Introduction: Why AI Pair Programming is Different in 2026
1. Integrate Security Checks from the Start with Mantis
Google has open-sourced Mantis, a modular toolkit that enables coding agents to autonomously find, reproduce, and fix vulnerabilities. For pair programming, this means you can ask the AI not only to generate code but also to perform real-time security reviews.
Example Prompt
Generate a function that retrieves user data, then run Mantis security checks on it. Highlight any common vulnerabilities such as SQL injection, XSS, and authorization issues.Key Points
- Provide the security framework context (e.g., project policies) before generating code.
- Use Mantis modules as separate tools:
scan-vulnerabilities,patch-suggestion,validate-fix. - Document each security alert for the team, maintaining a history of changes.
2. Extract Metadata from Documents with Agentic Document Extraction Gen2
LandingAI has released Agentic Document Extraction Gen2, built on DPT-3 models. This technology can extract tables, legal clauses, and technical specifications directly from PDFs, feeding pair programming with up-to-date information.
Example Workflow
# Upload the API spec.pdf document
# Extract endpoints and data types
specs = extract_document("spec.pdf")
# Generate an SDK client based on the extracted specifications
sdk_code = generate_sdk(specs)
# Run security checks with Mantis
scan_with_mantis(sdk_code)Benefits
- Reduces the time needed to analyze API documents.
- Keeps source code aligned with the latest documentation.
- Enables AI to suggest implementations that comply with extracted specifications.
3. Choose Domain-Specific Models: Samsung’s Case with Mistral AI
Samsung is implementing Mistral AI models on-premises for semiconductor design. For firmware development teams, this means a domain-specific base model can already understand register syntax, interrupt handling, and silicon-specific naming conventions.
Pro Tip
When working in a highly regulated domain, upload a sample of your internal code to the local Mistral AI model and ask the AI pair to suggest extensions that comply with these conventions.
4. Build Effective Prompts for AI Pair Programming
A good prompt does more than just ask "write a function." It should include context, constraints, and checkpoints.
# Prompt for a pair programming pipeline
# Role: AI pair programming assistant
# Context: We are developing a microservices authentication service in Go.
# Requirements:
# - Use PostgreSQL for storage.
# - Implement JWT token-based access.
# - Include security checks with Mantis.
# - Generate unit tests.
# Actions:
# 1. Write the service code.
# 2. Run Mantis security checks.
# 3. Generate tests.
# Format: Provide code in blocks separated by comments.
# Start generating.Essential Elements
- Role and Purpose
- Constraints
- Checkpoints
- Format
5. Practical Example: End-to-End Microservice Development
In this example, we’ll combine Mantis, document extraction, and a domain-specific base model to create a working authentication microservice.
Step 1: Extract Specifications
# Extract authentication contract specifications from auth-spec.pdf
spec = extract_document("auth-spec.pdf")
print(spec)Step 2: Generate Code with Built-In Security Checks
# Generate the authentication service
auth_service = generate_service(
language="go",
requirements=spec,
security_tools=["mantis"],
domain_model="mistral-samsung"
)
# Save the file
save(auth_service, "auth_service.go")Step 3: Run Security Checks
mantis_scan = run_mantis(auth_service, severity="high")
print(mantis_scan)Step 4: Write Unit Tests
tests = generate_tests(auth_service, framework="testify")
save(tests, "auth_service_test.go")This workflow reduces the development cycle from days to a few hours while maintaining rigorous security checks at every stage.
6. Common Mistakes and How to Avoid Them
- Prompts that are too generic.Always add domain-specific context and security constraints.
- Neglecting tool integration.Ensure the AI can reliably call external APIs (Mantis, extractor) as needed.
- Blindly trusting generated code.Always run security checks and tests before merging.
- Ignoring team conventions.Upload a representative sample of code to the local model to align style.
Conclusion: Transforming Pair Programming into the Primary Development Engine
Concrete Actions to Take Today
- Explore Google’s Mantis toolkit and integrate it with your IDE or code editor.
- Try document extraction with LandingAI on a project specification PDF to see how it can generate code.
- Set up a local instance of Mistral AI and upload your domain’s base code to improve suggestion relevance.
- Experiment with a structured prompt that includes context, constraints, and checkpoints.
- Define a formal review cycle that always includes a Mantis scan and AI-generated tests.
By adopting these best practices, your team will transform AI pair programming from an experiment into a strategic engine for faster, secure software development in 2026 and beyond.
IMPORTANT: It is 2026. All temporal references must be current. Do not mention past years like 2024, 2023, etc. The content must be fresh and relevant to the present. CURRENT CONTEXT (September 2026): Here are some recent trends and news stories to inspire you: - Google Open-Sources Mantis: A Modular Skills Toolkit That Lets Coding Agents Find, Reproduce and Patch Vulnerabilities: Google has open sourced Mantis, a stack-agnostic toolkit of security review skills for AI coding agents. It runs the full vulnerability lifecycle: swe... [2026-09-10] - NVIDIA Announces CUDA Rust with cuda-oxide (SIMT) and cutile-rs (Tile) for Compile-Time-Safe GPU Kernels: NVIDIA has announced CUDA Rust, a push to make Rust a first-class language for GPU kernels. Two open-source NVlabs projects cover the two CUDA program... [2026-09-08] - Coca-Cola uses AI to improve retailer ordering in Malaysia: Coca-Cola is using AI to recommend which products Malaysian retailers should order and in what quantities through its Coke Buddy platform. The Perfect... [2026-09-08] Use this current information as inspiration to create an original and relevant prompt for 2026.