Start with the challenge and KPIs
I analyze the team's processes, roles, and bottlenecks, selecting scenarios where AI can create measurable value rather than an impressive demo.
Now accepting corporate AI program bookings
For business owners · senior executives · functional leaders
From a business challenge to
a working AI tool in 1–2 days
An on-site corporate program for a team of 5–10 business owners and executives. Participants build prototypes for their own processes, define safe-use boundaries, and leave with a 30-day implementation plan. Standard scenarios can be prototyped without developers; requirements for IT and information security are captured separately in the implementation map.
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20+
years in business automation
developer / team lead / architect
developer / team lead / architect
30+
in-person workshops
over the last two years
over the last two years
1,000+
program participants
over the last two years
over the last two years
80%
of training program time is hands-on work
01 · Experience and trust
Corporate teams and expert platforms
Training, expert work, and speaking engagements across government, national television, banking, manufacturing, retail, and education. More than 1,000 people have taken part in 30+ in-person workshops over the last two years.
Sber
NTV television
Atlanty Business Club
Government of
Stavropol Krai
Voronezh Region
Ministry of Digital Development
School 21
VEB.RF
ALROSA
Rostic’s
02.1 · Professional background
From software and data to AI system architecture
More than 20 years in technology projects, 7+ years in AI, ML, and neural networks, and 10+ years training internal and external teams. This background makes it possible to address AI in the context of processes, data, roles, risk, and adoption—not as an isolated technology.
01 · Software developerSoftware solutions
Designing and implementing automation systems for business needs.
02 · Tech leadTechnical leadership
Coordinating teams, delivering projects, and transferring knowledge.
03 · Data engineerData and analytics
Data pipelines, transformation, and preparation of decision-ready information.
04 · ArchitectEnd-to-end systems
Applications, integrations, data, and processes from concept to implementation.
05 · AI expertAI and learning
LLMs, RAG, AI agents, and capability development for management teams.
02.3 · Method
From business challenge to applicable outcome
The program is built around participants' real challenges and KPIs: diagnosis, hands-on tool use, solution review, and a clear method for embedding the new capability within the team.
Design for the team
I build modules, cases, and practical work around the objectives—from a one-day intensive to a development program with progress tracking.
Build a usable capability
Participants solve their own challenges, build prototypes and AI tools through vibe coding, review mistakes, and receive feedback.
Translate it into business impact
The outcome is reinforced with an action plan, quality criteria, and team materials; extended support can include an impact review after 2–4 weeks.
In-person intensives
Live workshops and practicums for owners, executives, and teams—in person, in small groups, and focused on real challenges.
Corporate programs
End-to-end programs: needs analysis, modules, active practice, and post-program outcome evaluation.
Content and LMS
Lessons, assignments, assessments, scenarios, simulations, and video for internal platforms and knowledge bases—not just presentations.
Reviews and follow-up
Hands-on reviews, live sessions, and support for integrating AI tools into the team's work after training.
02.5 · For learning providers
AI program author and facilitator
I design learning for adult audiences—from the business challenge, learning objectives, and program architecture to practical assignments, assessment criteria, and launch support. I combine applied AI expertise with methods suited to executives and non-technical professionals.
Program or module
Topic decomposition, learning outcomes, module structure, lesson scripts, and the practice sequence.
Subject-matter expertise
Content review and validation of AI scenarios, constraints, safety considerations, and business applicability.
Hands-on sessions
In-person intensives, live online reviews, and workshops where participants build solutions and receive feedback.
Assignments and assessment
Cases, practice environments, assessments, checklists, quality criteria, and materials for independent reinforcement.
Evidence available now
Practice, learning design, and facilitation
This page presents the evidence that can be shared appropriately. Client names, testimonials, and outcomes are never supplemented with assumptions—only verifiable materials are used.
- Professional background: software development, technical leadership, data engineering, architecture, and AI
- Hands-on program design for management audiences
- Method: diagnosis, design, practice, and adoption support
- Topics: LLMs, RAG, AI agents, vibe coding, process automation, and safe AI use
03 · Corporate format
An on-site program at the client's premises
The program is delivered at the client's office or another agreed venue. Participants come from the same company and share business context, connected processes, and priorities, so the content is tailored to the specific management team.
- On-site delivery across European Russia — Moscow, St Petersburg, Kazan, Rostov-on-Don, Voronezh, or another city by agreement.
