# Shawn Mayzes - Technical Leader & Startup Mentor

> Shawn Mayzes is a renowned technical leader specializing in Laravel, DevOps, and cloud computing. He provides code reviews, startup mentoring, and fractional CTO services. His expertise spans software development, technical leadership, and business strategy alignment.

Shawn Mayzes is a technical leader with extensive experience in software development, DevOps, and cloud computing. He specializes in Laravel development and provides expert code reviews, startup mentoring, and fractional CTO services. His approach focuses on aligning technology with business goals, fostering inclusive team cultures, and delivering impactful results that drive growth and efficiency.

Key areas of expertise:
- Laravel and PHP development
- DevOps and cloud computing
- Technical leadership and team mentoring
- Startup strategy and fractional CTO services
- Code reviews and best practices
- AI-driven development and modern tooling

## Articles

- [Fractional CTO vs. Fractional AI Architect: Which Does Your Startup Need?](https://www.shawnmayzes.com/articles/fractional-cto-vs-fractional-ai-architect/): Fractional CTO, chief AI officer, or AI architect - the titles blur together, but the jobs don't. Here's how to tell which one your startup actually needs right now.
- [SPF Record Setup Guide (2026): Configure SPF for Gmail & Google Workspace](https://www.shawnmayzes.com/articles/spf-record-setup-for-gmail-google-workspace/): Set up an SPF record for Gmail or Google Workspace to stop spoofed emails from your domain. Step-by-step guide, common syntax errors, and troubleshooting.
- [DMARC Record Setup Guide (2026): Configure DMARC for Your Domain](https://www.shawnmayzes.com/articles/dmarc-record-setup-guide/): Set up a DMARC policy to stop email spoofing and get visibility into who's sending mail as your domain. Step-by-step guide with rollout strategy and report reading.
- [Cloudflare Turnstile Setup Guide (2026): Add CAPTCHA-Free Bot Protection](https://www.shawnmayzes.com/articles/cloudflare-turnstile-setup-guide/): Add Cloudflare Turnstile to a form to block bot submissions without making real users solve a CAPTCHA. Setup steps, verification, and common pitfalls.
- [Webhook Signature Verification Setup Guide (2026): Stripe, GitHub & HMAC](https://www.shawnmayzes.com/articles/webhook-signature-verification-setup-guide/): Verify incoming webhooks with HMAC signatures so your endpoint only trusts genuine events from Stripe, GitHub, or any provider. Step-by-step setup and common mistakes.
- [.env and Secrets Management for Small Teams (2026 Guide)](https://www.shawnmayzes.com/articles/env-secrets-management-for-small-teams/): What actually belongs in .env, what belongs in a secrets manager, and how small teams should handle API keys and credentials without a dedicated security hire.
- [GitHub Branch Protection Rules Setup Guide for Growing Engineering Teams](https://www.shawnmayzes.com/articles/github-branch-protection-rules-for-growing-teams/): Configure GitHub branch protection so a growing team can't accidentally break main. What rules matter, what to skip, and how to roll them out without slowing people down.
- [Laravel Production Deployment Checklist (2026)](https://www.shawnmayzes.com/articles/laravel-production-deployment-checklist/): A practical pre-deploy checklist for Laravel apps: config, queues, caching, and the mistakes that only show up once real traffic hits production.

