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AI team for companies, workflows, and skills for everyday operations.

I help companies and managers roll out AI into the business so it does not feel like a chat, but like a practical team of digital coworkers for sales, marketing, management, and day-to-day operations. We start without big development work. We build AI workflows, skills, and context that you can keep refining for your own company.

I want to build my AI team

Companies already use AI. Fewer know how to roll it into their process.

AI has already entered companies. But most people still use it mainly as a chat tool for quick answers, text drafts, or small automations. That helps, but it does not move the business forward on its own.

Real progress comes when AI stops acting like a one-off helper and starts working like an AI team. When it has context, rules, roles, and follow-up steps in sales, marketing, support, and operations.

2024 was the year of personal AI assistants. 2025 is the year of company AI teams. 2026 will belong to the people who build their own team of digital coworkers.

The difference will not come from who can talk to a chatbot better. It will come from who can connect AI to real work so it produces repeatable process and measurable performance.

Today it looks the same in most companies. One person gets help with an email. Another generates meeting notes. A third prepares an analysis or a small automation. Everyone gets a little help, but the company as a whole often still works the same way.

But a company is not a set of prompts. A company is a system. And that is exactly where the biggest opportunity for AI workflows and company rollout lies today.

Having an AI assistant is not enough. Performance will grow for the companies that build an AI team.

I help companies and managers build their own AI team of digital coworkers for sales, marketing, project management, client care, support, and everyday operations. No long development cycle, no blind experimentation. We start practically and adapt the system to the company over time.

What I help companies with

AI consulting for companies, AI rollout into the business, and workflow design for sales, marketing, support, and internal operations.

  • AI rollout into the company

    Without heavy development or random experimentation.

  • AI workflows for sales

    Follow-up, prep work, and prioritization.

  • Skills and company context

    Text files that tell AI how to actually work.

  • Tool integrations

    Email, calendar, CRM, and other company systems.

  • AI teams for operations

    Marketing, support, and internal processes.

  • A practical pilot

    A quick test in real work, not just a presentation.

The next step is a system of work and AI workflows

A common assumption is that using AI in a real company means new internal software, long development, and a large integration project. In practice, the start is simpler. Tools like Claude Code or Codex can do a lot. There are more tools, and they will keep changing. But the point is not the tool itself. The point is the AI workflow you build around it.

What context do you give it, what rules, what steps should connect, what information should it know, what should it work with, and what should it return. Once you connect AI to email, calendar, CRM, ERP, or other company data and give it a clear logic, it stops being chat. It becomes a system that works as part of the company.

It starts with a plain file and a clear brief

At the beginning, there is no complex technology. There is a well-described company. A simple text file where you define the company logic, priorities, communication style, and the biggest friction points. That becomes the base for the first AI workflow.

company-context-starter.md

# Company context starter

## Company name
Your company name

## What we do
Describe the core business in a few clear sentences. Focus on real work, not slogans.

## Our priorities
- sales
- customer care
- marketing
- operations
- internal coordination

## How we work
- direct communication
- fast response
- clear ownership
- simple handoffs

## Biggest friction points
- too much manual work
- information scattered across tools
- weak follow-up
- inconsistent outputs

## AI can help with
- research
- drafting
- summarizing
- prioritizing
- follow-up

## Tone of voice
Write the way the company actually speaks.

That is how the company context starts. Not with technical magic. Just with a clearly written company logic that AI can work with.

It begins with a company profile and context

company-profile.md

# Company profile

## Company name
Example company

## What we do
We help companies build and roll out AI teams, skills, and practical workflows for sales, marketing, project management, support, and other parts of the business.

## Who we work for
Small and medium-sized companies, founders, managers, and teams that want better performance without building custom software from scratch.

## Competitive advantage
We do more than design the system. We help actually put it into practice. We combine strategy, practical implementation, and team training.

