7 min read
Eight Prompt Engineering Myths to Drop in 2026
Eight prompt engineering myths worth dropping in 2026, from verbose prompts to reflexive chain-of-thought and temperature rules, and what to measure instead.
Best Practices
122 articles
1 min read
Preparing Your Codebase for 2026: A Technical Debt Audit Guide
Technical debt compounds like financial debt. Regular audits and systematic paydown keep your codebase healthy and your team productive.
1 min read
API Design Patterns That Stood the Test of Time in 2025
Good API design is timeless. These patterns work because they prioritize developer experience and operational reliability.
1 min read
Infrastructure as Code Best Practices: Lessons from 100+ Deployments
IaC is a skill that compounds. These practices become second nature and save countless hours of debugging and recovery.
1 min read
Winter Solstice Code Review: My Most Impactful Refactors of 2025
On the longest night of the year, let's reflect on code improvements. Here are the refactoring patterns that delivered the biggest impact in my projects…
1 min read
The Ultimate Azure Cost Optimization Checklist for 2026
Start the new year with optimized cloud spend. These changes compound over time into significant savings.
1 min read
Securing AI Applications: A Comprehensive 2025 Checklist
AI security is not optional. Implement these measures before going to production, and review them quarterly as threats evolve.
1 min read
Performance Optimization for .NET 9 Applications on Azure
Results: Cold start reduced from 800ms to 150ms. These optimizations combined typically reduce Azure compute costs by 30-50% while improving response times.…
1 min read
Building Production RAG Systems: Best Practices for 2026
Production RAG is iterative. Start simple, measure everything, and improve based on real user feedback.
1 min read
Building Data Lakehouses: Medallion Architecture Best Practices
Each layer serves a specific purpose in the data refinement pipeline. Bronze captures raw data, silver cleans and conforms it, and gold delivers…
1 min read
Securing AI Applications: Authentication and Authorization Patterns
AI applications face unique security concerns: protecting training data, controlling model access, securing inference endpoints, and preventing prompt…
1 min read
Prompt Engineering Patterns for Enterprise RAG Systems
Poorly designed prompts lead to hallucinations, ignored context, or responses that fail to meet business requirements. A systematic approach to prompt…
1 min read
Prompt Engineering Patterns for Enterprise Applications
Include examples in prompts to guide model behavior for domain-specific tasks. This is especially effective for classification and formatting tasks where…
1 min read
September 2025 Recap: Key Takeaways for Enterprise AI
The most successful AI implementations share common architectural patterns. Hybrid search combining vector and keyword retrieval consistently outperforms…
1 min read
Prompt Injection Defense: Securing LLM Applications
Prompt injection occurs when user input is interpreted as instructions rather than data. Attackers can attempt to override system prompts, extract…
1 min read
Prompt Engineering: System Prompts That Actually Work
Invest time in crafting and testing your system prompts. They are the foundation of consistent, high-quality AI interactions.
1 min read
Prompt Engineering: Chain-of-Thought Techniques for Complex Reasoning
When faced with multi-step problems, LLMs perform better when prompted to reason step-by-step rather than jump directly to answers.
1 min read
Prompt Engineering Best Practices for Enterprise Applications
A well-structured prompt includes context, instructions, examples, and output format specifications.
1 min read
June Recap: Building Modern AI Systems
Understanding june recap is essential for production AI systems. Here's what you need to know.
1 min read
Data Lineage: Building Modern AI Systems
Understanding data lineage is essential for production AI systems. Here's what you need to know.
1 min read
Metadata Management: Building Modern AI Systems
Understanding metadata management is essential for production AI systems. Here's what you need to know.
1 min read
Data Governance: Building Modern AI Systems
Understanding data governance is essential for production AI systems. Here's what you need to know.
1 min read
Unity Catalog: Building Modern AI Systems
Understanding unity catalog is essential for production AI systems. Here's what you need to know.
1 min read
Iceberg Ai: Building Modern AI Systems
Understanding iceberg ai is essential for production AI systems. Here's what you need to know.
