Guides
Comprehensive, bookmark-worthy guides for product managers, engineering leaders, and CTOs. The definitive resources on codebase intelligence.
Code Refactoring: When, Why, and How to Refactor Without Breaking Everything
Refactoring improves code without changing behavior. Learn when to refactor, which techniques to use, how to build the business case, and how to do it safely at scale.
Microservices vs Monolith: How to Choose the Right Architecture in 2026
Microservices or monolith? The answer depends on your team size, domain complexity, and operational maturity. This guide helps you make the right architectural call.
Code Smell: How to Detect, Diagnose, and Fix the 20 Most Common Code Smells
Code smells signal deeper design problems. Learn to identify the 20 most common smells, understand their root causes, and fix them with targeted refactoring patterns.
Software Development Lifecycle (SDLC): Every Phase Explained for 2026
Understand every phase of the SDLC: planning, analysis, design, development, testing, deployment, and maintenance. Includes model comparisons and modern AI-augmented workflows.
Shift Left: How Moving Testing Earlier Cuts Defect Costs by 100x
Shift left testing and security catches defects when they are cheapest to fix. Learn implementation strategies, tools, and how to measure the ROI of shifting left.
Incident Management: From Alert to Resolution to Prevention
Build an incident management process that reduces MTTR and prevents repeat failures. Covers severity levels, on-call rotations, postmortems, and the role of codebase context.
Feature Flags: The Complete Guide to Safe, Fast Feature Releases
Feature flags decouple deployment from release. Learn implementation patterns, management best practices, and how to avoid the flag debt trap.
Clean Code: Principles, Practices, and the Real Cost of Messy Code
Clean code is not about aesthetics — it is about velocity. Learn the principles that reduce bugs, speed up onboarding, and cut maintenance costs by measurable amounts.
Platform Engineering: Building the Internal Developer Platform Your Team Needs
Platform engineering reduces cognitive load so developers can ship faster. Learn how to build an internal developer platform with self-service, golden paths, and codebase intelligence.
API Documentation: How to Write Docs Developers Actually Want to Read
Great API documentation is the #1 driver of developer adoption. Learn structure, tools, examples, and how AI auto-generates endpoint docs from your codebase.
Observability: Beyond Monitoring — How to Actually Understand Your Systems
Observability goes beyond monitoring. Learn the three pillars (logs, metrics, traces), top tools, and how codebase intelligence adds the missing context layer.
Design Patterns in Software Engineering: A Practical Guide with Real Examples
Learn the 23 GoF design patterns with modern, real-world examples. Includes when to use each pattern, anti-patterns to avoid, and how AI can detect pattern opportunities.
Tech Stack: How to Choose, Document, and Communicate Your Technology Stack
How to choose a tech stack that scales, document it so everyone understands it, and avoid the architecture decisions that create years of technical debt.
DORA Metrics: The 4 Key Metrics That Predict Engineering Team Performance
Master the 4 DORA metrics: deployment frequency, lead time, change failure rate, and MTTR. Includes benchmarks, dashboards, and how to improve each metric.
What Is DevOps? A Plain-English Guide for Non-Engineers
DevOps explained without the jargon. Learn what DevOps means, why it matters for product delivery, and how it connects CI/CD, monitoring, and team culture.
Technical Debt: What It Really Is, How to Measure It, and When to Pay It Down
Technical debt costs the average team 42% of development time. Learn how to identify, quantify, and strategically eliminate it with data-driven prioritization.
CI/CD Pipeline: The Definitive Guide to Continuous Integration & Delivery
Build a CI/CD pipeline that actually works. Covers pipeline stages, tool comparison, security integration, and the metrics that matter for deployment velocity.
Burndown Charts Explained: How to Read, Build, and Actually Use Them
Master burndown charts: how to read them, build them, and use them to predict sprint outcomes. Includes templates, examples, and common anti-patterns.
Trunk-Based Development: Why Top Teams Ship Faster Without Long-Lived Branches
Learn why Google, Meta, and top engineering teams use trunk-based development. Includes migration guide, CI/CD setup, and how to handle feature flags.
Technical Documentation: The Complete Guide for Engineering Teams [2026]
Everything you need to know about technical documentation: types, templates, tools, and the AI-powered workflows that cut documentation time by 60%.
AI for Product Teams: The 2026 Playbook
How product teams can use AI for codebase intelligence, competitive analysis, spec writing, and planning.
The Complete Guide to Software Estimation
Everything you need to know about software estimation: why it fails, what works, and how to make it better.
The CTO's Guide to Product Visibility
How CTOs can answer board-level questions about features, competitive position, and technical health using code intelligence.
The Engineering Manager's Guide to Code Health
Everything engineering managers need to monitor, measure, and improve the health of their codebase.
The Product Manager's Guide to Understanding Your Codebase
The comprehensive guide for product managers who want to understand their codebase without learning to code.