- Timing aligned with the business need. Dates are agreed directly with the client rather than tied to a public schedule.
- Your team is the cohort: 5–10 people from one team, each working on a real business challenge.
Delivery locations
Moscow
St Petersburg
Kazan
Rostov-on-Don
Voronezh
Another city by agreement
Discuss an on-site program →
04 · Programs
Hands-on programs
that move the team into implementation
Hands-on work on your team's real challenges. Together, we select the right program and agree the expected outcome and acceptance criteria in advance. The core format takes 1–2 days; an extended program with follow-up may run for up to three days.
04.1 · Why AI training fails to change work
Why training does not always change operating processes
Knowing about tools does not lead to adoption on its own. Workplace application requires a real challenge, hands-on practice, validation criteria, and a clear owner for the next step.
That is why participants work on their own use cases and finish the program with a prototype they can demonstrate to colleagues and develop further.
Passive learning does not transfer into daily operations
→You work on your own challenge and leave with a working tool—not just inspiration
AI services are available, yet standard processes are still handled manually
→We teach participants to build a working solution: input → processing → output
Vendor demos look impressive, but the team cannot reproduce them
→The solution is built by the participants themselves using approved or anonymized data, followed by a review of the results
There are no clear rules for data use or AI-output validation
→Safety boundaries and validation rules are addressed during the program
From a first AI tool to an enterprise adoption system
From a first AI tool to an enterprise adoption system
In one day, you cover a path that often takes companies months. In the morning, you build a working AI tool for your own challenge. In the afternoon, you develop it into a usable solution, create a functional automation map, and leave with a 30-day adoption plan.
This is not two separate workshops. It is one integrated journey: first, you experience the technology hands-on, then learn how to turn it into a managed process within the company.
This is for you if
- You know the business needs AI but do not know where to start—and do not want months of trial and error.
- You want to move from isolated experiments to a controlled, usable tool.
- You need an outcome that can be applied immediately after the program.
- You want hands-on experience rather than listening to someone else's case studies.
Morning · hands-on build 3.5–4 hrs
Lunch 1 hr
Afternoon · adoption system 3–4 hrs
Morning
3.5–4 hours
Part 1 · Build your first tool
45 min
Introduction and goal settingVibe coding and the task → generation → validation workflow
30 min
Use-case reviewSelect one task capable of creating value this week
15 min
Live demonstrationBuild a report generator and dashboard from an export—live
60 min
Hands-on practiceBuild your own tool with individual support
60 min
Outcome reviewDemonstrate, validate, and refine the solutions together
30 min
Application planIdentify 1–2 tasks to automate immediately afterwards
Afternoon
3–4 hours · afternoon
Part 2 · From tool to adoption system
70 min
Upgrade to an operational MVPDevelop the morning prototype with a reusable prompt, input template, error handling, Excel / PDF / HTML export, and a short user guideenhanced tool + user guide
60 min
Functional automation mapMap 5–7 processes by impact and complexity, identify 2–3 quick wins, and select one priority processautomation map
50 min
Safety, roles, and a 30-day planDefine permitted data, accountability for outputs, team roles, and a step-by-step monthly planadoption plan + checklist
Six practical deliverables
Working AI toolbuilt in the morning for your own challenge
Enhanced versionwith export, error handling, and a short user guide
Functional automation mapprocesses, impact, and priorities
30-day adoption planactions, owners, and deadlines
AI safety checklistwhat AI may access and what requires human validation
Prompt librarya starter set that makes the solution transferable
Full-day outcome
After the program, you begin with a working prototype, a priority map, and an adoption plan.
Who it is for
Book a full day for your team →
Business owners, senior executives, and functional leaders who want hands-on AI experience and an immediate plan for their team.
AI Agents for Business: Methods and Practice
AI Agents for Business: Methods and Practice
A foundation workshop for leaders who want to understand AI through hands-on work rather than articles. Bring a real challenge—a report, data export, or recurring task—and leave with a tool you built yourself and a clear view of what to automate next. No programming is required: describe the task in business language, let the AI agent build the solution, validate it, and take it into your work.
Does this sound familiar?
- Every Monday starts with hours of manual reporting in Excel rather than decision-making.
- The data exists, but the picture does not: margin erosion and underperformance become visible too late.
- AI is readily available, yet it is unclear where to begin without creating new risks.
What is included
- Vibe coding from first principles — use the task → generation → validation workflow to frame AI tasks precisely and avoid rework.