## Typical services
- AI workflow design
- skill creation
- AI team implementation
- consulting and training
- sales and process automation

## Problems we solve
- chaos in the sales process
- low productivity
- underused AI
- missing operating system
- dependency on specific people

## How we communicate
Direct, practical, and without marketing fluff. Focused on fast use in real work.

A file like this is not documentation for a drawer. It is the living foundation of your AI team. You keep adjusting it based on reality, and that is how you tune the whole system.

Every member of the AI team needs a clear role and a skill

The next layer is skills. Again, these are simple text files. But this time they do not describe the company. They describe a specific job. They tell the AI team member how to think, what to do, what information to use, and what output to return.

For example, you can create a skill for researching companies you want to approach. Such a skill can tell the system to:

  • check the business register and company registry
  • find public information about the company
  • map the website and digital maturity
  • review social channels
  • look for signals of growth, hiring, expansion, or change
  • estimate the company’s likely needs
  • suggest the best outreach approach
  • prepare the next commercial steps

Skill: company research for a sales opportunity

company-research-skill.md

# Skill: Company research for a sales opportunity

## Goal
Find as much relevant information about a company as possible and suggest business opportunities based on our services and products.

## What to find
- basic company identification data
- legal form and status
- size, revenue, and number of employees, if available
- line of business
- company leadership and key people
- contacts and locations
- website and digital maturity
- activity on LinkedIn, Facebook, Instagram, and YouTube
- latest posts and their topics
- signals of growth, hiring, expansion, or change
- areas where our services may be relevant
- possible pain points
- recommended way to reach out first

## Output
1. Company summary
2. Sales opportunities
3. What to offer
4. Email strategy draft
5. Cold call preparation
6. First-meeting preparation
7. Recommended next prompts

This is the important part. You are still working with plain text files. You can edit, expand, and test them yourself. You do not have to wait for someone to ship a new software feature. You build and refine the process continuously on your own.

It is connected work.

Once you have the company context and a skill for a specific task, you can ask for something very simple:

“Research company XY according to our skill and suggest what we can offer based on our products and services.”

And that is where the difference between using AI and running an AI team starts to show. You do not just get an answer. You get prepared work. The system starts collecting information, evaluating context, and suggesting the next steps.

Example output after the first company research

To make this concrete, here is an example of what a research output can look like for one company. This is not just one email. It is complete preparation for acquiring a new company. And that is where AI becomes truly useful.

research-output.txt

Company summary
XY Logistics Ltd. is a regionally strong logistics and warehousing company based in Ostrava, serving the Moravian-Silesian and Olomouc regions. It focuses on warehousing, distribution, internal logistics, and supporting services for manufacturing companies and e-commerce. Publicly available information suggests the company is growing its capacity and likely expanding business opportunities.

First commercial conclusion:
This is not a company that lacks work. It is more likely a company where the challenge is follow-through, prioritization, and using information across sales, marketing, and leadership. That makes it a good candidate for a pilot that is not built around the promise of "saving clicks," but around improving pace and decision quality in the sales process.

Basic company profile
Legal form: limited liability company
Status: active
Headquarters: Ostrava
Coverage: Moravian-Silesian and Olomouc regions
Employees: approximately 85
Revenue: estimated CZK 120-180 million per year
Managing director: Petr Filip
Sales director: Jana Vítková
Digital maturity: medium

What matters commercially
- the company is no longer small, so the number of handoffs and manual steps is growing
- the company is large enough for inefficiency in sales preparation and follow-up to start compounding
- if the company is investing in capacity and growth, it will feel pressure on sales performance and management
- at this stage, the problem is often less about missing data and more about not working with it systematically

Public digital footprint
LinkedIn
1,280 followers
Latest post: Expanding warehouse capacity with a new hall in Mošnov
Estimated reach: 4,800 views

Facebook
860 followers
Latest post: Photos from the opening of the new warehouse section
Estimated reach: 1,900

Instagram
420 followers
Latest post: Short video from the warehouse and dispatch area
Estimated reach: 1,100

YouTube
95 subscribers
Latest video: How our new cross-dock process works
Estimated views: 640

