Blog

Engineering in depth

Technical content on architecture, performance, developer experience, and the craft of building software that scales.

AI AssistantsScopingProduct StrategyWorkflowsAI SystemsData FoundationsKnowledge SystemsArchitecture

39

Archive posts

29

On-site

10

External

1/5

Page

AI AssistantsScopingProduct StrategyWorkflowsAI SystemsData FoundationsKnowledge SystemsArchitectureTechnical LeadershipStartupsEngineering ManagementDeliveryResearch CollaborationUniversitiesProfessorsTechnical Writing
AI AssistantsScopingProduct StrategyWorkflowsAI SystemsData FoundationsKnowledge SystemsArchitectureTechnical LeadershipStartupsEngineering ManagementDeliveryResearch CollaborationUniversitiesProfessorsTechnical Writing

39

All posts

29

Original site essays

10

External links

10

Medium posts

Crawlable archive

Engineering in depth

39 published articles in this archive. Internal essays stay on-site and external posts open on their original platforms.

AI / MLFeatured

How to Scope an AI Assistant for Real Teams

The fastest way to waste time with AI is to scope the assistant too broadly. This guide explains how to define the first useful workflow instead.

AI AssistantsScopingProduct StrategyWorkflows
10 min readMarch 10, 2026Read article
AI / ML

How to Build AI-Ready Data Foundations Before Models

A practical guide to preparing data quality, permissions, freshness, lineage, and observability before layering assistants or agent workflows on top.

AI SystemsData FoundationsKnowledge Systems
9 minMar 2026
Read
Career

Technical Leadership for Startups Without Process Theater

How to add standards, architecture clarity, and better engineering judgment in startups without importing heavy process or slowing delivery.

Technical LeadershipStartupsEngineering Management
8 minMar 2026
Read
Career

What Professors Actually Need from Industry Research Collaborators

A practical look at how engineers can collaborate with professors, universities, and labs in ways that are rigorous, useful, and publication-friendly.

Research CollaborationUniversitiesProfessors
9 minMar 2026
Read
Web Dev

Designing Next.js Platforms That Stay Fast as Content Grows

Performance problems in large content platforms are usually architectural. This guide covers the decisions that keep Next.js systems fast as teams and pages grow.

Next.jsPerformanceSEO
10 minMar 2026
Read
Career

How to Prepare for Full-Stack and AI Engineering Interviews with Real Signal

Interview prep gets stronger when it is built around architectural reasoning, public artifacts, and project clarity instead of memorized trivia.

HiringInterviewsFull-Stack
9 minMar 2026
Read
Career

Designing Consulting Engagements That Create Momentum Instead of Dependency

A better consulting engagement makes teams faster and clearer over time instead of turning the consultant into the only person who understands the system.

ConsultingAdvisoryTechnical Leadership
8 minMar 2026
Read
AI / ML

How to Architect AI Systems That Survive Production

Production AI is not a model choice. It is an architecture choice. This piece covers why retrieval, evaluation, and fallback logic matter more than prompt cleverness.

AI SystemsArchitectureRAG
11 minMar 2026
Read
Career

How to Evaluate Open-Source Maintainers Before Hiring or Partnering

Open-source visibility is useful only if you know how to read documentation quality, maintenance taste, architectural clarity, and public reasoning.

Open SourceHiringDue Diligence
8 minFeb 2026
Read

Editorial model

Why the archive is split this way

01

On-site posts are written for deeper internal linking, stronger SEO coverage, and longer-form architectural explanation.

02

External posts remain linked to their original source so the canonical article stays where it was first published.

03

Source filters make it easier for readers and search engines to understand where content lives and how it relates.

04

Pagination is route-based so archive pages remain crawlable without client-only query state.

This archive intentionally combines original on-site essays with external writing so readers can evaluate one connected body of work while still respecting the canonical destination of outside posts.

Publishing system

How the archive grows

A content model shaped by production work, research-facing thinking, and public technical artifacts.

01

Start from repeated friction

The best articles begin with recurring technical, product, hiring, or research questions that keep showing up in practice.

02

Connect to evidence

Every useful article should connect to shipped systems, public projects, open source, or clearly scoped technical direction.

03

Link the knowledge graph

Articles should guide readers toward related services, projects, profiles, and adjacent essays instead of living in isolation.

04

Preserve canonical destinations

When a piece belongs on an external platform, the archive links outward instead of pretending the post was originally published here.

Topics covered

Archive taxonomy

The recurring technical and strategic themes represented across this archive.

AI AssistantsScopingProduct StrategyWorkflowsAI SystemsData FoundationsKnowledge SystemsArchitectureTechnical LeadershipStartupsEngineering ManagementDeliveryResearch CollaborationUniversitiesProfessorsTechnical WritingNext.jsPerformanceSEOContent PlatformsHiringInterviewsFull-StackAI EngineeringConsultingAdvisoryCollaborationRAGGuardrailsProductionOpen SourceDue DiligenceEvaluationCloud CostOptimizationData EngineeringObservabilityAWSAnalyticsPlatform EngineeringDeveloper ExperienceAdoptionInternal ToolsCase StudiesClient WorkHackathonsRoadmappingPrototypingMonorepoModernizationCI/CDPackage DesignMaintenanceAcademic PartnershipsResearchProduct ThinkingEngineering JudgmentFinTechProduct SystemsRiskMentorshipCode ReviewTeam GrowthFinancial EngineeringSystems ThinkingServerlessContainersCloud ArchitectureInfrastructureTechnical EvaluationWeb3BlockchainProduct DesignSmart ContractsReact NativeiOSXcodeAndroidBuild ConfigFundamentalsAWS LambdaPuppeteerNode.jsExpressScalingReact Three FiberPortfolio3DWeb WorkersQuantum ComputingPWASerwist

Archive FAQ

Common questions

A few quick answers about how the archive works.

Some articles were originally published elsewhere and remain canonical there. The archive keeps them visible while sending readers to the original source.

They make the archive easier to browse, easier to index, and easier to understand for both readers and search engines.

Yes. On-site essays are usually more tightly integrated with the rest of the portfolio through internal linking, related sections, and deeper context.

Absolutely. The best prompts for new writing usually come from real engineering, hiring, research, or product questions.

Want to turn these ideas into execution?

The archive is one way to evaluate how I think. Direct collaboration is where that thinking becomes implementation leverage.