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AI coding

AI-powered code generation, completion, and understanding

21 posts

blogengineer
06-Feb-2026

Why Copilot Doesn't Work on Your Hardest Tickets

AI code completion breaks down on cross-file refactors, legacy code, and tickets requiring business context. The problem isn't the AI — it's the context gap.

Tariro Mukandi
technicalengineer
05-Feb-2026

Model Context Protocol: The Missing Layer for Code AI

Why 60+ specialized MCP tools beat generic LLM prompting for code intelligence. Deep dive into the protocol that makes AI actually useful for developers.

Vivian M. Otieno
blogcto
05-Feb-2026

Sprint Planning Without 3-Hour Meetings

AI-generated dev plans with file-level tasks based on actual codebase architecture. How to cut sprint planning overhead by 50%.

Fatima Zahra Ghaddar
guidecto
05-Feb-2026

How to Protect Company Data When Using AI Agents: Complete Guide

Complete guide to securing company data when adopting AI coding agents. Data classification, access controls, audit trails, and practical security architecture.

Vivian M. Otieno
blogcto
04-Feb-2026

AI Development Productivity Tips: Avoid the 73% Failure Rate

Most AI tool adoptions fail to deliver ROI. Here are the productivity patterns that actually work for engineering teams.

Fatima Zahra Ghaddar
blogengineer
03-Feb-2026

Vibe Coding Is Not Engineering

AI-generated prototypes are impressive demos. They're terrible production systems. Here's where vibe coding ends and real engineering begins.

Vivian M. Otieno
blogcto
02-Feb-2026

What Engineering Leaders Get Wrong About AI Tool Adoption

Most teams measure AI tool success by adoption rate. The right metric is whether hard tickets get easier. Here's the framework that works.

Fatima Zahra Ghaddar
guideengineer
31-Jan-2026

How to Give Claude Code Full Project Context

Claude Code is powerful but limited by what it can see. Here's how to feed it codebase-level context for dramatically better results on complex tasks.

Fatima Zahra Ghaddar
blogengineer
31-Jan-2026

The Developer Tool Stack in 2026: What's Changed

AI reshaped the developer tool landscape. Here's what the modern engineering stack looks like and where the gaps remain.

Vivian M. Otieno
blogengineer
31-Jan-2026

25 Best AI Coding Tools in 2026: GitHub Copilot vs Cursor vs Top Alternatives

Comprehensive comparison of the top AI coding tools — Copilot, Cursor, Claude Code, Cody, and more. Updated for 2026 with real benchmarks on complex codebases.

Fatima Zahra Ghaddar
guideengineer
30-Jan-2026

How to Use Glue with Cursor: The Context-First Workflow

A practical guide to combining Glue's codebase intelligence with Cursor's AI editing for a workflow that understands before it generates.

Tariro Mukandi
blogcto
29-Jan-2026

How AI Is Changing Technical Interviews (And Why It Should)

LeetCode doesn't predict job performance. Codebase navigation and system understanding do. How interviews should evolve for the AI era.

Fatima Zahra Ghaddar
guideexecutive
28-Jan-2026

The CTO's Guide to AI Tool ROI

A framework for measuring actual return on AI coding tool investments. Spoiler: adoption rate is the wrong metric.

Vivian M. Otieno
blogengineer
28-Jan-2026

Lovable vs Dev: Migration Comparison for AI-Powered Development Platforms

Side-by-side comparison of Lovable and Dev for AI-powered application building. When to use each and how they compare to code intelligence tools.

Vivian M. Otieno
guidecto
27-Jan-2026

How to Conduct an AI Readiness Assessment for Your Engineering Team

Before buying AI tools, understand where your team will actually benefit. A practical framework for assessing AI readiness.

Vivian M. Otieno
blogcto
27-Jan-2026

AI Agents for Code: Build vs Buy in 2026

Every team considers building their own AI coding agent. Here's when it makes sense and when you should buy instead.

Fatima Zahra Ghaddar
guideengineer
26-Jan-2026

How to Use AI for Code Review Without Losing the Human Element

AI can flag dependency issues and style violations. Humans should focus on architecture, business logic, and mentoring. Here's how to split the work.

Vivian M. Otieno
technicalengineer
26-Jan-2026

Embedding vs Knowledge Graphs for Code Intelligence

Vector embeddings find similar code. Knowledge graphs find connected code. Why the best systems use both.

Tariro Mukandi
blogcto
24-Jan-2026

How Engineering Teams Should Prepare for AI-Native Development

AI-native development isn't about using more AI tools. It's about restructuring workflows around AI strengths and human judgment.

Vivian M. Otieno
technicalengineer
24-Jan-2026

Building Scalable AI Applications: Architecture Patterns That Actually Work

Practical architecture patterns for AI-powered applications — from RAG pipelines to agent orchestration. Lessons from building production AI systems.

Vivian M. Otieno
blogcto
23-Jan-2026

Why 80% of Dev Teams Will Use AI Code Tools by 2025 (And Why Most Will Be Disappointed)

The prediction came true - adoption is massive. But ROI? That is a different story. Here is why most teams are disappointed and what the successful ones do differently.

Ravi Kishore DSouza