Why AI-Generated Plans Need Visual Review, Not More Text
AI solved the generation problem and created the comprehension problem. The bottleneck is no longer output volume. It is review surface area.
Engineering
33 articles exploring engineering
On-Device AI Comes of Age, but Hardware Still Sets the Limits
Compact models run offline on phones, laptops, and edge devices. The bottleneck is no longer model capability. It is RAM, memory bandwidth, and thermal headroom under sustained load.
MD vs MDX: The Decision Most AI-Agent Repos Get Wrong
Markdown is a storage format. MDX is an execution format. Every AI coding tool chose .md for agent instructions. The distinction explains why, and when MDX earns its place.
CTO vs VP of Engineering: The Org Split That Most Companies Get Wrong
The structural signal for splitting CTO and VP Engineering roles isn't headcount — it's a specific week when strategy and delivery both need full attention. A founder's decision framework with real failure modes.
Context Engineering: The Operating Discipline for Reliable AI Systems
Why AI output depends on how teams assemble and retrieve context - not on prompting. A 7-metric measurement framework with 8 charts for engineering teams.
Vector Databases in 2026: Why Most Teams Adopt One Too Early
Most teams adopt a dedicated vector database before the production signals that justify it arrive. A decision framework for when pgvector stops being enough.
Document Parsers for Agentic Workflows: LiteParse, LlamaParse, and the Tools That Actually Matter
Benchmark-driven comparison of the 2026 document parsing landscape - LiteParse, LlamaParse, Unstructured, Docling, PyMuPDF, Google Document AI - with Python code, failure modes, and an async routing architecture.
LLM SEO: Rank in Google and Get Cited by AI Search in 2026
Three-wave audit that serves Google ranking and LLM citation simultaneously - fix crawl health, add entity disambiguation in structured data, and open AI crawler channels.
Improving PageSpeed Insights Score: 17 Points Gained, Every Fix Documented
A real audit case study - three rounds, 17 mobile score points gained, every fix shown. The systematic PageSpeed Insights approach that catches what visual QA misses.
The Second Bill: How AI Agents Create Costs Your FinOps Team Can't See
AI agents create a second bill: invisible to FinOps, landing on the wrong invoice, and breaking every financial model built for linear AI costs.
You Are a Senior Engineer: Why That Prompt Is Wrong
Expert persona prompting reduces factual accuracy by 3.6 points. Here are the four patterns that actually work - with a decision table and real session data.
Knowledge Graphs for AI Coding: What the Tools Actually Build (and What I Measured)
Most tools marketed as knowledge graphs for AI coding are dependency graphs. I built three production KGs, ran the experiments on LangChain, and the results were not what the vendors claimed.
The Phantom AI Strategy: How to Tell in 30 Minutes if a Company Is Actually AI-Native
Every company says it's AI-first. After 30+ CTO interviews, I can tell you exactly which questions reveal the ones that aren't - and what the real ones say instead.
Which Frontend Framework Wins in the AI Era
Framework choice is no longer about developer ergonomics. In an AI-driven era, the winners will be frameworks that resist entropy, enforce constraints, and scale safely under continuous AI modification.
The AI Coding Shift: Why Strongly-Typed and Compiled Languages May Win
For 30 years, language choice was driven by developer productivity. AI changes the equation. When machines generate code, verification matters more than velocity.
Why PostgreSQL Is Your Best Bet for AI Projects (And You Probably Already Have It)
Stop over-engineering AI infrastructure. PostgreSQL already has everything you need: pgvector for embeddings, pgai for automation, TimeScaleDB for metrics. Build faster by using what you have.
The 2% Problem: Why AI Harness Beats Model Capability
Production AI systems are 98% harness, 2% model. New research reveals why architecture, permissions, and safety matter more than model capability - and how to build systems that actually work.
The 5 Files You Must Still Review in the Age of AI-Generated Code
AI writes 80% of my code. I still review 100% of these 5 file types. A blast-radius framework ranking what to review line-by-line, and what to trust.
The Haiku-First Engineer: Why Smaller Models Make You Better at Building
Smaller, constrained AI models force clarity and structure. I build faster with Haiku than Opus because constraints eliminate bad habits. Here's why.
Airflow vs Prefect vs Dagster: The Production Migration Guide (2026)
After running all three in production: 20-criteria breakdown of real migration costs, team overhead, backfill behaviour, and which orchestrator survives 500+ pipelines.
Building Your Personal Stack Overflow: A Knowledge Management Journey
A journey building issue-search-skill: capturing errors once, retrieving solutions forever. Local-first knowledge management that resolves recurring issues 12x faster.
SaaS Metrics Stack: ARR, MRR & Churn You Can Actually Trust
How to build a SaaS metrics stack that produces ARR, MRR, churn, LTV, and CAC you can actually defend - with SQL, Python, and the right source-of-truth hierarchy.
The Only AI Coding Tool Comparison That Matters in 2026
Most AI coding tool comparisons still reward the wrong things. A workflow-first breakdown of Claude Code, Cursor, Copilot, Windsurf, and Antigravity through the lens that actually matters: how teams ship under real constraints.
The Hidden Cost of AI-Generated Code (and How to Fix It)
AI-generated code feels fast, but the maintenance cost appears later. Why AI creates locally correct but globally fragile systems, and the engineering standards that fix it.
From Prompt to System: Building AI Workflows That Actually Run
Why one-off prompting does not compound, and how to move from isolated prompts to repeatable AI workflows using playbooks, MCP data sources, and action layers.
Claude Code Project Structure That Actually Scales: Patterns, Templates & Real Examples
A battle-tested blueprint for Claude Code projects that stay predictable at 50+ files - folder layout, .claudeignore, skills architecture, and 3 ready-to-copy templates.
The 10 Most Valuable MCP Servers for Modern AI Workflows
The MCP servers that matter most for real AI leverage: analytics, email, calendar, GitHub, databases, observability, SEO, social, docs, and file storage. Plus practical playbooks for turning them into repeatable workflows.
The Most Important Claude Code Skills for Modern Web Development
The 10 Claude Code skills that now separate developers who merely generate from those who ship differentiated products. From UI taste and frontend structure to brand systems and skill creation.
How I Increased Delivery Speed by Doing Less, Not More
The uncomfortable truth: faster delivery doesn't come from working harder. It comes from structure. How I went from 6-month delivery cycles to weekly releases by investing in the unglamorous side of engineering - org design, clarity, and ruthless prioritization.
I Built My Own Portfolio From Scratch (Here's What Bit Me)
A CTO's honest account of building a personal portfolio site from scratch - the decisions that made sense at the time, the bugs that didn't, and what I'd do differently.
Cut Claude Code Token Usage by 60–90%: 16 Proven Techniques
Battle-tested techniques for .claudeignore, context compression, and multi-agent task splitting that cut token usage by 60–90% without losing Sonnet's predictive accuracy.
Building API Dev Utils: A 400+ Tool Developer Platform
From a simple JSON formatter to a 400+ tool developer platform serving 100K+ users - the complete engineering journey covering architecture, zero-backend design, performance, and deployment.
Cloud Cost Reduction Without Slowing Engineering: CTO Playbook
How to cut cloud spend 30–60% without freezing delivery velocity - using cloud credits, right-sizing, commitments, and platform guardrails that engineering teams actually adopt.