Ship Faster Without Breaking Things
Your team can learn the AI development workflow that maintains code quality while dramatically accelerating delivery.
The Reality Most Teams Face
The business wants more results. Everyone's talking about AI. But your developers are telling you it's not good enough for production work.
Whenever they try, they get code that looks good initially but crumbles under edge cases, fails to meet non-functional requirements, and creates technical debt faster than it creates value.
The problem isn't the tool.
It's the workflow.
A Proven Methodology
DiPSy
We're using our AI-assisted development methodology on projects like the Czech Republic's nationwide high school admission system
If we can use it to develop nation-wide critical system, your team can use it, too.
This training shows your team the exact workflow we use: how to structure tasks, guide AI step-by-step, maintain architecture and code quality, and deliver reliable results regardless of your tech stack or security restrictions.
Quality First
Maintain architecture, testing, and non-functional requirements while AI accelerates implementation. No shortcuts, no technical debt.
Stack Agnostic
Works in Java, .NET, React, Python, Kotlin - any stack. Works in regulated environments, internal clouds, restricted tool access.
Mental Shift
Remove developer resistance by showing why past attempts failed and how to structure work so AI becomes an advantage.
What Your Team Will Learn
The AI Development Workflow
How to break down tasks, write effective prompts, guide AI through complex changes, review and iterate on output, navigate codebases, conduct AI-assisted research, and create production-ready pull requests.
Realistic Expectations
Using AI effectively means you might save 6 hours of implementation work but invest 3 hours learning to do it right. It can be frustrating at first, but you're still ahead - and getting better every time.
Practical Constraints
You have your security rules to maintain, regulatory requirements to uphold, and your own ideas about architecture quality. We'll show you how to build workflows that respect these constraints and create automated gatekeepers to ensure they're followed.
Live End-to-End Demo
Watch us go from ticket → implementation → pull request → review → deploy using AI on real production codebases, including the pitfalls and recovery strategies.
Who This Is For
Internal Champions
You see AI's potential but face team skepticism. You need validation and concrete practices to push the initiative forward within your organization.
Engineering Managers
Your team tried AI and gave up, or you're worried about code quality degradation. You need a proven methodology that maintains standards while accelerating delivery.
Regulated Teams
Banks, insurance companies, government agencies, healthcare - any team where security, compliance, and reliability are non-negotiable. This workflow respects those constraints.
No participant limits. With a 10-person team, that's €140 per developer - less than one day of development costs to unlock a workflow that will double their productivity this month.
Duration: 2-2.5 hours • Format: Live presentation with Q&A • Delivery: Remote or on-site
Prompt Library
Our internal prompt templates used daily on production projects.
Workflow Templates
Task breakdown structures, PRD templates, and review checklists.
Optional Recording
Full session recording (excluding confidential sections) for team reference.
14-Day Follow-Up
Email support for questions as your team starts implementing.
Off-Record Section Included
We'll also show you how we use AI to run our business - something we don't do on camera because we want freedom to discuss even sensitive use cases without worrying about public exposure.
Give Your Team the Workflow That Actually Works
AI gets better every day. Right now is the worst it will ever be - which means getting ahead now compounds over time. If your team isn't using AI effectively, competitors who are will outpace you.