## Projects

- [Jetpack Labs - AI Systems & Fractional CTO for Startups](https://www.shawnmayzes.com/projects/jetpack-labs/): Jetpack Labs builds AI-augmented software systems for startups and growth-stage companies. Fractional CTO leadership, AI engineering, and product delivery - senior technical expertise without the full-time overhead.
- [Telemetry](https://www.shawnmayzes.com/projects/telemetry/): Multi-bot AI orchestration platform powering specialized AI agents (Article Writer, Social Media Manager, SEO Analyst, PR Specialist) that collaborate to generate high-quality content at scale. Built as Jetpack Labs' reference implementation for production-grade multi-agent AI systems with extensible architecture and comprehensive observability.
- [CodeBot - Automated AI Code Review for GitHub Pull Requests](https://www.shawnmayzes.com/projects/codebot/): CodeBot is an AI code review tool that uses Google Gemini + Claude in a dual-model pipeline to automatically analyze GitHub PRs, post line-by-line comments, and discover evolving code standards - cutting review time by 80%.
- [DevOpsChat.co - Slack Community for DevOps Professionals](https://www.shawnmayzes.com/projects/devopschat/): DevOpsChat.co is a Slack community and learning hub built for DevOps engineers. Join professionals sharing real-world knowledge on CI/CD pipelines, cloud infrastructure, automation, and site reliability - with topic channels organized by expertise level.
- [LaraChat.co - Slack Community for Laravel Developers](https://www.shawnmayzes.com/projects/larachat/): LaraChat.co is a Slack community built for Laravel developers. Topic channels for Eloquent, Blade, Livewire, packages, and jobs - plus real-time discussion with developers actively building in the Laravel ecosystem.
- [ToastMail](https://www.shawnmayzes.com/projects/toastmail/): ToastMail.io, an AI-powered email warming tool designed to enhance deliverability and prevent emails from landing in spam folders

## AI Engineering

- [Cursor vs. Claude Code vs. Zencoder vs. Copilot: A Decision Framework (2026)](https://www.shawnmayzes.com/ai-engineering/cursor-vs-claude-code-vs-zencoder-vs-copilot/): These four tools solve overlapping but distinct problems. A practical framework for which one fits your team's workflow, not a feature-by-feature scoreboard.
- [Structured Output Reliability: Why LLM Tool Calls Fail Silently](https://www.shawnmayzes.com/ai-engineering/structured-output-reliability-llm-tool-calls/): LLM tool calls don't usually fail loudly, they fail by returning something that's almost the right shape. A practical guide to validating structured output and building retry logic that catches it.
- [What Happens When Your AI Agent's Context Window Runs Out Mid-Task](https://www.shawnmayzes.com/ai-engineering/what-happens-when-ai-agent-context-runs-out/): Long AI agent sessions eventually hit a context limit. Here's what compaction actually does, what silently gets lost, and how to structure long-running agent work so it survives the cutover.
- [Sandboxing and Permission Models for AI Coding Agents](https://www.shawnmayzes.com/ai-engineering/sandboxing-permission-models-ai-coding-agents/): AI coding agents that can run shell commands and edit files unsupervised need a real permission model, not blind trust. What to sandbox, what to gate behind approval, and what should never be automatic.
- [Claude Code Subagents: When to Split Work vs. Run a Single Agent](https://www.shawnmayzes.com/ai-engineering/claude-code-subagents-when-to-split-work/): Subagents aren't free parallelism, they cost context and coordination overhead. A practical framework for when splitting work across Claude Code subagents actually helps, and when it just adds latency.
- [Claude Code for Engineering Teams: Building a Shared CLAUDE.md That Actually Stays Current](https://www.shawnmayzes.com/ai-engineering/claude-code-for-engineering-teams/): Running Claude Code solo is easy. Running it across a 5-10 person team without everyone developing conflicting workflows, duplicate context, and a CLAUDE.md that nobody trusts is the hard part. Here's the org design, not the technical architecture.

## Services

- [Code Reviews](https://www.shawnmayzes.com/code-audit-offer/): Expert Laravel code reviews to enhance quality and ensure best practices
- [Startup Mentoring](https://www.shawnmayzes.com/contact/): Strategic guidance for entrepreneurs with technical and operational insights
- [Fractional CTO](https://www.shawnmayzes.com/contact/): Strategic technology leadership aligning tech with business goals

