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In this video, I'll take you through a hands-on session with an agent. AI SDR. The idea is to showcase an entire automated funnel. We'll connect lead generation, qualification, CRM, and follow-up into a single flow.

The goal is simple. Receive the lead, respond immediately, and qualify it with context. After that, pass it on to the salesperson at the right time.

Example with form and WhatsApp

Example with form and WhatsApp

We start with a simple form. It can be Tally or whatever you already use on your website. Name, phone number, email, and the lead's needs.

As soon as the lead submits, the automation is triggered in N8N. The agent sends the first message in Whatsapp. Service begins in seconds, with no waiting.

The agent understands the context of the request. They respond in a humanized way based on the data in the form. And they guide the conversation towards qualification.

Qualification and transfer to the seller.

Qualification and transfer to the seller.

The AI SDR asks objective questions. It identifies pain points, urgency, budget, and the ideal service. It records everything so that no information is lost.

When interest increases, the agent changes the status in the CRM. They stop the automated service and transfer it directly to a human salesperson to finalize the transaction.

Automation and database

Automation and database

Every interaction is recorded in Supabase. This ensures historical data, metrics, and governance. It facilitates auditing and agent evolution.

The modeling saves the name, contact, origin, and stage. It also saves the latest messages and follow-up tags. This ensures accurate reports and mailings.

Integration with Notion CRM

Integration with Notion CRM

The CRM in the example is the Notion. But the logic applies to Pipedrive, RD Station or any other. You just need an API and connect to it. N8N.

The main columns are clear: New lead, human interaction, sale completed, and finalized. The agent moves the cards according to the progress.

When qualifying, the agent creates a summary on the card. It includes the main pain point, suggested solution, and next action. The salesperson then knows exactly what to do.

Follow-up function

If the lead stops responding, no one is left in the dark. The agent triggers a reactivation sequence. The schedule and rules are saved in the database.

The texts are useful and respectful. No spam, always with clear value. The focus is on making the lead's decision easier.

Tools and architecture

Tools and architecture

Conversation interface in Whatsapp. Automation and orchestration in N8N. Database in Supabase.

The form can be Tally or equivalent. CRM can be Notion or another of your choice. The architecture is flexible and modular.

We use the agent RAG For context. Memory to keep the conversation cohesive. And functions to trigger CRM and database.

Master stream and multimedia resources

Master stream and multimedia resources

The master workflow understands text, images, and audio. It breaks long messages into parts and responds in order. Everything is logged for reference and continuous improvement.

There's a dedicated subflow for Notion. It automatically creates, moves, and comments on cards. This keeps the pipeline and the team aligned.

Summary for salespeople

Summary for salespeople

The card arrives with pre-defined context. Who the lead is, what they requested, and what the agent suggested. Plus the recommended next step.

This reduces friction during the handoff process. It increases the conversion rate and closing speed. The salesperson focuses on closing, not on investigating.

Follow-up Strategies

Follow-up Strategies

Define specific time windows. Practical example: 2 hours for Follow Up 1, 4 hours for Follow Up 2. Then, mark it as unanswered and close the interview.

For e-commerce, use cart abandonment tracking. For recurring services, use scheduled reminders. Bonuses and discounts can trigger a response.

The important thing is to record each message sent. Who received it, when they received it, and what the message was. This prevents repetition and keeps you in control.

Agents 2.0 Training and Templates

Agents 2.0 Training and Templates

If you want to replicate it, the Training AI Agent Manager 2.0 It helps. There you'll find flow templates, prompts, and integrations. Plus support, a community, and case studies.

With a solid foundation and guided practice, you accelerate execution. You build professional agents with governance and metrics. And you put your funnel on high-quality autopilot.

In the context of 2025, where the speed of information and the personalization of the consumer experience are crucial competitive differentiators, the use of AI agent for digital marketing It has ceased to be a trend and has become a fundamental reality.

According to a McKinsey report on AI adoption in marketing, These agents not only automate tasks, but also make autonomous decisions based on data, behaviors, and business objectives.

In this comprehensive guide, you will discover how they work, what they are used for, which tools to use, and why companies that master this technology are light years ahead of the competition.