1 min read
Delta Lake Ai: Building Modern AI Systems
Understanding delta lake ai is essential for production AI systems. Here's what you need to know.
1 min read
Data Lakehouse Ai: Building Modern AI Systems
Understanding data lakehouse ai is essential for production AI systems. Here's what you need to know.
1 min read
Batch Processing: Building Modern AI Systems
Understanding batch processing is essential for production AI systems. Here's what you need to know.
1 min read
Caching Strategies: Building Modern AI Systems
Understanding caching strategies is essential for production AI systems. Here's what you need to know.
1 min read
Load Balancing Ai: Building Modern AI Systems
Understanding load balancing ai is essential for production AI systems. Here's what you need to know.
1 min read
Model Serving: Building Modern AI Systems
Understanding model serving is essential for production AI systems. Here's what you need to know.
1 min read
Gpu Optimization: Building Modern AI Systems
Understanding gpu optimization is essential for production AI systems. Here's what you need to know.
1 min read
Kubernetes Ai: Building Modern AI Systems
Understanding kubernetes ai is essential for production AI systems. Here's what you need to know.
1 min read
Container Apps Ai: Building Modern AI Systems
Understanding container apps ai is essential for production AI systems. Here's what you need to know.
1 min read
Durable Functions Ai: Building Modern AI Systems
Understanding durable functions ai is essential for production AI systems. Here's what you need to know.
1 min read
Azure Functions Ai: Building Modern AI Systems
Understanding azure functions ai is essential for production AI systems. Here's what you need to know.
1 min read
Serverless Ai: Building Modern AI Systems
Understanding serverless ai is essential for production AI systems. Here's what you need to know.
1 min read
Azure Event Grid Ai: Building Modern AI Systems
Understanding azure event grid ai is essential for production AI systems. Here's what you need to know.
1 min read
Kafka Ai: Building Modern AI Systems
Understanding kafka ai is essential for production AI systems. Here's what you need to know.
1 min read
Event Driven Ai: Building Modern AI Systems
Understanding event driven ai is essential for production AI systems. Here's what you need to know.
1 min read
Websocket Ai: Building Modern AI Systems
Understanding websocket ai is essential for production AI systems. Here's what you need to know.
1 min read
Streaming Inference: Building Modern AI Systems
Understanding streaming inference is essential for production AI systems. Here's what you need to know.
1 min read
Real Time Ai: Building Modern AI Systems
Understanding real time ai is essential for production AI systems. Here's what you need to know.
1 min read
AI Documentation: Documenting AI Systems Effectively
{promptconfig['template']} Comprehensive documentation ensures AI systems remain maintainable and understandable.
1 min read
AI Team Collaboration: Building Effective AI Development Teams
Effective AI teams combine diverse skills with clear collaboration patterns.
1 min read
AI Debugging Techniques: Diagnosing AI System Issues
Systematic debugging enables quick identification and resolution of AI issues.
1 min read
AI Testing Frameworks: Comprehensive Testing for AI Systems
Comprehensive AI testing ensures reliable behavior across diverse scenarios.
1 min read
Incident Response for AI Systems: Handling AI Failures
Effective incident response minimizes AI system impact and enables quick recovery.
1 min read
Model Versioning: Managing AI Model Lifecycle
Robust model versioning enables confident deployments and quick rollbacks.
1 min read
Prompt Management: Version Control for AI Instructions
Effective prompt management enables reliable AI applications with traceable changes.
1 min read
AI Security Best Practices: Protecting AI Systems
Comprehensive security protects AI systems from emerging threats.
1 min read
Responsible AI Practices: Implementing Ethical AI
Responsible AI practices build trust and ensure ethical AI deployment.
1 min read
AI Cost Optimization: Managing LLM Expenses
Strategic cost optimization can reduce AI expenses by 50-80% while maintaining quality.
1 min read
A/B Testing AI Features: Data-Driven AI Improvements
Rigorous experimentation enables confident AI improvements based on real user impact.
