AI agents brought speed. Now the real question is control.
Before our services, let's understand the problem clearly.

Small feature
BEFORE
3 months
NOW
10 days
Medium MVP
BEFORE
6 months
NOW
20 days
Large build
BEFORE
1 year
NOW
1–2 months
NEW REALITY
AI agents can compress months of development work into weeks, sometimes even into
days.
Speed is now a real differentiator.
SPEED
Development is 20× faster
AI agents working across multiple directions simultaneously significantly accelerate delivery pace.
- Thousands of lines of code generated in a short time
- Parallel task execution becomes possible
- Prototyping and iteration speed up
RISK
Mistakes became 20× more dangerous
Every wrong requirement is instantly turned into thousands of lines of wrong code. Fixing is more expensive than writing.
- Requirement errors immediately become code
- Architecture drift grows uncontrolled
- Invisible system errors accumulate

A human focuses on 1–2 connections.
An AI agent sees hundreds of connections at once.
This difference is not just speed — it is a difference in thinking model. If product teams do not understand this, the AI agent remains uncontrolled.
That is why prompting must be structured so the agent can distinguish information coming from the system and intent coming from you — and analyze each accordingly.

“Developers do not need to compete with AI agents. They need to learn how to manage them.”
To get the right results from AI agents, 3 problems exist.
Seeing the big picture
Without Agentic System Thinking, managing an AI agent is not possible.
Communication
Structured, precise prompt language — communicating effectively with AI is a separate craft.
Control
Monitoring AI agent outputs — a powerful tool requires powerful management.
Seeing the big picture — communicating and managing with AI without it is a major risk.
Without Agentic System Thinking, communicating with an Agent and managing it without seeing the big picture of product management leads to very serious risks.
You do not need to be a composer to enjoy great music.
You do not need to be a chef to enjoy great food.
You do not need to think like an AI agent to manage AI agents.
Communication problem
Prompt language is a separate craft.
Without structured, precise prompt language, the AI agent executes your words, not your intent. This difference leads to critical outcomes.
About effective communication
“The single biggest problem in communication is the illusion that it has taken place.”
George Bernard Shaw
Playwright
Management problem
AI agent is a powerful tool.
Without control, the codebase shifts from the team's hands to the agent's. The developer is no longer managing the code — they become someone watching the agent's decisions.
Agentic System Thinking
What happens without it?
AI agent builds design connections on its own
The system diverges from existing architecture, uncontrolled design decisions emerge.
Modules are connected incorrectly
UI, API, DB don't work together — integration problems multiply.
Requirement-code alignment weakens
Written code does not meet real needs, rewriting costs increase.
Architecture drift occurs
The project deviates from its technical direction, long-term costs rise.
Codebase grows uncontrolled
Duplicate logic, messy structure, maintenance difficulty arises.
Prompt impact is not measured
Which file/task/API changed becomes invisible, impact cannot be tracked.
Jira/GitHub system becomes chaotic
Commit-task mismatches emerge, tracking becomes harder.
QA risk increases
Critical bugs are missed, test coverage gaps grow.
Developer ownership is lost
AI decides, developer is sidelined, responsibility becomes blurred.
Maintenance becomes difficult
Understanding and fixing the system gets harder over time.
Transformation
From chaos to AI-Ready team
Making a team AI-ready is not just about buying AI tools.
It means changing how the team thinks, manages, and delivers. The team moves from chaos to a structured dashboard.
KEY INSIGHT
Individual skills are no longer enough. In the AI era, teams must have holistic system thinking.
Puzzle pieces come together into one product system.
THE ONLY SOLUTION
We offer the only solution to these problems.
01 · METHODOLOGY
CaDPM™
Canvas-Driven Product Management — a shared language for PMs, engineers and business.
Why CaDPM™?02 · SYSTEM
DPS Open Source System
The system that applies the methodology to real work environments. Full AI Agent integration.
Explore DPS03 · TRAININGS
AI-Ready Practical Trainings
An online training program that gets your team to ready-to-start in 8–10 weeks.
For Companies: 3 Consultation Programs
We provide companies with 3 core consultation programs to make their teams AI-Ready, communicate effectively with AI agents, and adapt to modern product development trends through optimal management.
Agentic Product Managers Development Consultation Program