- Your real use case — work with your own report, data export, or recurring task—not an artificial demo.
- Report automation — move from a raw export to a decision-ready summary without a separate development project.
- Interactive dashboard — use charts and filters to see the business picture rather than a wall of numbers.
- Live solution review — demonstrate your solution, validate it together, and identify improvements.
- Application plan — define 1–2 tasks to automate immediately after the workshop.
What you will build hands-on
- Turn one real task from your role into a practical use case.
- Automate a standard report or data-export workflow yourself.
- Build an interactive dashboard with charts and filters.
- Validate the output on your data and correct issues with the trainer.
Program agenda
45 min
Introduction and goal settingVibe coding and the principles of effective AI work
30 min
Agent workflow reviewTurn your challenge into an individual use case
15 min
DemonstrationBuild a report generator and simple dashboard live
60 min
Hands-on buildBuild your tool with my support
60 min
Outcome reviewSolution demonstrations and peer learning
30 min
How to apply the capability nextAdoption plan: 1–2 tasks after the workshop
What to bring: a laptop, an approved AI-service account, and the required secure-access setup. It is best to identify a candidate task in advance.
You will leave with
A working AI toolbuilt by you for your own challenge
Independent automation capabilitywithout relying on IT or external contractors for standard scenarios
A process automation shortlistand a plan for the first 1–2 steps
A clear view of where AI saves time and creates valuestarting this week
Outcome
Move from uncertainty about the right use case to a working prototype and a practical application plan.
Who it is for
Discuss a workshop for your team →
Business owners, senior executives, and leaders in sales, projects, and finance who work with reports and spreadsheets and want to reduce routine work.
Advanced Vibe Coding Practicum
Advanced Vibe Coding Practicum
The next step for participants who have completed the foundation module. Develop the tool for repeatable use and transfer to colleagues: a usable interface, file handling, export, and a straightforward launch process.
Does this sound familiar?
- You built the tool during the workshop, but only you can use it—and non-standard data breaks it.
- Each run requires explaining the task to the AI from scratch.
- Colleagues can view the output but cannot reproduce it.
What is included
- Interface and usability — add forms, guidance, and input validation so the tool can be used by colleagues.
- File upload and export — generate Excel, PDF, and HTML output in one click.
- Charts and summaries — turn raw data into a clear management view.
- Error handling — handle missing columns, mixed formats, empty rows, and other imperfect data.
- Repeatable workflow — package the solution so it can run without being rebuilt each time.
- Documentation — create a concise one-page user guide.
What you will build hands-on
- Improve the tool from the foundation workshop—or build a new one.
- Test it on imperfect data and correct the failures.
- Package the solution and write a guide for colleagues.
You will leave with
- A mature mini-product for your own work.
- A prompt set and concise user guide.
- A repeatable method for turning rough prototypes into usable tools.
Outcome
Leave with a mature mini-product that the function can use—not an unfinished draft.
Who it is for
Discuss this program for your team →
Participants who completed the foundation workshop and want to turn a rough tool into a usable product.
AI-Enabled Management Decision-Making
AI-Enabled Management Decision-Making
For an executive, AI is not merely a faster spreadsheet. It supports management workflows: see the full picture sooner, identify risk earlier, and prepare decisions from data rather than intuition and memory.
Does this sound familiar?
- The business picture arrives at the end of the week—after decisions are already due.
- Reports arrive on time, yet risks only become visible in hindsight.
- Meetings generate pages of notes while decisions and actions get lost.
What is included
- Weekly report automation — turn sales, finance, or project exports into management summaries in minutes.
- Variance and risk detection — identify anomalies before they become operational problems.
- Management briefs — summarize meetings, reports, and negotiations into key points, decisions, and actions.
- Email and task analysis — extract the substance from long threads and prepare response drafts.
- Executive digital assistant — build a personal workflow set for your role and responsibilities.
What you will build hands-on
- Automate one of your recurring management reports.
- Configure variance detection using your own or demonstration data.
- Build a meeting → brief → actions workflow.
You will leave with
- A set of AI-enabled management workflows for your role.
- A working report or management-brief automation.
- Reusable prompts for recurring management work.
Outcome
A personal set of AI-enabled management workflows that helps you see the picture sooner and make decisions from data rather than memory.
Who it is for
Discuss this program for your team →
Leaders who want data-informed decisions and faster visibility without manual consolidation.