1 min read
Evaluation Metrics for AI: Measuring What Matters
Regular evaluation with consistent metrics drives continuous improvement in AI quality.
1 min read
Prompt Injection Defense: Protecting AI Applications
Defense in depth with multiple layers provides the best protection against prompt injection.
1 min read
Guardrails for LLMs: Building Safe AI Applications
Comprehensive guardrails are essential for responsible AI deployment.
1 min read
Structured Outputs: Getting Reliable Data from LLMs
Structured outputs enable reliable integration of LLM capabilities into data pipelines.
1 min read
Function Calling Patterns: Building Reliable AI Tools
Well-designed function calling creates powerful AI applications that interact safely with real systems.
1 min read
Context Window Management: Maximizing LLM Effectiveness
Strategic context management enables handling of complex, long-context scenarios.
1 min read
Chunking Strategies for RAG: Finding the Right Granularity
Choose chunking strategy based on document structure and retrieval requirements.
1 min read
AI-Powered Documentation: Keeping Docs in Sync with Code
AI-generated documentation reduces maintenance burden while improving quality.
1 min read
Testing AI Applications: Strategies for Non-Deterministic Systems
Robust AI testing combines deterministic checks with AI-powered evaluation.
1 min read
AI-Assisted Data Modeling: Accelerating Schema Design
AI-assisted modeling reduces design time while improving schema quality.
9 min read
Azure OpenAI in Production, January 2025: Let the Platform Do the Work
Deployment types, keyless auth, SDK retries, APIM token limits and Global Batch: what to build on Azure OpenAI in January 2025, and what to stop building.
1 min read
MLOps Maturity: Productionizing Machine Learning
MLOps is essential for sustainable ML in production. Start with experiment tracking and gradually add components as your ML practice matures.
1 min read
DataOps Maturity: Building Reliable Data Operations
DataOps maturity directly impacts data reliability and team productivity. Invest in these practices to build a robust data operation.
1 min read
Fabric Adoption Patterns: Lessons from Enterprise Implementations
Success with Fabric comes from treating it as a platform transformation, not just a technology deployment. Invest in people, process, and governance…
1 min read
AI Project Learnings: What Actually Works in Practice
These lessons were learned the hard way. Hopefully, they save you some pain.
1 min read
AI Agent Templates: Quick Start Patterns for Enterprise Use Cases
Templates accelerate agent development by providing battle-tested patterns. Start with a template, customize for your needs, and iterate based on real usage.
1 min read
Building AI Applications: Choosing the Right Platform and Architecture
The key to successful AI applications is choosing the right architecture for your requirements and building with production considerations from the start.
1 min read
Agent Safety Patterns: Building Trustworthy AI Systems
Safety in AI agents is not optional - it's foundational. Build safety in from the start, and your agents will be both powerful and trustworthy.
1 min read
Retry Strategies for AI Applications: Beyond Simple Backoff
Smart retry strategies balance reliability with resource efficiency. The key is adapting behavior based on error type, system state, and business requirements.
1 min read
Error Handling in LLM Applications: A Comprehensive Guide
Robust error handling is what separates prototypes from production systems. Invest in comprehensive error handling early to avoid painful debugging later.
1 min read
Agent Reliability Patterns: Building Robust AI Systems
Building reliable agents requires investment in error handling, recovery mechanisms, and observability. These patterns form the foundation for production AI…
1 min read
Building Type-Safe AI Applications: From Prompts to Production
Type safety transforms AI applications from fragile prototypes into robust production systems. Invest in types early - your future self will thank you.
1 min read
When to Use o1: A Decision Guide for AI Applications
o1 shines in specific scenarios. Understanding these helps you deploy it effectively.
1 min read
Microsoft Fabric Governance: A Complete Guide
Effective Microsoft Fabric governance requires attention to access control, data quality, cost management, and lifecycle management. This month's…
1 min read
Microsoft Fabric June 2024: Month in Review
This month we explored Microsoft Fabric comprehensively. Today I'm summarizing key learnings and best practices from my June 2024 deep dive.
