AI Agentic Software Development

Focused workshops for engineering teams who want to transform LLMs from coding assistants into autonomous development partners
UP TO 7 workshops
2 hours live + 2-day support
Leave your email to discuss the workshops for your team in Q1'2026
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Partnering with the best

> Creators of most popular professional dev tools
> Trusted by 11.4m developers worldwide
> Engineers at Tesla, X, Google, Visa, and Valve rely on JetBrains tools

Join hundreds of companies using Hyperskill to upskill their teams

Traditional approach vs. AI-first approach in software engineering

Your team writes code, AI assists

Engineer writes most code manually
AI provides autocomplete suggestions
Copilot helps with boilerplate snippets
Focus: Writing and debugging code
Engineer reviews AI suggestions line-by-line
Speed: Incremental productivity gains (10-30%)

AI generates code, your team designs specs

AI agents write entire features autonomously
Engineer creates precise specifications
Agents handle implementation, testing, deployment
Focus: Architecture and business logic
Engineer reviews complete features and system behavior
Speed: deliver features up to 5 times faster

Pick workshops that fit your goals

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Agent Architecture & Levels of Autonomy
Why This Workshop:
Understanding how autonomous coding agents operate their components, memory systems, tool access, and control boundaries is essential for predicting their behavior and integrating them safely into your development workflow. This workshop demystifies agent architecture so you can make informed decisions about autonomy levels.
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Perfect For:
‍Technical leads and senior engineers who need to evaluate AI coding tools, set appropriate autonomy boundaries and design team workflows that leverage autonomous agents effectively.
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What You'll Create:
> Architecture diagrams mapping agent components and data flows
> Autonomy model defining safe control levels for your team 
> Control map showing where humans review vs. agents decide‍
Tools:
Architecture diagrams, decision frameworks‍
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Coding Workflow Patterns
Why This Workshop:
Ad-hoc prompting leads to inconsistent results. Professional AI-First Coding requires structured workflows, sequential generation, spec-first development, supervised refinement cycles and structured code reviews. Learn the patterns that make autonomous coding predictable and reliable.
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Perfect For:
‍Engineering teams transitioning from manual coding to AI-assisted workflows who need repeatable patterns that ensure quality and consistency across projects.
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What You'll Create:
> Pattern-based workflow diagram for your team's coding process
> Workflow templates for common development scenarios 
> Multi-step automation sequences that agents execute reliably‍
Tools:
Workflow templates, n8n, process documentation‍
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Applications Built by AI
Why This Workshop:
Most engineers experiment with AI coding tools but never ship production applications built entirely by autonomous agents. This workshop takes you from prompting to production—building a complete microservice where AI handles the entire development cycle.
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Perfect For:
‍Software engineers with 2+ years experience who want to practice orchestrating AI agents to generate, review, and deploy production-ready code.
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What You'll Build:
> Working microservice generated entirely by AI from your specifications
> End-to-end workflow: specify → generate → review → refine → deploy 
> Practical experience delegating real coding tasks to autonomous agents‍
Tools:
Claude Code, GitHub, REST APIs‍
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Specification & Context Engineering
Why This Workshop:
The quality of AI-generated code depends entirely on specification quality. Software engineers need to shift from writing code to writing precise, context-rich specifications that guide AI to produce production-grade results consistently.
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Perfect For:
‍Engineers who want to master the core skill of AI-First Coding: transforming business requirements into specifications that autonomous agents can execute reliably.
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Your key takeaways from this workshop:
> Technical specifications that produce consistent, high-quality AI output
> Context injection to align with your existing codebase
> How to validate AI-generated code against requirements systematically
> How to create reusable spec templates for your team‍
Tools:
Claude Code, Notion/Quivr‍
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Improving Code Generation Using Feedback & Codebase Patterns
Why This Workshop:
AI agents improve over time when they learn from your codebase patterns, review history, and team conventions. This workshop teaches you to extract patterns from existing code, encode team knowledge into specs and prompts, and create feedback loops that make autonomous developers better with each generation.
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Perfect For:
‍Engineering teams who want their AI coding tools to learn and adapt to their specific codebase style, architectural patterns, and quality standards over time.
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What You'll Create:
> System blueprint for continuous improvement of AI code generation
> Pattern extraction from your codebase for future generations
> Feedback mechanisms that refine agent behavior over time‍
Tools:
Git history, diff tools, Claude Code, pattern analysis tools‍
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Controlling the Quality of Code Generated by AI
Why This Workshop:
Shipping AI-generated code to production requires the same quality standards as human-written code but with different testing strategies. Learn to build automated quality gates specifically designed for AI-generated outputs.
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Perfect For:
‍Engineers responsible for code quality who need systematic approaches to validate, test, and maintain AI-generated codebases at scale.
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What You'll Create:
> Automated testing pipelines for AI-generated code
> LLM-as-judge evaluation frameworks
> Golden test sets for regression testing
> Quality gates integrated into CI/CD workflows‍
Tools:
pytest, GitHub Actions, AI-based code checkers, linters, type checkers‍
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Secure Integrations & Tool Access
Why This Workshop:
AI agents need access to real infrastructure—APIs, databases, CI/CD pipelines—to build and deploy applications. But giving AI systems broad access creates security risks. Learn how to connect AI agents to production tools safely using least-privilege principles, secrets management, and proper sandboxing.
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Perfect For:
‍DevOps engineers and security-conscious developers who need to integrate AI agents with production infrastructure without compromising security or creating vulnerabilities.
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What You'll Do:
> Connect AI agents to external services with proper authentication and rate limiting
> Grant AI systems minimal necessary permissions with full audit logging
> Allow AI agents to trigger deployments safely with approval gates
Tools:
Claude Skills SDK, Vault, SPIFFE, IAM policies, sandboxing frameworks

