Articles from 2025
23 articles published in 2025.
From Contractor to Consultant: The Mindset Shift That Changes Your Income
Contractors sell time. Consultants sell results. That distinction is the whole game. How I changed my pricing, positioning, and client selection once it clicked.
What the Teams Actually Shipping Coding Agents Have Figured Out
Coding agents are the most economically viable AI in production today. The patterns Devin, Cline, Amp, and others converged on, and what they mean for anyone building or using agents seriously.
Stop Shipping Features: Why AI Products Need an Experiment Mindset
12 features shipped in a quarter. Zero meaningful metrics moved. AI products aren't software projects. The roadmap is a hypothesis board, not a delivery schedule, and treating it otherwise is expensive.
Beyond Chunks: Why Faceted Context Is the Future of RAG
Chunk-based RAG returns results. Faceted context gives agents peripheral vision: an understanding of the information landscape that lets them navigate rather than just consume. What that looks like in a domain where getting it wrong matters.
Context Engineering: The Skill That Replaced Prompt Engineering
Prompt engineering is a symptom, not a skill. The engineers shipping better agents aren't writing better instructions. They're designing better information spaces. Context engineering is the meta-skill no one teaches.
Every Service Is Going to Need an MCP Layer
REST APIs were designed for humans calling services through UIs. AI agents are not humans. What breaks when you expose your existing APIs to agents, and what the right architecture looks like.
When English Became a Programming Language
v0 just proved that English plus AI can replace traditional web development for most apps. That changes what it means to be a developer. An honest take on what shifts, what doesn't, and what to do about it.
Fine-Tuning LLMs Without the RLHF Headache: The DPO Approach
RLHF is the right idea with the wrong implementation cost for most teams. DPO flips the math. How to align a healthcare AI model on clinician feedback without burning a month on reward model engineering.
Agency Beats Intelligence: How I Now Hire (And Evaluate Myself)
Raw intelligence is abundant and cheap. The engineers thriving in the AI era are the ones with agency: setting goals, acting under uncertainty, self-correcting. How I changed my interview process to find them.
You Are No Longer a Coder: The Shift from Execution to Direction
I stopped writing most of my own code. What changed, what I delegated to AI, what I found it can't do, and why the hardest part of the transition had nothing to do with technology.
Context Rot: The Silent Performance Killer in Your LLM Application
Your LLM system works great in demos and degrades in production. The culprit is almost never the model. It's what you're feeding it. How to diagnose and fix context rot before it kills your product.
Why Your AI Gets Smarter When You Let It Think Longer
Test-time compute is the most underused lever in production AI right now. What chain-of-thought, best-of-N sampling, and process reward models mean for practitioners, and when to use them instead of grabbing a bigger model.
The Async-First Engineering Team: What Actually Works (And What Doesn't)
I went async-first with my remote engineering team. Productivity went up. Culture took a hit. What changed, what broke, and the specific practices that made it worth it.
What the AI Tool Ecosystem Is Actually Telling You
Tool selection in healthcare AI is a compliance problem, not a productivity one. Most AI tools that sounded great in 2023 are dead or deprecated. The framework I use for betting on the right ones.
What Autonomous Vehicles Taught Me About Multi-Agent AI Design
BAIR researchers discovered that just 5% autonomous vehicle penetration can smooth all highway traffic, with no central coordination. That finding reshapes how I think about building multi-agent AI systems.
The Death of Institutional Memory: Why I'm Building Atlas (And Why It Matters)
Every resignation takes a piece of the organization nobody wrote down. Org charts capture hierarchy, not the relationship networks that keep things running. A different approach to preserving institutional knowledge before it walks out the door.
Vision + Language: How Multimodal LLMs Actually Work (And When to Use Them)
Multimodal LLMs integrate vision through two fundamentally different architectures. Knowing which one you need, and why, shapes every other technical choice in your build.
The Self-Healing Stack: What AI-Native Infrastructure Actually Means
The AI Cloud vision, where infrastructure monitors, optimizes, and repairs itself, is compelling. Some of it exists today. Most doesn't yet. What self-healing infrastructure looks like in practice, and what engineers should be doing to prepare.
FHIR Meets Graph Databases: Exploring Healthcare's Natural Network Structure
FHIR data is a graph. Treating it as flat tables is why most healthcare AI struggles with relationships between patients, providers, and encounters. What happens when you model it the way it actually is.
The Tools I Dropped When AI Changed My Development Workflow
AI coding assistants forced a full rethink of every layer of the dev stack. What I dropped, what I added, and the principle behind the restructuring.
From GPT-2 to DeepSeek: The Architectural Changes That Actually Mattered
I've been reading ML papers for 10 years. Most don't matter. These architectural choices did. RoPE, GQA, SwiGLU: each one solved a real scaling problem. What to look for when a new model claims 'better architecture.'
Building a GenAI Platform That Doesn't Collapse Under Its Own Weight
GenAI platforms don't fail because the models are bad. They fail because teams build everything at once. A practitioner's guide to layered architecture, from the minimal production-ready core to healthcare-grade guardrails.
The GenAI Strategy Question You're Not Asking (But Should Be)
Everyone asks 'how should we use GenAI?' The honest answer requires a harder question: does AI's unique capability create new value here, or is it just a more expensive way to do something that already worked? A practitioner's framework for getting this right in healthcare.