Specifications Are the New API Between Product and Engineering
Picture this. Your team just adopted an AI coding agent. Cursor, Claude Code, Copilot, it doesn’t matter which. The first week is electric. A developer promp...
Categories
- Engineering 18
- AI-Assisted Development 8
- AI Infrastructure 7
- Process 6
- AI 5
- Best Practices 5
- Cloud Native 3
- Product Management 3
- Career 2
- Enterprise AI 2
- MLOps 2
- Go 2
- Leadership 2
- Security 1
- Software Development 1
- Startup 1
- Cloud 1
- Infrastructure 1
- Tooling 1
- Culture 1
- Kubernetes 1
- Agentic AI 1
- Distributed Systems 1
- Open Source 1
- Philosophy 1
- Actualyze 1
Engineering
From PRFAQ to Backlog: How Amazon’s Working Backwards Process Becomes an AI Pipeline
In my previous post on Amazon’s Working Backwards SDLC for SMBs, I walked through the structured artifact chain (personas, use cases, PRFAQ, capability maps,...
The Missing Half of AI-Assisted Development
There’s a growing conversation in the industry about building a “Cursor for product management,” an AI-native system focused on helping teams figure out what...
Amazon’s Working Backwards SDLC: A Practical Guide for SMB Engineering Teams
Amazon’s software development lifecycle is one of the most effective product development processes ever created. It has produced AWS, Kindle, Prime, Alexa, a...
Onboarding Our Founding Engineering Team
Today I’m onboarding the founding engineers at Actualyze. I’ve worked with all of them before. Excited to be getting the band back together.
Getting Started with the CNCF Cloud-Native AI Stack: A Practical Guide for New Engineers
If you’re a new engineer looking to understand the CNCF Cloud-Native AI (CNAI) ecosystem, you’re entering at exactly the right moment. The stack has matured ...
What KodeOps Means: Unified SDLC Automation
The name KodeOps is deliberate. Just as DevOps unified development and operations, KodeOps unifies the entire software development lifecycle under a single a...
Introducing KodeOps: Open Source SDLC Automation
In my year-end reflections, I mentioned that I’d be sharing more of my work through open source releases in the coming year. Today, I’m delivering on that pr...
The LLM Complexity Gap: Why No-Code Works for Web UIs But Not for Distributed Systems
LLMs have democratized software development in ways that seemed impossible just a few years ago. Tools like Lovable.com, Bolt.new, and v0.dev let non-technic...
Why Go is the Best Language for Production-Grade Agentic AI and Orchestration
A Personal Perspective
Choosing the Right Kubernetes Development Environment: Why KIND Wins for Enterprise AI Platforms
When you’re building a platform that runs on Kubernetes, you need a local development environment that doesn’t lie to you. The choice matters more than most ...
Building High-Performance Engineering Culture: Mission, Vision, and Tenets
Every high-performance engineering team needs a foundation. Not the technical stack-that’s the easy part. The foundation that matters is shared understanding...
The IDE Doesn’t Matter: A Philosophy for LLM-Powered Code Generation
LLMs are transforming how we build software. They can generate entire functions, refactor complex modules, and implement features faster than ever before. Bu...
Working Backwards with SDLD: Building a Go Service with Mage
Written in the working-backwards narrative style we use for launch docs.*
Spec-Driven Development: A Comprehensive SDLC for AI-Assisted Software Engineering
Modern software development teams face a fundamental tension: AI assistants dramatically accelerate code generation, but without structured workflows, this s...
The SDLD Specification Format: A Canonical Reference
A comprehensive guide to the SDLD specification format for LLM-assisted software development.
Spec-Driven LLM Development (SDLD): Precise Engineering Through Specifications
LLMs are transforming how we write code. They can generate entire functions, refactor complex modules, and implement features faster than ever before. But th...
re:Invent 2025: AWS Frontier Agents and Developer Tools
Last day at re:Invent. Want to share notes on the AWS developer tools announcements.
AI-Assisted Development
Specifications Are the New API Between Product and Engineering
Picture this. Your team just adopted an AI coding agent. Cursor, Claude Code, Copilot, it doesn’t matter which. The first week is electric. A developer promp...
From PRFAQ to Backlog: How Amazon’s Working Backwards Process Becomes an AI Pipeline
In my previous post on Amazon’s Working Backwards SDLC for SMBs, I walked through the structured artifact chain (personas, use cases, PRFAQ, capability maps,...
The Missing Half of AI-Assisted Development
There’s a growing conversation in the industry about building a “Cursor for product management,” an AI-native system focused on helping teams figure out what...
The IDE Doesn’t Matter: A Philosophy for LLM-Powered Code Generation
LLMs are transforming how we build software. They can generate entire functions, refactor complex modules, and implement features faster than ever before. Bu...
Working Backwards with SDLD: Building a Go Service with Mage
Written in the working-backwards narrative style we use for launch docs.*
Spec-Driven Development: A Comprehensive SDLC for AI-Assisted Software Engineering
Modern software development teams face a fundamental tension: AI assistants dramatically accelerate code generation, but without structured workflows, this s...