Workshops structure

Live Session
2 hours
- 15 min: Context and real-world use cases
- 40 min: Live demonstration with production examples
- 55 min: Guided hands-on practice with your own code
- 10 min: Next steps and async work assignment
Async Support
48 hours
- Continue building on your own schedule
- Submit solution for expert review
- Get answers to specific implementation questions
- Access step-by-step guides and templates
- Join group discussions with other participants
Post-Workshop
- Keep all recordings and materials permanently
- Access to workshop-specific Discord channel
- Reusable templates and checklists for your team

Why Hyperskill Training works

Direct access to instructors
Instructors who've built real products and explain complex concepts clearly will help you grow fast.
Built around industry needs
Workshops materials adapted to innovative market goals.
AI workshops from industry leaders
Participate in practical workshops where you'll learn to use the same AI coding tools professionals rely on to build more efficiently and effectively.
Production-focused curriculum
Every workshop builds something you can deploy immediately.
Hands-on code review
Get your AI-generated code reviewed by practitioners who've shipped AI-driven products.
48-hour expert support
Continue working after the live session with direct access to instructors for code review, debugging, and architecture questions.

Let’s talk about your team’s  goals

Leave your email to discuss the workshops for your team in Q1'2026
Thank you! We will contact you in the next 24 hours.
Oops! Something went wrong while submitting the form.

What our students say

AI helps me be more productive at work and in life. Deep-dives into new concepts were fantastic, and I even created a project that could help JetBrains PMs make better decisions. Those who embrace AI will have a clear advantage moving forward.
Anastasiia
QA Lead, JetBrains
I like the material; it is a great chance to familiarize myself with AI tools. The proportion between Math and non-math tasks is just right. I also enjoy practical projects and exercises. Community helps with my questions and supports my motivation.
Avraham
Full Stack Developer
If I just needed a single project, I could hire a freelancer. But this is different. AI, especially LLMs, will be part of software development for a long time. <...>
You learn from people who’ve done it before, that’s what made studies meaningful.
Cezar
Chief Technical Officer
I feel confident and appreciate how AI Engineer program is structured: it gives truly practical knowledge. As someone project-oriented, I see this training as a way to fill my gaps, and I really admire what JetBrains and Hyperskill are building with their programs.
Lyubomir
Solo Entrepreneur

Frequently asked questions

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Can our team take individual workshops or do I need the full series?

Each workshop is standalone. Take all of them for the complete journey from methodology to production, or choose specific workshops based on your current needs.

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What if I can't attend the live session?

Live attendance is essential: these are hands-on workshops, not recorded lectures. The majority of time is spent in small group practice sessions with real-time instructor support. Recordings cover the main demonstrations, but miss the collaborative work that creates the learning breakthroughs. If your schedule doesn't allow live participation, we recommend choosing a different workshop date.

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What tools do I need access to?

GitHub account, Claude Code and basic cloud access. Detailed setup guide provided to a team after registration.

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Is this suitable for senior developers?

Sure! The workshops assume professional development experience and focus on production-grade engineering practices, not beginner concepts.

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