Interpretation of the digital footprint
- the company communicates growth and operational development, not just employer branding
- the main public message is capacity, operations, and expansion
- the content feels more informational than sales-driven
- marketing likely exists, but is not tightly connected to sales prioritization
- if the sales team does not work with these signals systematically, part of the natural outreach opportunity is lost

Growth and change signals
- the warehouse expansion in Mošnov suggests investment activity and likely pressure to use the new capacity quickly
- the communication around new operational capabilities suggests the company wants to be seen as a growing and more modern player
- for companies like this, the critical challenge is aligning operational reality, acquisition pace, and existing client work
- growth in capacity also increases the demands on internal coordination, reporting, and sales preparation

Likely needs and pain points
1. Sales preparation is likely time-consuming and inconsistent
The salesperson or leadership has to look up information manually, piece together the picture, prepare the argument, and decide what matters for a specific client. That slows things down and the quality of output depends on the person.

2. Follow-up after meetings can be fragmented
In companies of this size, good meetings often happen, but follow-up is weak. Notes are not consistent, the next step is not specific enough, and momentum gets lost.

3. Leadership probably does not have a fast enough view of sales follow-through
The data probably exists in CRM, email, calendars, and people's heads, but it is not turned into a clear system that shows where the sales process is moving and where it is stuck.

4. Marketing and sales may operate side by side rather than together
The public footprint shows the company is communicating something, but it is not obvious that content and sales prioritization are tightly connected. That is a common place where performance leaks away without anyone noticing immediately.

5. Company growth increases dependence on a few key people
As the company grows, the risk also grows that knowledge about clients, follow-ups, and priorities is scattered and held by only a few people. That is not scalable in the long run.

Sales hypothesis
For XY Logistics, the main opportunity is not "AI in general." The real opportunity is to introduce an AI team into specific follow-through steps:
- company research before outreach
- sales argument preparation
- post-meeting follow-up
- working with communication history
- preparation of materials for leadership and sales

In other words:
I would not sell them technology. I would sell them higher pace and better quality in sales follow-through without having to expand the team right away.

Where the commercial opportunity is
For this company, the strongest offer would be:

1. AI workflow for sales research and outreach preparation
Use cases:
- research the target company
- evaluate the opportunity
- suggest the right offer
- prepare the first message and meeting questions

Benefits:
- less preparation time for the salesperson
- better quality first contact
- less improvisation

2. AI team for post-meeting follow-up and ongoing sales execution
Use cases:
- meeting notes
- structured client context updates
- suggested next step
- follow-up email draft
- tracking open opportunities

Benefits:
- better follow-through discipline
- less dependence on individuals
- lower risk of losing momentum after a meeting

3. Connecting marketing and sales
Use cases:
- identify topics that resonate with target accounts
- select the right contacts based on content and signals
- connect newsletter, content, and outreach

Benefits:
- marketing is not a separate activity
- content supports real commercial movement

4. AI support for leadership and faster information handling
Use cases:
- quick summary of the sales situation
- identify open opportunities with no movement
- prepare decision materials

Benefits:
- leadership gets a better overview
- faster decisions
- less information noise

Opportunity priority
Priority 1
AI team for sales preparation and post-meeting follow-up
Reason:
The fastest route to visible impact. Low resistance to adoption. Clearly measurable benefit.

Priority 2
Connecting marketing and sales
Reason:
Makes sense once sales follow-through is under control and the company is ready to expand the system into more areas.

Priority 3
Management reporting and opportunity prioritization
Reason:
Suitable as a second or third phase, not as the first entry point.

Recommended first step
I would not start with a big transformation. The best first step is a pilot on one specific process.