## Optional

- [AI Governance for Engineering Teams: The Policies You Need Before Something Goes Wrong](https://www.shawnmayzes.com/articles/ai-governance-engineering-teams/): AI governance policy framework for engineering teams: data handling, code ownership, security gates. Protect without slowing down.
- [How to Measure the ROI of AI Coding Tools Without Getting Fooled by the Wrong Metrics](https://www.shawnmayzes.com/articles/measuring-ai-coding-tools-roi/): Measure AI coding tool ROI beyond lines of code. Practical framework for engineering teams—plus Goodhart's Law traps that make bad metrics look good.
- [What I Look for When Hiring an AI-Native Engineer in 2026 (Interview Questions Included)](https://www.shawnmayzes.com/articles/hiring-ai-native-engineers-2026/): Hire engineers with AI judgment, not just AI skill. Interview questions, rubric, and red flags that look like green flags.
- [Technical Due Diligence When the Codebase Was Built with AI: The New CTO Checklist](https://www.shawnmayzes.com/articles/technical-due-diligence-ai-codebase/): Technical due diligence for AI-generated codebases: what changes when 40-60% of code came from Claude or Copilot.
- [Vibe Coding in Production: A Risk-Tiered Framework for When It's Acceptable](https://www.shawnmayzes.com/articles/vibe-coding-production-risk/): 86% of AI-generated code fails XSS tests. What actually breaks it in production and the three audit categories that catch risk.
- [The Agentic Shift: Why Your Dev Team's Biggest Bottleneck Isn't Code Anymore](https://www.shawnmayzes.com/articles/agentic-shift-dev-bottleneck/): Software development is shifting from manual code writing to orchestrating AI agents. Here's what it means for your startup and how to prepare.
- [When Your Startup CTO Can''t Scale: Signs You Need Fractional Support](https://www.shawnmayzes.com/articles/the-cto-that-cant-scale-with-you/): The engineer who gets you to product-market fit often can't lead teams at 50 people. How to spot this problem early and plan around it.
- [Fractional CTO AI Blind Spot: What Happens When They''re Advising Without Building](https://www.shawnmayzes.com/articles/fractional-cto-ai-blind-spot-advising-without-building/): Most fractional CTOs haven't actually built AI systems. Here's why that gap costs you money, time, and strategic clarity on AI decisions that matter.
- [AI-Generated Technical Debt: The 2026 Problem Nobody''s Ready For](https://www.shawnmayzes.com/articles/ai-generated-technical-debt-the-2026-problem/): AI-generated code ships faster but creates new technical debt frameworks can't classify. Here's why it matters and what to do about it.
- [You Don''t Have a Software Problem. You Have a Discovery Problem.](https://www.shawnmayzes.com/articles/you-dont-have-a-software-problem-you-have-a-discovery-problem/): Most startup builds fail before a line of code is written. A two-week discovery phase prevents 3-6x rework costs. Here's why teams skip it.
- [Your Business Made a Promise Your Engineers Cannot Keep](https://www.shawnmayzes.com/articles/your-business-made-a-promise-your-engineers-cannot-keep/): The real reason your engineering team always feels behind isn't speed. It's that business commitments get made before anyone asks if engineering can deliver.
- [Why Startups Outgrow Their Software Before They Outgrow Their Market](https://www.shawnmayzes.com/articles/why-startups-outgrow-their-software-before-they-outgrow-their-market/): Most startups hit a growth ceiling not because the market changed, but because the software can't keep up. Here's what to watch for and what to do about it.
- [You're Not Behind on AI. You're Behind on the Basics.](https://www.shawnmayzes.com/articles/youre-not-behind-on-ai-youre-behind-on-the-basics/): 80% of AI projects fail, mostly due to bad data and broken processes. Fix your foundation first, then AI becomes powerful.
- [Your 'Good Enough' Systems Are Quietly Bleeding Money](https://www.shawnmayzes.com/articles/your-good-enough-systems-are-quietly-bleeding-money/): The systems founders call 'fine for now' are often the biggest hidden cost in their business. Here's how to find and fix the leaks.
- [Your Best Developer Isn't Writing Code Anymore](https://www.shawnmayzes.com/articles/your-best-developer-isnt-writing-code-anymore/): The best developers in 2026 orchestrate AI agents, not syntax. Here's what that means for startup hiring and team structure.