AI Adoption in a Business Unit
AI Adoption in a Business Unit
You have built a tool for yourself. The next challenge is scaling it across a function without creating a collection of disconnected personal chatbots. This program creates a structured adoption approach, an economic case, and an automation map.
Does this sound familiar?
- AI is already being used, yet the function still operates as before—the tool remains one person's side project.
- Everyone uses a different chatbot, with no shared rules or consistent outcome.
- It is unclear which processes to automate first or how to evaluate impact.
What is included
- Use-case discovery — identify functional processes suited to AI using criteria, a checklist, and examples.
- Economic impact — estimate the time, financial, and quality impact of automation.
- Task definition — define tasks for employees and AI agents and establish output acceptance rules.
- Automation map — create a functional map with 30-day priorities.
- Roles and accountability — clarify who sponsors, builds, and validates each solution.
What you will build hands-on
- Review your function's processes and identify 3–5 candidate use cases.
- Evaluate them using an impact / complexity matrix and select quick wins.
- Create a 30-day adoption map with owners and deadlines.
You will leave with
- A functional automation map.
- A prioritized list of AI initiatives.
- A ready-to-execute 30-day adoption plan.
Outcome
A practical one-month AI adoption plan for your function, with owners, deadlines, and expected impact.
Who it is for
Discuss this program for your team →
Functional and business-unit leaders accountable for bringing AI into team operations and delivering results.
Strategic Roadmap for Enterprise AI Adoption
Strategic Roadmap for Enterprise AI Adoption
An owner and executive-team program for building an enterprise pipeline from challenge → prototype → validation → adoption → operating standard, without depending on a single AI enthusiast. It also defines safety boundaries and the foundations of corporate AI policy.
Does this sound familiar?
- Everything related to AI depends on one enthusiast; if that person leaves, progress stops.
- There are no workable rules—only a total ban or uncontrolled use.
- Leaders are concerned about data leakage, hallucinations, and decisions with no accountable owner.
What is included
- Roles and accountability — define accountability for the business sponsor, AI operator, reviewer, IT, and security.
- AI initiative portfolio — select enterprise use cases using an impact / complexity matrix.
- AI Delivery Process — establish a challenge → prototype → validation → adoption → operating-standard pipeline.
- Prompt and solution library — retain organizational knowledge rather than losing it when people move on.
- Build internally vs engage vendors — determine what the business can prototype, what IT should own, and when vendors are appropriate.
- Safety and policy — define boundaries, data rules, output validation, and a draft corporate AI policy.
What you will build hands-on
- Design a compact AI Delivery Process for your company.
- Evaluate candidates and select the first 3–5 initiatives.
- Prepare a draft set of corporate AI-use rules.
You will leave with
- A compact AI Delivery Process model.
- A prioritized portfolio of AI initiatives.
- A draft corporate AI policy.
Outcome
Design a practical AI Delivery Process and operating rules so the company gains a repeatable solution pipeline rather than dependence on one individual.
Who it is for
Discuss this program for your team →
Business owners and senior executives building a systematic, enterprise-wide approach to AI.
04.2 · Program selection
Where to start
Start from your current maturity level—the programs form one coherent pathway.
04.3 · Program outcomes
A working result you can demonstrate to colleagues and develop further
Every program centers on hands-on work on the team's own challenge. The resulting prototype can be demonstrated to colleagues and incorporated into the next adoption plan.
- A tool for your challenge — built by you during the workshop rather than supplied as a generic demo.
- A lasting capability — learn a task → generation → validation method, not a single button.
- First-action plan — concrete steps for the first week after the workshop.
- Individual trainer support — review the team's challenges and help bring each solution to an outcome.
- Post-program support — ask questions and share results after the workshop.
- Clear boundaries — establish up front what AI can and cannot currently do.
05 · Pricing
Three levels of engagement for management teams
Pricing depends not only on duration but on the required outcome: introduce the team to the technology, build a connected solution set for a function, or define an enterprise adoption framework. The appropriate level is selected after a short needs assessment.
Hands-on intensive
1 day · team of 5–10
RUB 10,000–15,000per participant
For a first hands-on experience in which every participant builds one applicable solution.
- Program tailored to the team's priorities
- Working prototype for each participant's use case
- Outcome validation and safe-use rules
- Materials and templates for continued work
Team program
2–3 days · one function or business unit
RUB 20,000–30,000per participant
For a team that needs a connected solution portfolio and adoption plan rather than isolated experiments.
