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AI Training for Teams

Your team has access to AI. Do they know how to use it?

We run hands-on AI training for engineering, product, and executive teams - built around your stack, your use cases, and the actual problems your team faces.

Training by role

Engineers
Hands-on
LLM API integration
Prompt engineering at scale
Fine-tuning & RAG patterns
Evaluation frameworks
Building with agents
Product Managers
Applied
AI feature design
Evaluation & quality metrics
AI product roadmapping
Working with AI engineering teams
Risk & limitation awareness
Executives
Strategic
AI ROI frameworks
Risk & governance
Vendor assessment
Build vs. buy decisions
Communicating AI to stakeholders

Workshop formats

Half-day intro
4 hours
Who: Any team
AI fundamentals, use case identification, live demos and discussion.
Full-day deep dive
8 hours
Who: Engineers or PMs
Hands-on labs, API integration, prompt design, and evaluation techniques.
Multi-day bootcamp
2–3 days
Who: Cross-functional teams
End-to-end AI product skills: strategy, design, engineering, and evaluation.
Ongoing monthly sessions
Monthly half-days
Who: Any team
Keeping pace with fast-moving AI landscape; new model capabilities, tools, and patterns.

What we teach

Prompt engineering
Structured prompting, chain-of-thought, few-shot, and system prompt design.
LLM APIs & models
Model selection, cost management, latency trade-offs, and provider comparison.
AI product design
Designing AI features with appropriate UX, feedback loops, and fallbacks.
Evaluations & testing
Building eval frameworks that measure what matters for your specific use case.
AI safety & risk
Hallucination, bias, PII risks, and building responsible AI workflows.
Building with agents
Agentic patterns, tool use, orchestration, and when agents are the right answer.

Custom curriculum

We don't run generic AI courses

Off-the-shelf AI training teaches people about AI in the abstract. We teach people how to use AI in your specific context - your stack, your product domain, your team's actual skill gaps. Everything is built fresh for each engagement.

The customisation process
Pre-workshop survey to understand team skill level and gaps
Domain research - we learn your product area before we teach
Custom labs built on your actual stack and tools
Use case selection based on your roadmap, not our templates
Post-workshop follow-up to embed learning in real work

Outcomes

01
Spec AI features
Teams that can write clear, testable specs for AI-powered product features.
02
Identify AI opportunities
People who can spot where AI adds real value - and where it doesn't.
03
Evaluate AI vendors
Structured evaluation skills for comparing models, tools, and providers.
04
Build basic AI prototypes
Engineers who can take an AI idea to a working prototype without hand-holding.

Past participants

"Exactly what we needed - no generic content, everything was tied to our stack and our product. The team shipped their first AI feature the week after."
VP of Engineering, B2B SaaS
"Our product team went from 'AI is scary' to pitching AI features in sprint planning. That shift happened in one day."
CPO, Fintech startup
Impact by the numbers
1 day

Average time for a product team to go from AI-hesitant to pitching AI features in sprint planning

94%

Of workshop participants rate the training as 'directly applicable' to their current work

3×

Increase in AI-related tickets shipped in the 30 days after an engineering bootcamp

100%

Custom curriculum per engagement - no off-the-shelf slides, ever

Engagement model

How a training engagement works

01
Intake survey

We survey every participant to understand skill level, current AI usage, and what they most want to learn.

02
Curriculum design

We build custom labs, slides, and exercises based on your stack and the specific AI problems your team faces.

03
Live workshop

Hands-on, interactive session - not a lecture. Teams work through real problems in your product domain.

04
Follow-up & embed

Post-workshop resources, a Slack channel for 30 days, and an optional follow-up session to embed learning.

A different approach

Generic AI training vs. ours

Generic courses
✕

Pre-recorded videos with no interaction

✕

Uses examples from unrelated industries

✕

Teaches ChatGPT tricks, not engineering patterns

✕

Same material for engineers and executives

✕

No follow-up once the course ends

StartxLabs training
✓

Live, hands-on workshops tailored to your team

✓

Labs built on your actual stack and product domain

✓

Real engineering patterns: APIs, evals, RAG, agents

✓

Role-specific tracks for engineers, PMs, and execs

✓

30-day async follow-up to embed learning in real work

Topics & tools covered

What your team walks away knowing

Models & APIs
GPT-4oClaude 3.5GeminiMistralOpenAI APIAnthropic APIModel routingCost estimation
Prompting & evaluation
System promptsChain-of-thoughtFew-shot examplesLLM-as-judgeEvals frameworksA/B prompt testingHallucination mitigation
Engineering patterns
RAGFine-tuningFunction callingStructured outputsStreamingEmbeddingsVector storesAgents
Product & strategy
AI feature designBuild vs. buyRisk & governanceROI frameworksUser trust patternsFallback UX

Ready to build your
next digital product?

Whether you have a detailed specification or just an early idea - we'll help you scope it, challenge the assumptions, and deliver it on time. No pitch decks. Straight to the point.

Get in TouchSee Our Work

What happens next

1

Send us a message

Tell us what you're building or what's broken.

2

Discovery call (30 min)

We ask hard questions. You get honest answers.

3

Scoped proposal

Clear deliverables, timeline, and team in 48 hours.

Contact Us

Tell us about
your project

Whether you have a detailed brief or just an early idea, we will help you scope it, challenge it, and ship it.

  • Agentic AI development and multi-agent systems
  • Generative AI consulting and LLM integration
  • RAG development and custom model deployment
  • Data engineering, MLOps and custom software
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