What is an AI agent for digital marketing?
What is an AI agent for digital marketing?

What is an AI agent for digital marketing?

One AI agent for digital marketing It is an autonomous entity based on artificial intelligence that operates with partial or total autonomy in marketing processes, such as lead generation, audience segmentation, content creation, data analysis, and campaign execution.

To better understand the concept, it's worth consulting this. academic definition of intelligent agents. These agents use machine learning models and natural language processing to understand behaviors and respond in a personalized way at scale.

Unlike simple automations, such as scheduled emails or response bots, AI agents are able to learn from past interactions, adapt their strategies, and act based on real-time metrics.

A classic article from Harvard Business Review on adaptive automation This highlights the natural evolution of data-driven digital marketing.

How do intelligent agents work in modern marketing?

AI agents operate by integrating internal data (CRM, ERPs, funnels) with external data (market trends, social networks, user behavior).

For a technical dive, the CDP Institute It maintains a comprehensive guide on the governance of this data. From this database, agents can make decisions and perform tasks independently.

For example, an agent can:

  • Detect that a lead has visited a pricing page three times and has not yet converted;
  • Personalize an email with a specific offer based on past behavior;
  • Monitor email open rates and interaction, and reschedule follow-up if the lead clicks or ignores the email.

This adaptive logic is what allows for a truly customer-centric marketing experience.

Tools and platforms that utilize AI agents.

In 2025, some of the most relevant tools for creating and managing AI agents for marketing include:

Make (Integromat)

With its visual approach and integration with thousands of apps systems, it's possible to create agents that react to events in CRMs, landing pages, and e-commerce platforms. Learn more about it. official Make website to explore advanced integrations.

O No Code Start Up Makeup Course (Integromat) It teaches exactly how to build these smart routines.

Agents with OpenAI and Dify

Using GPT-40 models and tools such as Agents Course with OpenAI, It is feasible to create agents that write copy, converse with leads in real time, and analyze sentiment in comments.

THE OpenAI documentation it's the Official guide to Dify They show how these agents can be deployed with logical flows and contextual memory.

Salesforce Einstein & HubSpot AI

Established platforms have also made progress in adopting AI. Salesforce Einstein for Marketing It recommends customized automations based on historical data, while the HubSpot AI Detects cross-selling opportunities in real time.

Real-world use cases of AI agents in digital campaigns.
Real-world use cases of AI agents in digital campaigns.

Real-world use cases of AI agents in digital campaigns.

E-commerce with predictive AI

The online retailer Dafiti has implemented an AI agent to recommend personalized products in emails based on purchase and browsing history.

According to Detailed case study published in TI Inside, The initiative not only increased the conversion rate by 28 %, but also provided reduction of operational costs of up to 80% % and significant gains in agility in campaign execution.

B2B demand generation

Companies like Resultados Digitais (RD Station) have implemented agents that identify leads most likely to convert based on behavioral signals.

O RD Station official case This demonstrates the reduction in commercial response time achieved by 40%.

Social listening with autonomous response

Brands like Netflix use agents that monitor social media and automatically react to mentions with content suggestions or humorous responses.

THE Brand24 analyzed how Netflix dominates social media. analyzed this strategy and its impact on engagement.

Strategic benefits of AI agents in digital marketing.

Companies that correctly implement AI agents are able not only to scale their operations, but also to dramatically increase the efficiency of their campaigns. A report from Deloitte on personalization at scale. proves gains such as:

  • Customization at scale: Each user receives interactions tailored to their profile and stage in the journey.
  • Real-time decisions: Optimizing campaigns as the data changes.
  • Reducing operational costs: Less need for giant teams for tactical execution.
  • Learning speed: The agents improve as they operate, creating a positive feedback loop.
Trends for 2025 and beyond in the use of intelligent agents.
Trends for 2025 and beyond in the use of intelligent agents.

Trends for 2025 and beyond in the use of intelligent agents.

With the popularization of multimodal AI models and the concept of "autonomous marketing," the Gartner — Marketing Predictions 2025-2028 It projects an explosion in the adoption of specialized agents by channel (email, social media, SEO, CRM).