The SDLD Specification Format: A Canonical Reference
A comprehensive guide to the SDLD specification format for LLM-assisted software development.
Spec-Driven LLM Development (SDLD): Precise Engineering Through Specifications
LLMs are transforming how we write code. They can generate entire functions, refactor complex modules, and implement features faster than ever before. But th...
AI Infrastructure
Production AI Inference on Your Laptop in 8 Minutes: Mastering KServe with kFabric
Deploy Production-Like AI Inference Infrastructure on Your Laptop – In Eight Minutes
Getting Started with the CNCF Cloud-Native AI Stack: A Practical Guide for New Engineers
If you’re a new engineer looking to understand the CNCF Cloud-Native AI (CNAI) ecosystem, you’re entering at exactly the right moment. The stack has matured ...
The LLM Complexity Gap: Why No-Code Works for Web UIs But Not for Distributed Systems
LLMs have democratized software development in ways that seemed impossible just a few years ago. Tools like Lovable.com, Bolt.new, and v0.dev let non-technic...
Why Go is the Best Language for Production-Grade Agentic AI and Orchestration
A Personal Perspective
Choosing the Right Kubernetes Development Environment: Why KIND Wins for Enterprise AI Platforms
When you’re building a platform that runs on Kubernetes, you need a local development environment that doesn’t lie to you. The choice matters more than most ...
KubeCon 2025: The Enterprise AI Infrastructure Moment Has Arrived
KubeCon + CloudNativeCon North America 2025 in Atlanta wasn’t just another cloud native conference. It was the event where the industry collectively acknowle...
The Enterprise AI Infrastructure Stack: From Proof of Concept to Production
Why 87% of AI Projects Fail (And How to Be in the 13% That Succeed)
Process
Amazon’s Working Backwards SDLC: A Practical Guide for SMB Engineering Teams
Amazon’s software development lifecycle is one of the most effective product development processes ever created. It has produced AWS, Kindle, Prime, Alexa, a...
The IDE Doesn’t Matter: A Philosophy for LLM-Powered Code Generation
LLMs are transforming how we build software. They can generate entire functions, refactor complex modules, and implement features faster than ever before. Bu...
Working Backwards with SDLD: Building a Go Service with Mage
Written in the working-backwards narrative style we use for launch docs.*
Spec-Driven Development: A Comprehensive SDLC for AI-Assisted Software Engineering
Modern software development teams face a fundamental tension: AI assistants dramatically accelerate code generation, but without structured workflows, this s...
The SDLD Specification Format: A Canonical Reference
A comprehensive guide to the SDLD specification format for LLM-assisted software development.
Spec-Driven LLM Development (SDLD): Precise Engineering Through Specifications
LLMs are transforming how we write code. They can generate entire functions, refactor complex modules, and implement features faster than ever before. But th...
AI
What KodeOps Means: Unified SDLC Automation
The name KodeOps is deliberate. Just as DevOps unified development and operations, KodeOps unifies the entire software development lifecycle under a single a...
Introducing KodeOps: Open Source SDLC Automation
In my year-end reflections, I mentioned that I’d be sharing more of my work through open source releases in the coming year. Today, I’m delivering on that pr...
Year-End Reflections: The Last 18 Months, and What Comes Next
As the year comes to a close, I’ve been reflecting on the last 18 months since leaving AWS. It’s been a long, focused chapter of deep work, and it’s now sett...
re:Invent 2025: AWS Frontier Agents and Developer Tools
Last day at re:Invent. Want to share notes on the AWS developer tools announcements.
Announcing ActualyzeAI
One year ago, I decided to leave Amazon Web Services to start my own company. Since then I’ve had the chance to meet some amazing people, build some incredib...
Best Practices
The IDE Doesn’t Matter: A Philosophy for LLM-Powered Code Generation
LLMs are transforming how we build software. They can generate entire functions, refactor complex modules, and implement features faster than ever before. Bu...
Working Backwards with SDLD: Building a Go Service with Mage
Written in the working-backwards narrative style we use for launch docs.*
Spec-Driven Development: A Comprehensive SDLC for AI-Assisted Software Engineering
Modern software development teams face a fundamental tension: AI assistants dramatically accelerate code generation, but without structured workflows, this s...
The SDLD Specification Format: A Canonical Reference
A comprehensive guide to the SDLD specification format for LLM-assisted software development.
Spec-Driven LLM Development (SDLD): Precise Engineering Through Specifications
LLMs are transforming how we write code. They can generate entire functions, refactor complex modules, and implement features faster than ever before. But th...
Cloud Native
Production AI Inference on Your Laptop in 8 Minutes: Mastering KServe with kFabric
Deploy Production-Like AI Inference Infrastructure on Your Laptop – In Eight Minutes
Getting Started with the CNCF Cloud-Native AI Stack: A Practical Guide for New Engineers
If you’re a new engineer looking to understand the CNCF Cloud-Native AI (CNAI) ecosystem, you’re entering at exactly the right moment. The stack has matured ...