1 min read
Building Data Products in Microsoft Fabric
Data products are the deliverables of a data mesh. Today I'm exploring how to build, manage, and consume data products in Microsoft Fabric.
1 min read
Workspace Governance in Microsoft Fabric
Workspaces are the containers for collaboration in Fabric. Effective governance ensures organization, security, and efficiency. Today I'm covering workspace…
1 min read
AI Agent Best Practices: Lessons from Production
AI Agent Best Practices: Lessons from Production
2 min read
Microsoft Fabric Data Engineering: Best Practices After 6 Months in Production
Avoid over-partitioning. If partitions have < 1GB of data, consolidate. Use Data Pipelines, Not Just Notebooks
1 min read
Fabric Performance Tuning: Optimizing Your Data Platform
Performance tuning in Fabric blends write-time optimisations (v-ordering, partitioning) with query-time strategies (predicate pushdown, materialised views).…
1 min read
Fabric Components: When to Use What
Fabric's component set is broad; the hard part is picking the minimal surface that solves your business need. This guide distils when to use Lakehouse…
1 min read
Microsoft Fabric Best Practices for Production
Shipping Fabric into production exposes common anti-patterns — unbounded capacity use, duplicated data copies, and insufficient observability. The best…
1 min read
Responsible AI Practices: Building Ethical AI Systems
Responsible AI isn't merely compliance box-ticking; it's product design that protects people and preserves trust. In practice I've found that pairing…
1 min read
Enterprise AI Lessons: What We Learned in 2023
Working with teams across finance, healthcare and retail this year, the same practical lessons come up: start with the business question, instrument for…
1 min read
AI Adoption Patterns: What Separates Success from Failure
After advising a range of enterprise AI programmes in 2023, the patterns are consistent: success comes from narrow business-first problem definition…
5 min read
LLM Application Testing: Strategies and Frameworks
Testing LLM applications is a problem that doesn't have a satisfying general-purpose solution yet, and that's worth acknowledging before diving into…
2 min read
Prompt Engineering Mastery: Advanced Techniques for GPT-4
GPT-4 has been available since March 2023 and the gap between practitioners who've put in real work with it and those still writing prompts by intuition is…
1 min read
Azure OpenAI Enterprise Patterns: Lessons from Production Deployments
After months of working with Azure OpenAI in enterprise environments, the patterns that separate solid deployments from problematic ones have become clear …
1 min read
Microsoft Fabric Best Practices: Lessons Learned
Best practices and lessons learned from implementing Microsoft Fabric solutions for enterprise analytics.
1 min read
Fabric Workspace Setup: Organization and Best Practices
How you structure workspaces in Fabric matters more than most getting-started guides acknowledge. A workspace is the unit of security, capacity binding, and…
1 min read
Error Handling for AI Applications: Building Resilient Systems
Robust error handling ensures AI applications remain useful even during failures. Tomorrow, I will cover retry strategies in more depth.
1 min read
Token Budgeting: Cost-Effective LLM Applications
Token costs for GPT-4 in mid-2023 are real enough to design around: roughly $0.03 per 1K input tokens and $0.06 per 1K output tokens for the 8K context…
1 min read
Migrating to Microsoft Fabric: Strategies and Best Practices
The fastest approach uses OneLake shortcuts to reference existing data without copying. Run Fabric alongside existing platform during transition.
1 min read
GPT-4 Limitations and Workarounds
GPT-4's training data ends in September 2021. It doesn't know about recent events, technologies, or updates.