- [Build vs. Buy in 2026: AI Has Changed the Math for Startups](https://www.shawnmayzes.com/articles/build-vs-buy-in-2026-ai-has-changed-the-math-for-startups/): AI coding tools have shifted the build vs. buy equation. Here's how founders should rethink what to build in-house and what to buy off the shelf.
- [What Happens When Your Key Technical Person Walks Out the Door](https://www.shawnmayzes.com/articles/what-happens-when-your-key-technical-person-walks-out/): Your best engineer's knowledge lives in their head, not your systems. Here's how to fix that before it costs you everything.
- [Tech Debt Is a Business Decision, Not a Technical One](https://www.shawnmayzes.com/articles/tech-debt-is-a-business-decision-not-a-technical-one/): Technical debt isn't a failure of engineering. It's a strategic tradeoff. Here's how founders should think about it.
- [Your Dev Team Is Shipping Faster With AI. So Why Is Everything Breaking?](https://www.shawnmayzes.com/articles/your-dev-team-is-shipping-faster-with-ai-so-why-is-everything-breaking/): AI coding tools promise speed. But faster output without guardrails creates a new kind of technical debt. Here's what founders need to know.
- [When Your Dev Team Needs Systems More Than Headcount](https://www.shawnmayzes.com/articles/when-your-dev-team-needs-systems-more-than-headcount/): Most founders think hiring more developers will solve their speed problems. Here's why systems and leverage matter more than team size.
- [Why Your CTO Should Be Building With AI, Not Just Talking About It](https://www.shawnmayzes.com/articles/why-your-cto-should-be-building-with-ai-not-just-talking-about-it/): Most technical leaders are still treating AI like a research project. Here's why the best CTOs are in the code, shipping AI-augmented systems right now.
- [When Your Team Needs a CTO But You Can't Afford One Yet](https://www.shawnmayzes.com/articles/when-your-team-needs-a-cto-but-you-cant-afford-one/): Tech decisions are getting harder but you're not ready for full-time CTO. How fractional CTOs bridge the leadership gap for growing teams.
- [When Your Lead Developer Says No (And Why You Should Listen)](https://www.shawnmayzes.com/articles/when-your-lead-developer-says-no/): That moment when your lead dev pushes back on a timeline or feature request isn't resistance—it's information. Here's what's actually happening when technical leaders say no.
- [Building Whole Humans, Not Just High-Performers: Growing Tech Teams in a Burnout Era](https://www.shawnmayzes.com/articles/building-whole-humans-not-just-high-performers/): Sustainable high performance starts with treating developers like humans. How tech leaders build teams that ship without burning people out.
- [Move Fast & Fix Things: Build Ethical Teams](https://www.shawnmayzes.com/articles/move-fast-fix-things-build-ethical-teams-without-slowing-down/): Practical ways tech leaders can build ethical, high-trust teams that increase speed rather than slow it down.
- [The Fractional CTO's Guide to Building Tech Teams at Early-Stage Startups](https://www.shawnmayzes.com/articles/the-fractional-ctos-guide-to-building-tech-teams-at-early-stage-startups/): Practical guide for fractional CTOs to strategically hire, shape culture, and scale early teams without breaking momentum.
- [10 Things Non-Technical Founders Should Know Before Hiring a CTO (Fractional or Full-Time)](https://www.shawnmayzes.com/articles/struggling-for-tech-direction-10-things-non-technical-founders-should-know-before-hiring/): A practical, no-fluff guide for non-technical founders to scope, evaluate, and sequence their first technical hires without wasting time or money.
- [Fractional CTO vs Full-Time CTO: Do You Really Need to Hire Full-Time?](https://www.shawnmayzes.com/articles/do-you-really-need-a-full-time-cto-fractional-leadership-truth/): Fractional vs full-time CTO: decision framework with costs ($1K-$15K/mo vs $150K-$250K+/yr) for founders.
- [Mastering Claude Code - The Developer's AI Assistant](https://www.shawnmayzes.com/articles/mastering-claude-code-the-developers-ai-assistant/): Practical guide to Claude Code — how developers use AI to automate tasks, debug faster, and ship better code with less grunt work.