KubeCon 2025: The Enterprise AI Infrastructure Moment Has Arrived
KubeCon + CloudNativeCon North America 2025 in Atlanta wasn’t just another cloud native conference. It was the event where the industry collectively acknowle...
Product Management
Specifications Are the New API Between Product and Engineering
Picture this. Your team just adopted an AI coding agent. Cursor, Claude Code, Copilot, it doesn’t matter which. The first week is electric. A developer promp...
From PRFAQ to Backlog: How Amazon’s Working Backwards Process Becomes an AI Pipeline
In my previous post on Amazon’s Working Backwards SDLC for SMBs, I walked through the structured artifact chain (personas, use cases, PRFAQ, capability maps,...
The Missing Half of AI-Assisted Development
There’s a growing conversation in the industry about building a “Cursor for product management,” an AI-native system focused on helping teams figure out what...
Career
Year-End Reflections: The Last 18 Months, and What Comes Next
As the year comes to a close, I’ve been reflecting on the last 18 months since leaving AWS. It’s been a long, focused chapter of deep work, and it’s now sett...
Announcing ActualyzeAI
One year ago, I decided to leave Amazon Web Services to start my own company. Since then I’ve had the chance to meet some amazing people, build some incredib...
Enterprise AI
KubeCon 2025: The Enterprise AI Infrastructure Moment Has Arrived
KubeCon + CloudNativeCon North America 2025 in Atlanta wasn’t just another cloud native conference. It was the event where the industry collectively acknowle...
The Enterprise AI Infrastructure Stack: From Proof of Concept to Production
Why 87% of AI Projects Fail (And How to Be in the 13% That Succeed)
MLOps
Production AI Inference on Your Laptop in 8 Minutes: Mastering KServe with kFabric
Deploy Production-Like AI Inference Infrastructure on Your Laptop – In Eight Minutes
The Enterprise AI Infrastructure Stack: From Proof of Concept to Production
Why 87% of AI Projects Fail (And How to Be in the 13% That Succeed)
Go
Why Go is the Best Language for Production-Grade Agentic AI and Orchestration
A Personal Perspective
Working Backwards with SDLD: Building a Go Service with Mage
Written in the working-backwards narrative style we use for launch docs.*
Leadership
Amazon’s Working Backwards SDLC: A Practical Guide for SMB Engineering Teams
Amazon’s software development lifecycle is one of the most effective product development processes ever created. It has produced AWS, Kindle, Prime, Alexa, a...
Building High-Performance Engineering Culture: Mission, Vision, and Tenets
Every high-performance engineering team needs a foundation. Not the technical stack-that’s the easy part. The foundation that matters is shared understanding...
Security
The Importance of a Secure Development Lifecycle
In today’s digital landscape, security is more crucial than ever. Cyber threats are evolving at an unprecedented pace, and the need to build secure software ...
Software Development
The Importance of a Secure Development Lifecycle
In today’s digital landscape, security is more crucial than ever. Cyber threats are evolving at an unprecedented pace, and the need to build secure software ...
Startup
Announcing ActualyzeAI
One year ago, I decided to leave Amazon Web Services to start my own company. Since then I’ve had the chance to meet some amazing people, build some incredib...
Cloud
re:Invent 2025: AWS Frontier Agents and Developer Tools
Last day at re:Invent. Want to share notes on the AWS developer tools announcements.
Infrastructure
Year-End Reflections: The Last 18 Months, and What Comes Next
As the year comes to a close, I’ve been reflecting on the last 18 months since leaving AWS. It’s been a long, focused chapter of deep work, and it’s now sett...
Tooling
Working Backwards with SDLD: Building a Go Service with Mage
Written in the working-backwards narrative style we use for launch docs.*
Culture
Building High-Performance Engineering Culture: Mission, Vision, and Tenets
Every high-performance engineering team needs a foundation. Not the technical stack-that’s the easy part. The foundation that matters is shared understanding...
Kubernetes
Choosing the Right Kubernetes Development Environment: Why KIND Wins for Enterprise AI Platforms
When you’re building a platform that runs on Kubernetes, you need a local development environment that doesn’t lie to you. The choice matters more than most ...
Agentic AI
Why Go is the Best Language for Production-Grade Agentic AI and Orchestration
A Personal Perspective
Distributed Systems
The LLM Complexity Gap: Why No-Code Works for Web UIs But Not for Distributed Systems
LLMs have democratized software development in ways that seemed impossible just a few years ago. Tools like Lovable.com, Bolt.new, and v0.dev let non-technic...
Open Source
Introducing KodeOps: Open Source SDLC Automation
In my year-end reflections, I mentioned that I’d be sharing more of my work through open source releases in the coming year. Today, I’m delivering on that pr...
Philosophy
What KodeOps Means: Unified SDLC Automation
The name KodeOps is deliberate. Just as DevOps unified development and operations, KodeOps unifies the entire software development lifecycle under a single a...
Actualyze
Onboarding Our Founding Engineering Team
Today I’m onboarding the founding engineers at Actualyze. I’ve worked with all of them before. Excited to be getting the band back together.