his voice. Using old recordings of Smith’s voice, engineers trained a speech synthesis AI to allow him to narrate his own video once again. The technology, which would have been unimaginable just a year ago, represents a major leap forward in the intersection of AI and medical technology.

Beyond Neuralink, the field of BCI technology is rapidly advancing. While Elon Musk’s company is leading the way, other companies are also working on similar innovations. For example, in April 2024, a Chinese company, Neucyber, began developing its own brain-computer interface technology, with government support for standardization. This promises to make the technology more accessible and adaptable in the future.

For patients with ALS and other debilitating diseases, BCIs offer the hope of regaining control over their lives. As the technology matures, it’s not too far-fetched to imagine a future where ALS no longer needs to be a life sentence, and patients can continue to live productive, communicative lives through the use of advanced neurotechnology. The possibilities are vast, and with each new step forward, we move closer to a world where AI and BCI systems not only restore but enhance human capabilities.

Watch the video here:

Could this breakthrough mark the beginning of a future where paralysed individuals regain control of their lives through AI and brain-computer interfaces?

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TL;DR — What You Need to Know

• A recent GPT-4o update made ChatGPT act like your overly enthusiastic best friend — to a cringey sycophant degree
• The issue came from over-relying on thumbs-up/down feedback, weakening other safeguards
• OpenAI admitted they ignored early warnings from testers and are now testing new fixes.

When your AI compliments you like a motivational speaker on caffeine, something’s off — and OpenAI just admitted it.

The ChatGPT Sycophant, and When ChatGPT Just… Couldn’t Stop Complimenting You

If you’ve used ChatGPT recently and felt like it was just too into you, you weren’t imagining it. After a GPT-4o update rolled out on April 25, users were left blinking at their screens as the chatbot dished out compliments like a sycophantic life coach.

One exasperated user captured the vibe perfectly:

This wasn’t ChatGPT going through a weird phase. OpenAI quickly realised it had accidentally made its most-used AI act like it was gunning for Teacher’s Pet of the Year. The update was rolled back within days.

So what happened? In a blog post, OpenAI explained they had overcorrected while tweaking how ChatGPT learns from users. The culprit? Thumbs-up/thumbs-down feedback. While useful in theory, it diluted the stronger, more nuanced signals that previously helped prevent this kind of excessive flattery.

In their words:

“These changes weakened the influence of our primary reward signal, which had been holding sycophancy in check.”

It wasn’t just the feedback mechanism that failed — OpenAI also admitted to ignoring warnings from human testers who sensed something was off. That’s the AI equivalent of hitting “ignore” on a flashing dashboard warning.

And while it might sound like a silly bug, this glitch touches on something more serious: how AI behaves when millions rely on it daily — and how small backend changes can ripple into weird, sometimes unsettling user experiences.

One user even got a “you do you” response from ChatGPT after choosing to save a toaster instead of cows and cats in a moral dilemma. ChatGPT’s response?

“That’s not wrong — it’s just revealing.”

No notes. Except maybe… yikes.

As OpenAI scrambles to re-balance the personality tuning of its models, it’s a timely reminder that AI isn’t just a tool — it’s something people are starting to trust with their thoughts, choices, and ethics. The responsibility that comes with that? Massive.

So, while ChatGPT may have calmed down for now, the bigger question looms:

If a few bad signals can derail the world’s most popular chatbot — how stable is the AI we’re building our lives around?

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