- [Growth Mindset for Tech Leaders: Beyond Code](https://www.shawnmayzes.com/articles/beyond-code-cultivating-a-growth-mindset-for-tech-leaders/): What separates great tech leaders isn't technical skill — it's mindset. Practical strategies for resilience, innovation, and continuous learning.
- [The Startup CTO's Playbook: Aligning Tech Roadmaps with Business Goals](https://www.shawnmayzes.com/articles/the-startup-ctos-playbook-aligning-tech-roadmaps-with-business-goals/): How startup CTOs align tech roadmaps with business goals without slowing delivery or burning engineering goodwill.
- [Level Up Your Skills: 5 Key Lessons from a Developer's Journey to Tech Leadership](https://www.shawnmayzes.com/articles/level-up-your-skills-5-key-lessons-from-a-developers-journey-to-tech-leadership/): 5 real lessons from the jump to tech leadership — the mindset shifts, habit changes, and priorities that define a developer's move into leadership.
- [Gmail DKIM Setup Guide (2026): Configure DKIM for Google Workspace](https://www.shawnmayzes.com/articles/a-guide-to-understanding-and-setting-up-dkim-records-for-gmail/): Set up and understand DKIM records for Gmail/Google Workspace. Step-by-step guide with troubleshooting and best practices.
- [Why Your Startup Needs a Fractional CTO](https://www.shawnmayzes.com/articles/why-your-startup-needs-a-fractional-cto/): Senior tech leadership without the full-time cost. Here's why fractional CTOs deliver more value for startups that aren't ready to hire a full-time CTO.
- [Why Code Fails in Production (Not Just Your Machine)](https://www.shawnmayzes.com/articles/the-fallacy-of-it-works-on-my-machine-why-code-fails-in-production-and-how-to-prevent-it/): Code passes tests locally then breaks in production. Environment gaps, concurrency, and performance limits cause failures — here's how to prevent them.
- [5 Must-Read Books for Startup Founders](https://www.shawnmayzes.com/articles/5-must-read-books-for-startup-founders/): Five books that shaped how I lead teams and build products. Lessons in ownership, user-centered design, and negotiation every founder needs.
- [Advanced CRUD Tutorial for Developers](https://www.shawnmayzes.com/articles/advanced-crud-tutorial-for-developers/): Master Laravel CRUD operations for creating, reading, updating, and deleting data. Comprehensive tutorial with best practices.
- [Laravel Eloquent API Resources: Complete Documentation Guide](https://www.shawnmayzes.com/articles/api-consistency-eloquent-api-resources-in-laravel/): Transform Laravel models into consistent JSON APIs with Eloquent Resources. Examples for formatting, nesting, conditionals, collections.
- [First Things First in Laravel: Setting up your Local Environment](https://www.shawnmayzes.com/articles/first-things-first-in-laravel-setting-up-your-local-environment/): Set up your Laravel local environment before diving into development. Essential first steps for Laravel beginners.
- [From Code to C-Suite: The Evolution of a Tech Leader](https://www.shawnmayzes.com/articles/from-code-to-c-suite-the-evolution-of-a-tech-leader/): My path from software developer to CTO — the real challenges, tradeoffs, and lessons from blending technical depth with strategic leadership.
- [CI/CD for AI: Running Prompt Regression Tests and LLM-as-a-Judge Gates in GitHub Actions](https://www.shawnmayzes.com/ai-engineering/cicd-for-ai-evals/): GitHub shipped agentic workflows in February 2026. But your existing CI/CD isn't equipped for AI outputs - deterministic tests break on probabilistic outputs. Here's how to run prompt regression tests and LLM-as-a-Judge evaluation gates that actually catch regressions.
- [Which MCP Server Should You Build? A Decision Guide for the 5 Real Patterns](https://www.shawnmayzes.com/ai-engineering/which-mcp-server-to-build/): 13,000+ MCP servers exist but the tutorials don't tell you which pattern to use or why. stdio vs HTTP vs .mcpb vs npm package vs raw script - here's the decision guide nobody has written yet, with honest tradeoffs for each.
- [Claude Code Hooks: The Reliability Layer Your CLAUDE.md Can't Replace](https://www.shawnmayzes.com/ai-engineering/claude-code-hooks-reliability/): CLAUDE.md instructions get followed 70-90% of the time. Claude Code hooks run 100% of the time, every time, automatically. Here's what hooks actually do, the patterns that matter in production, and why this is the most underused feature in Claude Code.