- Preliminary process and KPI assessment
- Multiple prototypes tailored to participant roles
- Functional automation map
- Priorities, owners, and a 30-day plan
- Post-program outcome review
Strategic engagement
assessment · strategy session · adoption architecture
On requestcustom proposal
For business owners and executive teams building an enterprise portfolio of AI initiatives.
- Interviews with key process owners
- Use-case portfolio and prioritization criteria
- Data, roles, IT, and information-security framework
- Pilot and scale-up roadmap
What is included
Preparation is included
Before the engagement, we define the expected program outcome—not a slide count. Scope, acceptance criteria, and budget are documented in the agreement.
- Scoping meeting with the client
- Cases tailored to the industry and participant roles
- Technology, data, and preparation checklist
- Hands-on work and feedback
- Team materials and templates
- Recommendations for next steps
05.1 · Completion commitment
The agreed prototype is brought to a working state
If a participant has not completed the agreed prototype by the end of the program, I provide an individual online session to help finish it at no additional charge. The prototype scope and completion criteria are agreed before hands-on work begins.
06 · Approach
What vibe coding is—and why it matters to executives
Andrej Karpathy coined the term “vibe coding” in 2025: you describe the task in natural language while an AI agent writes, runs, and checks the solution. For developers, it is a new way of working. For owners and senior executives, it is a way to produce in hours what once required weeks and a dedicated budget.
In the workshops, vibe coding is treated as a disciplined way of working: define the task clearly, move in small steps, and validate the output. You leave not with theory, but with a working tool for your own challenge—a report, dashboard, or routine automation.
“Do not delegate your understanding of AI. Try it yourself—otherwise you will not see where it can create economic value.” — Ruslan Gromov
01
Define the outcome instead of writing code
You describe the what and why in business language; AI turns it into a solution. The executive's key skill is precision in framing the task—not programming syntax.
02
Work on your own use case
No generic examples. You bring a real challenge—a report, process, or recurring task—and automate that exact piece of work.
03
Leave with a tangible outcome
By the end of the workshop, you have a working prototype and a clear next step. The value of vibe coding is determined by practical applicability and measurable operational impact.
07 · Learning format
Why the corporate program is in person and delivered in small groups
This is neither a webinar nor a lecture. Participants work hands-on from the first minute, with individual support throughout.
01
In-person format for a corporate team
The primary B2B format brings the team together in one room for rapid individual feedback and collective solution review. Separate online formats are available for learning providers.
02
Your team is the cohort
I train one team at a time: 5–10 people, each working on a challenge from their own role. A shared context makes the cases relevant and peer exchange immediately useful.
03
Live collaboration, not a lecture
Minimal slides, maximum practice. We review cases, validate intermediate outputs, and refine solutions together.
04
Practical value, not theory
You leave with a solution for your own challenge and a prioritized list of processes to automate next.
Who this format is for
For leaders accountable for adoption
The program is designed for one management team with a shared business context. Each participant works on an individual challenge while the group develops a common understanding of AI's capabilities and boundaries.
A strong fit
If you are ready to move from interest to action
- 01Business owners and senior executives
To understand the potential of AI tools first-hand and make informed adoption decisions.
- 02Functional and business-unit leaders
To identify automation opportunities within their function and lead implementation.
- 03Teams ready to build prototypes
To build a standard AI workflow independently and validate it on a real business task.
- 04Outcome-oriented leaders
To connect AI capabilities with time, process quality, risk, and economics.
08 · Applied scenarios
Projects that transform how a function or business unit operates
Coding agents make it possible to move beyond chatbots and simple reports. During the program, the team designs the architecture and builds a working prototype; integrations, production deployment, and scaling are defined as separate roadmap steps.
Manufacturing · CEO / COO
Digital production control center
- Context
- Orders, line utilization, downtime, shifts, and material availability are spread across different exports and systems.
- Prototype
- A team of AI agents consolidates the data, identifies constraints, models production-plan scenarios, and prepares a brief for the operations meeting.
- Value
- The executive sees not only the variance, but also its causes, response options, and the impact of each decision on order lead times.
Group of companies · CFO / treasury
Liquidity and covenant monitoring agent
- Context
- The payment calendar, bank statements, group-company budgets, and loan covenants are analyzed separately.
- Prototype
- The system forecasts cash gaps, checks contractual constraints, models payment rescheduling, and produces source-linked explanations.