Another key point is the integration between AI and no-code interfaces, allowing marketing professionals to create their own agents without relying on developers.

Platforms like official Bubble manual it's the Dify Course They allow this construction in an intuitive way.

Innovations are also expected, such as agents with distinct personalities for each campaign, and regulation of generative AI — including initiatives like the EU AI Act — and advances in AI that encompass irony, humor, and deep brand context.

Moving forward with AI agents in marketing requires preparation.

It is clear that the use of AI agent for digital marketing This represents a clear competitive advantage in 2025.

However, successful implementation requires technical understanding, clarity of objectives, and choosing the right tools. 

If you want to master these skills, see the No Code Start Up training programs And start creating your first agents with a focus on performance, scale, and true personalization.

The adoption of AI for veterinary clinics It is profoundly reshaping animal healthcare. With the exponential increase in demand for faster, more effective, and personalized veterinary services, artificial intelligence is emerging as a strategic ally for clinics that want to raise their quality and productivity standards.

What is AI in the context of a veterinary clinic?
What is AI in the context of a veterinary clinic?

What is AI in the context of a veterinary clinic?

THE artificial intelligence (AI) It consists of using algorithms and computational models capable of simulating human decision-making.

In a veterinary clinic setting, this ranges from pattern recognition in imaging exams to automated appointment scheduling, including predictive diagnostic systems and automated medical record management.

Unlike traditional technologies, AI doesn't just automate tasks; it continuously learns from data.

This allows for more accurate diagnoses, faster interventions, and more efficient care.

Practical benefits of AI for veterinary clinics

The application of AI in veterinary clinics goes beyond innovation: it's about increasing the value of the care provided to pet owners and their animals.

One of the main impacts is in Reducing diagnostic errors, ...since AI systems can compare millions of clinical patterns in seconds. Furthermore, it enables:

  • Early identification of diseases through analysis of clinical and laboratory data;
  • Personalizing treatments based on history and behavioral patterns;
  • Intelligent inventory and supply management;
  • Optimizing the veterinary team's time.
AI tools and technologies applied to veterinary medicine.
AI tools and technologies applied to veterinary medicine.

AI tools and technologies applied to veterinary medicine.

Modern clinics are already using AI-powered platforms that integrate different resources. Among the most popular tools are:

AI-assisted diagnostic systems

Solutions like Vetology AI and SignalPET They analyze imaging exams (such as X-rays) in real time, identifying anomalies with high precision. These technologies accelerate the interpretation of exams and increase the reliability of assessments.

Virtual triage assistants

AI-powered agents and applications perform the initial screening of symptoms reported by pet owners, prioritizing care and guiding professionals on potential differential diagnoses.

Smart electronic health records

Software such as Shepherd Veterinary Software They use machine learning to suggest treatments, remember vaccinations, and predict complications based on past medical history.

Real-life success stories: AI in veterinary clinics in Brazil and around the world.

In Brazil, the Golden Vets, located in Cotia (SP), was the first veterinary clinic in the country to adopt the AI-assisted radiology platform. SignalPET.

According to clinical director Beatriz Soares Petri de Oliveira, the preview generated by the algorithm reduces the report delivery time from 24 hours to approximately 15 minutes, speeding up the start of treatment and increasing pet owner satisfaction.

In the United States, the Banfield Pet Hospital developed models of machine learning supported by more than eight million electronic medical records for predict the risk of chronic kidney disease in dogs and cats up to two years earlier.

The report Veterinary Emerging Topics 2023 It indicates an accuracy greater than 95% % and shows sustained reductions in anesthetic mortality after the adoption of clinical protocols based on these predictions.

How to implement AI in your veterinary clinic.
How to implement AI in your veterinary clinic.

How to implement AI in your veterinary clinic.

Before adopting any AI solution, it's essential to understand the reality of your clinic. The first step is to map the processes that consume the most time or have the highest chance of error.

Next, choose tools that are compatible with your service model.

It is also recommended to train the team in no-code and AI technologies. AI Agent and Automation Manager Training No Code Startup is an excellent option for teams that want autonomy in implementing artificial intelligence.

Common barriers and how to overcome them.