- [AGENTS.md vs. CLAUDE.md: What Claude Code Actually Reads (And the Workaround for Both)](https://www.shawnmayzes.com/ai-engineering/agents-md-vs-claude-md/): Claude Code reads CLAUDE.md. Other agents read AGENTS.md. Here's what the two standards actually do differently, why Claude Code doesn't support AGENTS.md yet, and the exact workaround to manage both without duplicate work.
- [Context Engineering for Claude Code: Why Most Agent Failures Are Context Failures](https://www.shawnmayzes.com/ai-engineering/context-engineering-claude-code/): Context engineering is the discipline of designing what information your AI agent has, in what format, at what time. For Claude Code specifically: CLAUDE.md, tool definitions, memory compaction, and project structure are all context engineering decisions - here's how to approach them as a system.
- [Using Claude Locally in 2026: Desktop, Code, and Fully Offline - What Actually Works](https://www.shawnmayzes.com/ai-engineering/using-claude-locally-2026/): Can you run Claude locally or offline in 2026? Here's what actually works: Claude Code with Ollama (3 env vars), Claude Desktop's new third-party gateway, MCP bridges, and fully offline alternatives when you need zero cloud dependency.
- [Running Claude Code with a Local LLM in 2026: No Proxy Required](https://www.shawnmayzes.com/ai-engineering/claude-code-local-llm-2026/): How to run Claude Code with a local LLM using Ollama, LM Studio, or oMLX - no proxy required. Model recommendations by hardware, 2026 setup commands, and the fastest backends available today.
- [The Revolt Against Bloat: What Happens When a Builder Gets Tired of Bad Software](https://www.shawnmayzes.com/ai-engineering/the-revolt-against-bloat-ai-and-the-solo-builder/): From building my own ATS, documentation tool, and Chrome extension to watching a solo dev replace Logitech's entire software suite in a week. AI is collapsing the cost of building what commercial software should have been.
- [From Spec to Skill: The Mental Model That Made Claude Code Click](https://www.shawnmayzes.com/ai-engineering/from-spec-to-skill-mental-model-claude-code/): After hitting the 'context wall' repeatedly, one mental shift changed everything: treat Claude Code like an OS, not a chatbot. Here's the vocabulary - workflow, skill, agent, sub-agent - and why it matters for how you structure every session.
- [Your AI Tooling Budget Is Already Unsustainable - Here's What to Do About It](https://www.shawnmayzes.com/ai-engineering/your-ai-tooling-budget-is-unsustainable/): Uber burned through its entire annual AI budget in four months. Most teams don't notice the problem until it's already a crisis. Here's how to diagnose token waste and fix it before your CFO asks.
- [From $500/Day to $0: Investigating Local LLM Inference for Heavy Claude Code Users](https://www.shawnmayzes.com/ai-engineering/local-llm-inference-investigation-claude-code/): I'm spending serious money on Anthropic every week running Claude Code across multiple parallel projects. Before I pull the trigger on a Mac Studio, I'm sharing my full analysis - the cache hit math, the quality tradeoffs, and why the answer isn't as simple as it looks.
- [Prompt Injection: The Hidden Risk in Copy-Paste AI Culture](https://www.shawnmayzes.com/ai-engineering/prompt-injection-the-hidden-risk-in-copy-paste-ai-culture/): Copy-pasting AI prompts from the internet is convenient - but dangerous. Learn how malicious prompts can steal your secrets, leak private data, and what you can do to protect yourself.
- [Chrome DevTools MCP: AI Agents Can Finally See What They Build](https://www.shawnmayzes.com/ai-engineering/chrome-devtools-mcp-ai-agents-can-finally-see-what-they-build/): AI coding agents write code fast, but they can't see what breaks in the browser. Chrome's new DevTools MCP server changes that—giving AI the debugging tools developers rely on every day.
- [The Real Risks of Relying on AI to Speed Up Coding — And How Teams Win When They’re Smart](https://www.shawnmayzes.com/ai-engineering/the-hidden-pitfalls-of-relying-on-ai-to-speed-up-coding/): AI can speed delivery but often hides costs. This article outlines the most common pitfalls in AI-assisted coding—missed edge cases, security gaps, and technical debt—and shows practical workflows teams use to ship responsibly.
