Adding LLM Features to Your App
This workshop shows developers how to add language model features to an existing application in a robust way. You work through API integration, structured outputs, prompt management, error handling and evaluation. We also cover cost, latency, privacy and guardrails, so features stay reliable and accountable after the demo.
Request without obligation- Duration
- 1 day
- Level
- Intermediate
- Format
- Remote or on-site, English or German
- Group size
- Up to 12 participants per trainer
Who it is for
- Backend and full-stack developers adding AI features
- Tech leads planning LLM-based product features
- Product engineers moving from experiments to production
- Teams that must justify design decisions to security and data protection
What your team will be able to do
- Integrate an LLM API into an application with sensible error handling
- Request and validate structured output instead of free text
- Manage prompts as versioned, testable parts of the codebase
- Build a small evaluation set and use it to compare changes
- Control cost and latency through caching, model choice and limits
- Apply guardrails and privacy-conscious handling of user input
Agenda
- Architecture of LLM featuresLook at where model calls belong in your system and which failure modes to design for.
- First integrationImplement a call end to end, with timeouts, retries and streaming where useful.
- Structured output and validationDefine schemas, validate model output and handle invalid responses gracefully.
- EvaluationCreate test cases for a feature and measure how prompt or model changes affect quality.
- Cost, safety and privacyAdd limits and monitoring, discuss prompt injection and sensitive data, and agree on review practices.
Prerequisites
- Solid programming experience in at least one backend or web language
- Laptop with a development environment
- API access to a model provider (we align on the provider in advance)
Why apprat.io workshops
- Taught by practising AI Code Engineers
- Your repositories or a sandbox project
- AI speed, human responsibility: review, security and governance included
- ISO 9001 & ISO/IEC 27001 certified processes
- Follow-up office hours after 30 days
Request without obligation
Tell us about your team and goals. We reply within one business day with a tailored agenda and a quote – free and without obligation.
24/7 call support in English & German:
+49 761 519 751 50
Frequently asked questions
Which model provider is used?
We stay provider-neutral where possible and use the provider you prefer. Please tell us in advance so access can be prepared.
Do we cover fine-tuning?
No. The focus is on integrating and evaluating model features in applications, using prompting and application-side design.
Can we use our own codebase?
Yes. Working in a sandbox copy of your application is ideal and makes the results directly usable.
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