Context Engineering Lab
Build reliable, scalable RAG workflows with proven practices and expert guidance.
2 hour workshop
on demand
for teams of 10-20
Our students work at
Why join the
the Context Engineering Lab
Who it’s for
> Backend & fullstack devs
> ML engineers & solution architects
> Platform teams building internal tools
> Engineers improving or maintaining RAG
> ML engineers & solution architects
> Platform teams building internal tools
> Engineers improving or maintaining RAG
What you’ll learn
> How to make RAG reliable & scalable
> Top mistakes and how to avoid them
> Hands-on RAG pipeline improvements
> A universal workflow for any RAG project
> Top mistakes and how to avoid them
> Hands-on RAG pipeline improvements
> A universal workflow for any RAG project
What you’ll achieve
> A reusable, battle-tested RAG workflow
> Faster fixes, fewer wasted iterations
> Reliable RAG adoption across products
> Faster fixes, fewer wasted iterations
> Reliable RAG adoption across products
Join hundreds of companies using
Hyperskill to upskill their teams
Workshop program
Context engineering
& goal setting
& goal setting
20 min
> What context engineering is and why it’s critical
> How to define measurable goals for a RAG project
> Baseline requirements: memory, metadata, multilingual capabilities, evaluation setup
Where it breaks
25 min
> Common failure points: flat text retrieval, missing evaluation, multilingual gaps, no guardrails
> Industry examples (Picnic, LinkedIn, DoorDash) and the metrics they improved
Live bot improvement
25 min
> Demo of the initial bot
> Context enrichment, Retrieval optimization, Human-in-the-loop integration, Knowledge graph for structured retrieval
> Measuring improvements at each stage
Mini-hackathon:
fixing the bot
fixing the bot
40 min
> Teams work on a pre-built repo (Docker-based)
> Implement improvements in retrieval, context processing, evaluation
> Compare results to target KPIs and discuss solutions
Generalization & scaling
15 min
> How to apply the same approach to any RAG system or domain
> Key considerations for deployment and maintenance
> Q&A
Upskill your teams like it's 2025
Teach the same way as 5 years ago
Add one perfunctory AI module
Made by corporations which are too rigid to embrace AI transformation
New content created from scratch and updated each launch
Prioritized market needs and latest tech developments
Made by AI-first company which uses AI in development tasks daily
Let’s talk about your team’s goals
Book a call & get a custom demo based on your needs
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Real results from real companies
Hyperskill makes you learn. It's not just re-typing code already given to you: you have to think. In six weeks of using it our team was writing more efficient code
AI feels like a bicycle for my mind now—helping me be more productive at work and in life. The course's weekend 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.
Hyperskill is an excellent tool to enable someone with no development experience to become a confident skilled software developer in the working environment. It was useful for lots of new starters in our team to enable them to learn on their own or with others of the same path.
Hyperskill is a very well-developed platform. Hands-on projects, supported with well-explained and developed theoretical material and unit tests, embedded in the browser, make coding interactive and fun.
The training from Hyperskill exceeded our expectations. Through hands-on projects, we gained practical experience integrating AI technologies into our work. We’ll definitely save time by automating some of our routine tasks.
Hyperskill is a motivating and playful way to encourage people to learn how to code. The combination of theory and practical exercises helps to enhance the learning experience. Hyperskill is a comfortable support for our trainers and a perfect way for future coders to make their first steps into the world of coding.