- Value
- Treasury receives early warnings and response scenarios, while the CFO gets reproducible calculation logic for decision-making.
Retail · Chief Commercial Officer
Margin and assortment control center
- Context
- Sales, inventory, promotions, purchase prices, and competitor pricing do not provide a unified view of margin leakage by SKU and region.
- Prototype
- Agents identify stockouts and excess inventory, assess promotion impact, detect pricing anomalies, and propose actions.
- Value
- The commercial team receives a prioritized action list with expected impact, source data, and validation conditions.
HR / corporate university · CHRO
Skills map and internal mobility
- Context
- Role profiles, assessments, learning history, and project experience are stored in different formats and are difficult to compare.
- Prototype
- The system builds a skills graph, reveals gaps for target roles, identifies candidates for the internal talent pool, and creates development pathways.
- Value
- HR gains an explainable basis for succession and learning planning, with mandatory human review and access controls.
Procurement and legal · CPO / counsel
Contract and procurement risk control
- Context
- Hundreds of contracts, negotiation protocols, and tender documents must be checked against policies and standard terms.
- Prototype
- A RAG system compares terms, flags deviations, identifies related risks, and drafts comments with document citations.
- Value
- Experts can focus on non-standard risks, while every agent suggestion remains verifiable and subject to professional approval.
Regulated industry / public sector · Chief of Staff
Regulatory and correspondence navigator
- Context
- Regulations, directives, guidance, and prior correspondence have multiple versions, overlaps, and different access levels.
- Prototype
- A secure assistant finds the current rule, highlights changes, drafts a response, and attaches precise references to the underlying authority.
- Value
- Research and drafting time is reduced while source logs, version control, and final human accountability are preserved.
* These are solution-design scenarios, not claims of implementation for a specific client. Prototype scope depends on access, data quality, and information-security requirements; production integration is assessed separately.
09 · Questions and answers
Frequently asked questions
Our employees are not programmers. Can they do this?
Yes. The task → generation → validation workflow does not require coding: the task is defined in business language, the AI agent builds the solution, and the participant validates it. Even people whose previous toolset was limited to Excel build a working tool during the workshop. If someone does not complete the agreed prototype, the completion commitment applies.
Which AI services do you use, and are paid subscriptions required?
Services and access requirements are agreed in advance based on the team's objectives, corporate restrictions, and information-security requirements. Participants receive a preparation checklist before the program.
How do we arrange access to AI services for the team?
Before the workshop, we agree on the permitted tools and your security team's requirements. Corporate data is used only within the approved environment or in anonymized form.
What equipment is required?
Each participant needs an internet-connected laptop. The venue provides a projector or flip chart; all other requirements are covered in the preparation checklist sent in advance.
Can the program be tailored to our industry?
Yes. That is the purpose of the corporate format: the cohort is one team, so the cases, data, and examples are yours. I conduct a short needs assessment and tailor the program before delivery.
How safe is it to work with company data?
A dedicated module covers data boundaries: what may be sent to cloud models, what must be anonymized, and what should be processed locally. Participants receive a safety checklist. Where requirements are strict, we work with anonymized data.
How is this different from an online ChatGPT course?
The corporate program is built around one team's actual challenges: participants create a solution, receive feedback, and define an application plan. I use online formats separately for learning-provider projects and follow-up support.
How many people can participate?
The hands-on format is designed for a team of 5–10 people. I have facilitated groups of up to 80: for larger audiences, we separately agree on parallel cohorts or a blended format involving functional leaders.
What is included in the price?
Program preparation, workshop delivery, materials, a prompt library, and follow-up support. The final price is fixed in the agreement before work begins.
Is the workshop recorded?
The corporate program is designed around live practice, so its main value lies in in-room work and individual feedback. Participants receive written materials and templates; recording individual segments can be agreed with the client and participants in advance.
10 · Booking
Let us discuss your management team's challenge
STEP 1
Call or message — discuss the team's challenge and select the right program.
STEP 2
Select a date and city — agree on the in-person format, venue, and final budget.
STEP 3
Deliver the on-site program — participants build the agreed prototypes and plan the next adoption steps.
11 · Follow-up
The workshop is only the beginning
After the workshop, the team can handle standard tasks independently and reinforce the new practice. AI's greater value emerges in end-to-end projects: connecting data across systems, building multi-agent pipelines, or embedding a solution into a function's operating model. I take on such projects as an architect and implementation lead—from concept to working result.