How I Actually Use AI Agents Every Day
Most AI agent tutorials show Python loops and vector databases. Here's what daily agent use actually looks like: terminal-first orchestration, agent files, context architecture, and a knowledge system that feeds all of it.
All Articles
AI Code Review: Approaches, Trends, and Best Practices
AI is writing more code. Here's how to review it faster — local agent patterns, CI/CD integration, and the vendor landscape including Greptile, CodeRabbit, and GitHub Copilot.
How I Automated My SaaS Signup Flow in a Weekend
Built a beta signup pipeline (form to email in 30 seconds) with Modal, Resend, and Google Sheets. 913 lines of Python, 4 hours, $0/month.
Context Engineering for AI Coding Tools: Why Your Codebase Structure Matters More Than Your Prompts
Most developers over-invest in prompt engineering and ignore context. Here's the four-layer framework that makes every AI coding session better.
The AI Coding Model Wars: How Open Source Is Closing the Gap on Proprietary Coding Models
Four major coding models launched in six days. The benchmark gap? 2.6 points. The price gap? 45x. A head-to-head comparison of Opus 4.6, Codex 5.3, GLM-5, and Kimi K2.5.
From Vibe Coding to Agentic Engineering: What Changed and What It Means
Vibe coding was the prompt-first era. Agentic engineering is the orchestration-first era. Here's what changed, why it matters, and what you need to learn next.
Lessons Learned in 2026
A generalist's field notes from 2026. AI changed the game, execution still wins, and the engineers who connect dots nobody else sees are the ones getting ahead.
5 Automations Every Service Business Should Have by 2026
The 5 automations that save service businesses 10+ hours/week. Concrete tools, setup times, and ROI for agencies and consultants.
Context Engineering: The Skill That Makes AI Coding Tools Actually Work
Most developers blame the model when AI coding tools produce bad output. The real problem is context. Here's the system I built to fix that.
AI Model Selection: Choosing the Right Model and Application Pattern
Not all tasks need the most powerful AI model. Learn how to match model intelligence to task complexity and stop overpaying for sledgehammers when you need scalpels.
Enterprise Best Practices for AI-Assisted Software Engineering Teams
AI tooling can speed up enterprise engineering teams, but only with the right guardrails. A practical guide to prompting, context management, governance, and parallelization across Claude, Copilot, and CLI tools.
The Changing AI Landscape: Practical Insight for 2026 and Beyond
AI has moved from a shiny new toy to everyday infrastructure. Here's a realistic look at what that means for developers, managers, and business owners.
Modern Design Patterns: Beyond the Bookmarks
Classic design patterns still solve modern problems, but only if you use them to fix real friction. Here's how I use them to build maintainable systems without the architecture astronaut fluff.
How to Integrate With (Nearly) Any CRM: A Beginner No Code Guide
A practical, evergreen guide for beginners and no-code users who need reliable CRM integrations across finance, real estate, and professional services.
Structured Outputs in LLMs: Reliable Data for Real Pipelines
Structured outputs turn LLM text into dependable, validated data. Learn schemas, validation loops, provider-native features, and practical patterns for extraction, routing, and ETL.
CLI Agents for Self-Hosting: Terminal AI That Boosts Productivity
Explore how LLM-powered CLI agents simplify self-hosting on VPS and homelabs. Learn deployment patterns, Docker Compose examples, and guardrails for safe automation.
Best Practices for System Design: Lessons from Real-World Applications
Cloud-native system design that scales and fails well. Learn durable patterns—consistency, resilience, observability—with lessons from Amazon, Google, Netflix, LinkedIn, and Stripe.
AI Coding Assistants: Trends, Limits, and What's Next
What AI coding assistants actually do well, where they fail, and how to use them without breaking things or forgetting how to code.
Understanding BGP Anomalies for Engineers and Architects
A practical guide to BGP anomalies: taxonomy, detection signals, and mitigation patterns. Deploy RPKI, build guardrails, and design networks that limit blast radius.
Lessons Learned in 2025
Sharing lessons learned as a Senior Software Developer.
AWS Lambda Practices: Messaging & Compute Best Practices
A breakdown of production-ready AWS Lambda and SQS configurations, covering visibility timeouts, batch sizes, failure handling, and idempotency strategies.
Postgres SQL Optimization with DBeaver
Use DBeaver to run EXPLAIN/ANALYZE, find index gaps, apply VACUUM wisely, and enlist AI to build a safe, testable Postgres tuning plan.
JPA/Hibernate: Pragmatic Data Access That Scales
A pragmatic guide to JPA/Hibernate for tech leaders and engineers. Learn hidden tradeoffs, when to use native SQL, and patterns to ship fast, safe data access.
Microservices Redesign for Builders and Leaders
Microservices are not the default. Explore universal-interface architecture and the modular monolith, with concrete patterns, migration steps, and metrics.
Terraform and IaC: Practical Guide for Tech Teams
Why IaC matters, how to run Terraform at team scale, and a step-by-step EC2 example to get started.
MCP: Model Context Protocol for Builders and Leaders
Learn the Model Context Protocol (MCP): what it is, why it matters, and how to ship secure, observable AI tooling with a step-by-step example. Get started now.
n8n: Automation Patterns
Learn n8n: what it is, why it matters, and how to ship secure, observable automations with a free RSS-to-Slack example. Start building value fast.
Prompt Engineering Tips for Tech Leaders
A pragmatic guide to prompt engineering for tech leaders and engineers. Learn durable patterns, ROI-focused choices, and a full before/after example.
Architecture as Code: Why Tech Leaders and Engineers Should Adopt Diagrams‑as‑Code Now
AI now writes a large share of new code. Stand out with Architecture as Code—pros, cons, tools, and a simple adoption plan for leaders, engineers, and recruiters.
AI-Assisted Coding in 2025
How AI is actually changing software development—from what I've seen in the wild and what's working versus what's hype.
No-code development in enterprise software
How low-code and no-code tools actually work in enterprise environments, based on what I've seen.