This program prepares Product Managers to work more effectively in the AI era and manage AI agents properly.
Program key components
- 1Product Manager assessment— 2 days
- 2Teaching «Agentic System Thinking» skills (individualized per participant)— 10 weeks
Agentic System Thinking structured courses available for teaching.
All courses are built on 1–4 hours of practical foundations. Tracked from start to finish.
User Story Canvas Development
Helps define what the user needs, why they need it, and how the requirement should be expressed clearly.
Business Canvas Development
Helps structure the business problem, customer need, value proposition, and expected business outcome.
Monetization Requirement Canvas Development
Helps define early monetization expectations, revenue logic, and business value behind the product idea.
Data Flow Canvas Development
Helps visualize how data moves between users, pages, systems, APIs, and databases.
UI Canvas Development
Helps design and describe product pages, UI components, user actions, and screen-level requirements.
Jira-type systems are not designed to work with AI agents.
DPS is built specifically for AI-powered delivery management. Plus, DPS is now open-source — no extra monthly fees needed.
Traditional systems (Jira etc.)
DPS System
PROBLEM
Existing systems were not built
for the AI era.
Neither task management systems nor methodologies are enough to manage projects with AI agents at speed.
Jira & Trello
Task managementDoes not teach teams how to think, how to communicate with AI agents, or how to measure delivery.
Scrum / Kanban / PMI / IIBA
MethodologyProvides methodology and approach, but no unified system to apply them in an AI-powered real work environment.
As a result, a new chaos has emerged in companies: AI agents increase speed, but control over product delivery weakens.
DPS — manages projects by numbers
Designed for AI prompting in task and project management. Shows delivery in measurable form.
Estimated code lines
12,400
Completed code lines
8,730
Remaining code lines
3,670
Estimated finish date
2025-08-14
Req-code alignment rate
94.2%
INDIVIDUAL GROWTH PATH
Assessment & Growth Path
A personalized growth path built on individual assessment for each participant — every step is measured, tracked, and delivers results.
LXP Platform
Each participant takes an individual assessment across 20 skills
Each participant's current level is measured separately across 20 practical skills. Results are shown as percentages and strengths and weaknesses are clearly identified for each skill.
Measure your team's progress for the first time — for real
Assessment · Individual Growth Path · Daily tracking · Lesson-based performance — all on one platform, in real time.
EXPLORE THE PLATFORM
Learning Experience Platform
AI-powered learning platform — every lesson, every assignment, every skill tracked in real time. Learners see their daily lesson plan, while the company monitors the entire team's progress on one screen.
Individual learning path
Each participant receives a personalized Growth Path based on their assessment results.
Application-based lessons
Each lesson consists of video + canvas assignment — watching alone is not enough.
Real-time tracking
Daily, monthly and skill-based performance is visible to the company.
Company dashboard
All team progress on one screen — lagging participants are immediately visible.
Learning Platform — Questions
Questions arising during lessons are asked and answered directly on the platform.
HOW IT WORKS
Format, duration and pricing
Online format, multilingual
Online program available in multiple languages. Not just reading materials — video subtitles and voiceovers are also provided in those languages.
2 hours per day
Learning is possible with 10 hours per week. This does not interfere with daily work and is easy to apply.
8–10 weeks
8–10 weeks is sufficient for 1 person. Each skill is structured so it can be completed in a short time alongside practical application.
LXP Platform
Both theoretical and practical application is provided on the Learning Experience Platform for each sub-skill.
CONTACT
Prepare Your Team for the AI Era
Our consultant will contact you directly, answer all your questions and send pricing information.
Contact for consultation
Get detailed information about the program
Contact for demo course
View demo online courses before starting the consultation program
Team assessment contact
Measure your team's current level based on 20 skills
Online exam assessment
Online exam-based evaluation for your team
ARTICLES
Related Articles

Agentic MVP Development Starts With Structured Product Communication

How Will the Product Manager of the Future Manage AI Agents?

What Is DPS System?

What Is Prompting and How Do You Write the Right Prompt?

What Is Agentic System Thinking?