1 min read
Embedding Best Practices for Production AI Systems
OpenAI Embeddings Guide MTEB Benchmark Embedding Best Practices
1 min read
Azure Security: A Year in Review
2022 brought significant security advancements in Azure, from Defender for Cloud improvements to enhanced Zero Trust capabilities. As we move into 2023,…
1 min read
Right-Sizing Azure Resources: A Data-Driven Approach
1. Collect metrics CPU, memory, network, IOPS 2. Analyze patterns Peak, average, trends 3. Identify candidates Under utilized resources 4. Recommend changes…
1 min read
Auto-Scaling Best Practices in Azure
Auto scaling is powerful but requires careful tuning. Start with conservative settings, monitor behavior, and adjust based on real data. Combine metric…
1 min read
Azure Spot Instance Strategies for Cost Savings
Spot VMs use Azure's excess capacity at significant discounts. Key characteristics: Up to 90% discount Can be evicted anytime 30 second eviction notice Best…
1 min read
Azure Cost Optimization Tips for 2023
Cost optimization is an ongoing practice, not a one time project. The combination of right sizing, reservations, storage optimization, and operational…
1 min read
FinOps Adoption: Managing Azure Costs Effectively
1. Teams need to collaborate : Finance, engineering, and business work together 2. Everyone takes ownership : Cost is everyone's responsibility 3. A…
1 min read
Developer Productivity Tools and Practices for 2023
The game changer for code generation: Beyond Copilot, ChatGPT helps with: Code explanation and review Documentation generation Debugging assistance Learning…
1 min read
DevOps Practices That Defined 2022
The four key metrics gained mainstream adoption: Security integrated earlier in the pipeline: IaC practices became more sophisticated: Three pillars…
1 min read
Model Cards: Documenting AI for Transparency and Trust
A model card is a documentation framework for machine learning models, inspired by nutrition labels on food. It provides essential information about a…
1 min read
Prompt Engineering Basics: Getting Better Results from AI
Poor prompt: "Write code for a website" Better prompt: "Write HTML and CSS for a responsive landing page for a SaaS product. Include a hero section with…
1 min read
Black Friday Azure Tips: Cost Optimization for Peak Traffic
Don't wait for auto scaling to catch up during traffic spikes: Reduce database load with intelligent caching: Use read replicas and query optimization:…
1 min read
Azure DevOps Best Practices - October 2022 Summary
Azure DevOps provides a comprehensive platform for enterprise DevOps with robust security and governance features.
1 min read
GitHub Reusable Workflows Patterns
Reusable workflows reduce duplication and improve maintainability across repositories.
1 min read
Designing End-to-End IoT Solution Architecture on Azure
This architecture provides a scalable, secure foundation for enterprise IoT solutions on Azure.
1 min read
Azure IoT Security Best Practices
Implementing these security best practices creates a defense-in-depth approach for your IoT solutions.
1 min read
DataOps Practices: Agile for Data Teams
DataOps in 2021 matured from concept to standard practice. Teams that adopted these practices delivered faster and more reliably than those stuck in manual…
1 min read
Data Quality Practices: Building Trust in Your Data
Data quality in 2021 became an engineering discipline. The tools matured, but success requires organizational commitment to treating data as a product.
1 min read
Cost Optimization Strategies for Azure Workloads
Cost optimization in 2021 became a core cloud competency. The tools are powerful; success requires discipline and cultural change.
1 min read
Azure Automanage: Automated VM Management Best Practices
Azure Automanage transforms VM management from a series of manual tasks into an automated, best-practice-driven process. It's ideal for organizations that…
2 min read
Job Clusters vs All-Purpose Clusters: Choosing the Right Approach
The job cluster versus all-purpose cluster decision in Databricks is primarily a cost decision: all-purpose clusters stay running between tasks (you pay for…
1 min read
Leveraging Azure Architecture Center Reference Architectures
The Azure Architecture Center is the reference resource I bookmark more than any other when I need to move from "I know what I want to build" to "I know the…
1 min read
Implementing the Azure Well-Architected Framework
The Azure Well-Architected Framework is the document I send to clients at the start of every architecture engagement and the checklist I review before every…
1 min read
Implementing Azure Advisor Recommendations at Scale
Azure Advisor is the free recommendation service that surfaces findings your team should have already found—and usually hasn't. The five categories (Cost…
1 min read
Azure Storage Account Security Best Practices
Storage accounts are deceptively easy to deploy and easy to misconfigure into a leak. Public blob containers are still the most common "how did this get…