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World Congress 2024 • Aug 20, 2024 • Session details

GitHub Copilot Beyond the Basics - 10 Ways to Elevate Your Coding

lgonta , Yuliya Khadasevich

Stop treating GitHub Copilot as a glorified autocomplete. Discover ten advanced prompt engineering and context management techniques to automate tests, refactor bugs, and accelerate your development workflow.

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#1 about 3 min

Understanding GitHub Copilot and core developer benefits

Delegating repetitive tasks to an AI-powered code completion tool helps software engineers focus on generating business value.

#2 about 2 min

Requirements and licensing plans for GitHub Copilot

Getting started requires navigating individual, business, and enterprise subscriptions with varying privacy controls for training data.

#3 about 3 min

Processing code context securely through proxy servers

Information flows from IDE contexts through privacy filters to large language models without training on proprietary codebase data.

#4 about 1 min

Generative pre-trained transformer models powering code completions

Understanding the trade-offs between GPT-3.5 for fast completions and GPT-4 for advanced chat interactions clarifies ideal use cases.

#5 about 5 min

Leveraging auto-suggestions and context management in IDEs

Managing open tabs and utilizing slash commands ensures that completions accurately reflect existing codebase conventions.

#6 about 4 min

Streamlining unit and acceptance testing with AI

Generating test scenarios and behavior-driven setup scripts accelerates the test-driven development cycle for backend features.

#7 about 1 min

Troubleshooting exceptions and debugging code execution errors

Analyzing complex application logic and generating automated fixes helps operators resolve runtime crashes efficiently.

#8 about 1 min

Optimizing algorithms to improve runtime performance metrics

Replacing custom routines with native library patterns reduces execution time and prevents redundant programming efforts.

#9 about 1 min

Generating front-end user interfaces from backend models

Providing design instructions based on server-side logic automatically creates corresponding web forms and framework components.

#10 about 1 min

Automating interface test creation for frontend elements

Defining explicit framework requirements yields comprehensive assertions and end-to-end testing suites for new capabilities.

#11 about 3 min

Applying structured prompt engineering and reasoning methodologies

Feeding the model zero-shot, few-shot, and chain-of-thought examples yields higher fidelity results for complicated architectures like deployment pipelines.

#12 about 5 min

Demonstrating API method creation and test definition

Natural language instructions can scaffold controllers, implement test assertion libraries, and resolve console stack traces inside the editor.

#13 about 3 min

Refactoring mathematical operations to reduce execution time

Highlighting inefficient processes allows the system to suggest simplified logic for immediate computational speed bumps.

#14 about 3 min

Validating AI suggestions and avoiding over-reliance

Consistently evaluating generated output alongside continuous input refinement guarantees accurate application architectures.

Matching moments

4:37 min

Designing GitHub Copilot for developer flow

Krzystof Czieslak · LIVE

1:40 min

Adoption of integrated AI assistants in developer workflows

Julia Wilson Julia Wilson +1 · WWC 2025

51 sec

Impact of AI tools on developer collaboration

Brooke Gazdag Brooke Gazdag · Europe 2026 Virtual

1:46 min

Minimizing context switching with original GitHub Copilot

Krzysztof Cieślak Krzysztof Cieślak · WWC Europe 2026

1:10 min

Rolling out GitHub Copilot to thousands of developers

Katrin Lehmann Katrin Lehmann +1 · Coffee With Developers

3:16 min

Driving developer productivity with AI in automotive tech

Mike Butcher Mike Butcher +3 · WWC 2024

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