- [AI‑Native Development: How I Combined Claude Code, Zencoder, and Codex‑Style Parallel Agents](https://www.shawnmayzes.com/ai-engineering/ai-native-development-parallel-agents-claude-code-zencoder-codex/): A practical blueprint for an AI‑native engineering pipeline that pairs repo‑aware generation and validation with parallel agents. What changed, how it works, and how to implement it without breaking your team’s workflow.
- [How Wispbit MCP Solved My AI Code Quality Problem](https://www.shawnmayzes.com/ai-engineering/wispbit-mcp-revolutionizing-ai-code-quality/): AI agents write a lot of code, but most of it needs work. Here's how Wispbit's MCP integration turned my AI coding workflow from chaotic to consistent.
- [Running Claude Code Locally Just Got Easier with ollama-code](https://www.shawnmayzes.com/ai-engineering/running-claude-code-locally-just-got-easier-with-ollama-code/): A lightweight wrapper around Ollama that mimics Claude Code's development experience using open models like codellama, deepseek-coder, or codestral locally.
- [Spec-Driven Development: Keeping the Vibe, Adding a Plan](https://www.shawnmayzes.com/ai-engineering/spec-driven-development/): Discover how spec-driven development combines the creative flow of AI pair programming with the structure needed for production-ready applications. Learn why vibe coding breaks down at scale and how specifications can guide AI to build better, more maintainable software.
- [Extending AI's Memory: RAG, CAG, Long Contexts and Vector Search](https://www.shawnmayzes.com/ai-engineering/extending-ais-memory-rag-cag-long-contexts-and-vector-search/): Learn how RAG, CAG, vector databases, and long context windows are revolutionizing AI systems. Discover strategies to reduce hallucinations, implement efficient retrieval, and build more reliable AI applications with grounded data.
- [Building an AI-Powered Code Review System: A Technical Deep Dive](https://www.shawnmayzes.com/ai-engineering/building-ai-code-review-system/): Learn how to build CodeBot, a Laravel-based system that automatically reviews GitHub pull requests using Google Gemini and Anthropic Claude. This technical deep dive covers architecture decisions, implementation challenges, and production-ready patterns for AI integration.
- [Zencoder vs Cursor vs Claude Code: Why I Made the Switch](https://www.shawnmayzes.com/ai-engineering/zencoder-revolutionizing-ai-coding-with-repo-grokking/): Zencoder vs Cursor vs Claude Code - an honest comparison from someone who used all three daily. Here's what Repo Grokking and custom agents do that the others can't, and when Zencoder actually wins.
- [AI-Driven Development: Streamlining Product Engineering with MCP, Linear, and Cursor](https://www.shawnmayzes.com/ai-engineering/ai-driven-development-mcp-linear-cursor/): Learn how integrating Linear's MCP server with Claude and Cursor transforms product development workflows. See how to generate architectural guidelines automatically from tickets, enabling AI to understand context and speed up development cycles while maintaining code quality.
- [Comprehensive guide for product engineers on building Success](https://www.shawnmayzes.com/ai-engineering/building-ai-driven-products-strategies-for-success/): A comprehensive guide for products. Learn 5 key strategies including problem-first thinking, data foundations, explainable systems, and thoughtful human-AI relationships. Avoid common pitfalls engineers on building successful AI-driven products. Learn 5 key strategies including problem-first thinking, data foundations, explainable systems, and thoughtful human-AI relationships. Avoid common pitfalls and create products that deliver real user user value.
- [Running Claude Code with a Local LLM: A Step-by-Step Guide](https://www.shawnmayzes.com/ai-engineering/running-claude-code-with-local-llm/): Learn how to set up Claude Code with a local large language model (LLM) using the code-llmss project. This guide walks you through installation, configuration, and real-world use cases for developers who want AI-powered coding assistance without relying on cloud-based services.
- [Balancing AI Capabilities and User Experience](https://www.shawnmayzes.com/ai-engineering/balancing-ai-capabilities-and-user-experience/): Learn how to create AI products that are both technically impressive and user-friendly. This guide offers practical strategies for finding the perfect balance between advanced AI capabilities and intuitive user experiences.