Despite the benefits, many clinics face challenges such as:

  • Lack of technical knowledge about AI;
  • Cost of implementing the technologies;
  • Team resistance to process change.

These issues can be overcome with continuing education, strategic planning, and the selection of accessible tools.

Courses like the N8N Course They help create complex automations without coding, which reduces deployment costs.

The future of AI for veterinary clinics: what's coming next?
The future of AI for veterinary clinics: what's coming next?

The future of AI for veterinary clinics: what's coming next?

Future innovations should include conversational agents trained on veterinary clinical data, integration with wearable devices for remote animal health monitoring, and more robust predictive algorithms.

Companies like VET.AI and the IDEXX They are leading this global transformation, which shows that the trend is irreversible.

For clinics that want to get ahead, starting to explore the possibilities of AI for veterinary clinics It's not just a strategic choice, but a necessity.

Next steps: empower yourself to lead the transformation.

By incorporating AI for veterinary clinics In your team's daily routine, you not only increase operational efficiency, but also deliver more humanized and proactive care.

Want to master the entire process of planning, implementing, and scaling these solutions? Enroll in... AI Agent and Automation Manager Training Join the No Code Start Up and become a leader in veterinary innovation.

Guys, the ChatGPT-5 arrived in August 7, 2025 And I rushed to summarize the news that impacts those who create technology, software and AI (Artificial Intelligence) agents.
The idea is straightforward and to the point. What's new, how to use it, and where it applies to your projects.

First, a message in the same vein as the video. A No-Code Startup is having a lifetime subscription week., Released for a limited time because of the anniversary. If it makes sense, check it out later and come back to the content.

Launch of ChatGPT-5 and its impact on the market.

What is ChatGPT 5 and what is its impact on the market?
Source: No-Code Startup and Open AI

GPT-5 came out faster, more accurate, and better for code.
This removes friction from prototypes and shortens the path to a working app.
Agent projects become more stable and easier to scale.

New features and performance improvements

What's new in the GPT 5 chat?
Source: No-Code Startup and Open AI

The model organizes responses more clearly and reduces errors.
It's better suited for debugging, explaining, and rewriting large sections.
It also received style adjustments for more didactic or informal answers.

Models: GPT-5, mini and nano

VariantBest for
gpt-5Complex reasoning, broad worldly knowledge, and agency tasks involving many codes or multiple steps.
gpt-5-miniCost-optimized reasoning and chat; balances speed, cost, and capacity.
gpt-5-nanoHigh-throughput tasks, especially simple follow-up or classification instructions.

The family comes in three sizes to balance cost and latency.
GPT-5 is the strongest for complex tasks and agents.
The mini and nano versions help to reduce costs and speed up simple workloads.

Creating apps and webapps within GPT.

What GPT changed for developers
Source: No-Code Startup and Open AI

Now you can request websites, apps, and even complete games directly from GPT.
The workflow became more visual and offered a quick preview.
The idea is to transform a prompt into a navigable prototype without leaving the environment.

Practical examples and use cases

How can I use ChatGPT to create an application?
Source: Open AI

There's a demo of an app that tracks camera movements in real time.
There are games for learning languages with simple mechanics and immediate feedback.
It has page generators, dashboards, and tools that read CSV files and have already turned graphs into charts.

Integration with tools like Cursor and Lovable

Node Cursor, GPT-5 writes and organizes the project with more consistency.
Node Lovable, the flow of creating an app from a single prompt continues.
For very complex projects, iteration is still necessary, but the leap helps a lot.

Price and cost-benefit of ChatGPT-5

How much does ChatGPT 5 cost?
Source: No-Code Startup and Open AI

The cost became competitive due to the gain in quality.
Mini and nano reduce your bill when call volume increases.
This combination opens up the possibility of more advanced apps systems without breaking the budget.

Summary of the jump

More good code, more control, and a better cost-to-performance ratio.
If you build agents, front-ends, or automations, you can start testing and measuring impact now.
Tell us in the comments what you thought of the launch and what project you plan to bring to life with the GPT-5.

Promotion: Lifetime access to Code Startup
Promotion: Lifetime access to Code Startup
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Matheus Castelo

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Neto Camarano

Two entrepreneurs who believe technology can change the world

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