Recommended pilot
AI team for sales preparation and post-meeting follow-up

Why this pilot
- it is close to revenue and sales team performance
- the benefit is understandable for both leadership and sales
- it does not depend on a large infrastructure
- it can be built on top of existing tools
- it can be tested quickly on real opportunities

Pilot goal
- speed up sales preparation
- improve outreach quality
- unify follow-up
- reduce dependence on individuals
- create a base for further expansion

What the pilot could look like in practice
Phase 1: understand the reality
- map the current sales process
- identify where delays and follow-through losses happen
- choose one specific workflow for the pilot

Phase 2: build context and skills
- create the company context
- create a skill for company research
- create a skill for post-meeting follow-up
- create a basic workflow between those steps

Phase 3: pilot operation
- use it on the first 10 to 20 real opportunities
- refine outputs based on sales feedback
- connect the follow-up to CRM or internal tracking

Phase 4: evaluate
- how much time was saved in preparation
- how much more consistent the follow-up became
- whether the team gained better quality inputs
- whether the process became more repeatable

What the result should look like
The goal is not a flashy demo. The goal is a working process that:
- helps the salesperson prepare faster
- keeps the conversation in context
- reduces the loss of momentum after meetings
- makes outreach more relevant
- gives leadership clearer visibility

In that sense, the pilot is less about AI and more about a better way of running the sales process.

What this is not
This is not about replacing people.
This is not about building a giant internal system right away.
This is not about forcing AI into every process at once.

It is about finding one valuable workflow, making it work well, and then expanding from there.

Suggested next step
The most useful next step is a short working session focused on one specific process:
- sales research
- post-meeting follow-up
- internal reporting
- marketing-sales handover

From there, it becomes clear what the first workflow should be and what the AI team needs to do.

Once it works once, it can scale

Once you have the company context, skills, and workflow in place, you can scale the whole process. You prepare a list of target companies, for example in Excel, and tell the system:

“Use the companies in the file and prepare company research based on our skill.”

Then you leave for the day and wake up to prepared sales work for 50 companies. Not just a list of names, but:

  • company context ready for reuse
  • matching skills for each task
  • repeatable workflow instead of one-off prompting
  • faster preparation for more companies
  • more consistent quality of output
  • less manual work in the morning

You do not start from zero in the morning. You continue from work that is already prepared.

Gradually, you build an AI team for the whole process

Once the first part works, you can add the next connected steps.

Examples of additional connected steps

prepare a short brief for each company before outreach
turn meeting notes into structured follow-up tasks
draft a follow-up email after every meeting
summarize the sales status for leadership

More examples:

  • company research before a cold call
  • lead prioritization based on company signals
  • internal briefing before a sales meeting
  • content ideas based on recurring customer pain points

That is no longer one prompt. That is a connected work system.

I already have skills and tools for the main parts of a company

All of this can already be used today. Practically and without waiting for a long development cycle.

I already have skills and tools for the main parts of company operations:

  • sales research and outreach preparation
  • post-meeting follow-up and next-step drafting
  • company context and knowledge base
  • lead prioritization and account selection
  • marketing and sales handover
  • management summaries and reporting
  • AI support for support, operations, and everyday work

You load these skills into your AI team, adapt them for your own company, and can start using them very quickly. They are text files that you refine over time based on how your company, processes, and needs evolve.

This is how you create a system that does not wait for someone to code it one day in the future. You start using it now and improve it over time.

In each area, you get a team that works for you. And each person in the company can gradually build their own AI team for their own role.

When you do not want to just try AI, but actually use it

It makes sense when you want to use AI in the company practically, not just experimentally.

When you do not want to wait for software development, but want to start using a system you can gradually adapt for yourself right away.

When you want to strengthen sales, marketing, management, or support without unnecessary complexity.

And when you need someone who can design the whole system, help roll it out, and teach your team how to use it as an AI team for the company.

My role is not primarily to code. My role is to design and roll out the system.

I understand technology, but my main role is different. I help create a system that makes sense for the company and works in practice.

I look at the company as a whole: sales, processes, people, tools, AI, and the way management works. That is where I help companies make a practical leap. It is about rolling AI into the company so it becomes a real support for the work, not just another experiment.

It is not just about the technology. It is about making sure the whole system actually works and delivers results.

Do you want to roll out an AI system in your company, not just another chat?

I can help you design an AI team, prepare skills, connect them to your tools, and roll them into daily company operations. From the first workflow to scaling into additional areas.

I want the first step

Frequently asked questions about the AI team

Contact form

Tell me what your company is dealing with. I will respond concretely and suggest what the first practical step could look like.