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Browse this website posts across architecture, delivery, product systems, and the public writing footprint connected to this site.
Zero-downtime deploys on a cheap VPS
Field notes
485 published articles. Essays written here open in place; older tutorials take you back to the site where they first appeared.
Yes—but only with rigorous guardrails, human oversight, and strict boundaries. Real incidents show what happens when you skip these.
CareerMost academic-industry collaborations stall on logistics, not ideas — mismatched timing, evidence standards, and what actually counts as progress. Here's a model that holds up.
AI / MLYes—but only with rigorous guardrails, human oversight, and strict boundaries. Real incidents show what happens when you skip these.
AI / MLThe standalone prompt engineering role faded by 2026. But the skill became non-negotiable. Here's what really happened.
ArticleMost AI automation agencies are resellers marking up no-code platforms. Learn to spot the difference between real builders and thin wrappers—and evaluate vendors before you sign.
TutorialVoice agents that update CRM and book calendars need bulletproof sync. Learn webhook patterns, idempotency guards, and conflict resolution that keep data clean.
Web DevTechnical SEO isn't optional—it's the infrastructure layer that determines whether your site can be found, ranked, and trusted. Here's what developers actually need to own.
Cloud / DevOpsCloud scaling drives bills higher faster than revenue. Learn proven patterns for horizontal scaling, caching strategies, database optimization, and monitoring-driven capacity planning that keep costs aligned with actual demand.
TutorialA strong agent prompt separates reliable automation from chaos. Learn what distinguishes effective agent prompts from ones that fail in production.
TutorialWhen and how to safely transition from Zapier to a custom-built automation system without breaking your workflows. A realistic guide to incremental migration.
CareerA research mindset doesn't cost you speed — it sharpens the assumptions under everything you ship faster. Here's how that actually plays out on a product team.
CareerFractional CTOs provide strategic technology leadership without full-time commitment. But not every startup needs one—here's when they actually matter.
ArticleAI vendors make big promises. Here's the checklist to verify they can deliver—and what to protect before you sign.
AI / MLHallucinating agents fabricate information confidently. Learn the five root causes—missing retrieval, insufficient context, ambiguous prompts, temperature settings, and no verification—with practical fixes for each.
AI / MLVoice AI agents handle accents and languages through multi-component pipelines combining speech recognition, language detection, and voice synthesis—each with different robustness levels and failure modes.
TutorialSelf-hosting or cloud convenience? Pricing at scale? We break down n8n and Make.com across 6 dimensions—architecture, cost, ecosystem, and when to use each.
FinTechFinance-aware doesn't mean building for every edge case up front. It means being deliberate about traceability, correctness, and downside control — and disciplined about everything else.
TutorialLearn to build AI-assisted lead scoring in HubSpot using custom properties, behavioral signals, and enrichment APIs—then automate workflows that actually convert.
AI / MLSelf-hosting AI agents is technically possible but economically justified only for high-volume, privacy-critical, or edge-deployment scenarios. The GPU hardware, electricity, and ops burden often exceed hosted API savings.
AI / MLLLM APIs scale in cost with usage. Learn concrete tactics—prompt caching, model routing, output control, and batching—to cut expenses 40-90% without compromising results.
AI / MLSystem prompts shape AI behavior persistently; user prompts ask specific questions. Understand the distinction to build better agents and get better results.
TutorialFour pillars of AI agent testing: golden datasets, LLM-as-judge evaluation, red-teaming, and shadow deployment. A practical guide to catching failures before production.
AI / MLAI models don't just retrieve memorized answers. They calculate probabilities for each word and make random choices—by design. Here's why, and when it matters.
CareerCustomer ten and customer one thousand are solved by completely different work. Paul Graham's advice to "do things that don't scale," Stripe's Collison installation, and Airbnb's Craigslist integration are all the same answer to the same early problem: there is no channel yet, so you have to be the channel.
AI / MLFunction calling lets LLMs request external tools and APIs to accomplish tasks beyond text generation. Here's how it works and why it matters for AI agents.
FinTechThe same job title, the same SOC code, the same skills — and BLS data puts the national spread between the 10th and 90th percentile developer at over $130,000 a year before you even bring geography into it.
CareerExpert pricing guide for hiring freelance AI developers. Navigate rates, red flags, and what experience levels deliver.
ArticleNo-code automation is excellent until it isn't. Learn where it excels, when it breaks, and the clear signals that you need to graduate to custom development.
ArticleAI tools are transformative but risky. Learn how to safely use them with customer data—from retention controls to vendor agreements to what you should never send.
AI / MLEmbeddings convert text into numerical patterns that capture meaning, not just characters. Here's how that powers semantic search and RAG, and why the embedding model you pick usually matters more than the LLM.
AI / MLProprietary models offer reliability, but open-source alternatives now deliver competitive reasoning. A practical framework for evaluating quality, cost, privacy, and control.
A working notebook
“Some ideas belong here because they connect directly to projects and services.
Older tutorials still live on Medium, where people first found them. This page keeps the trail intact without pretending everything was published in one place.
How I choose a topic
I would rather publish one useful explanation from lived work than five summaries of things everyone already knows.
Step 01
A topic usually starts as the second or third time the same engineering, product, hiring, or research question lands on my desk.
Step 02
I look for a shipped system, a measured result, a failed approach, or a public artifact that keeps the argument honest.
Step 03
Most technical choices touch something else. The useful links are the ones that help a reader follow that chain without opening fifteen tabs.
Step 04
Some pieces belong on this site; others already have a life elsewhere. I keep the original destination and publishing history intact.
Topics covered
The recurring technical and strategic themes represented across this archive.
A quick orientation
The practical details behind this mixed archive.
Those pieces were published there first. I would rather send you to the original article—with its date, responses, and history—than create a duplicate here.
Thirty-five posts are enough to become noisy. The filters separate original essays from outside tutorials, and permanent page links make it easier to pick up where you left off.
Usually. The essays here tend to connect a technical decision to the project, service, or research context behind it. External posts are often narrower, practical guides.
Please do. Real questions are where the best pieces start. Send the context, what you have already tried, and the part that still feels unclear.
Next step
You do not need a polished brief. A bottleneck, an uncertain architecture decision, or a product idea that refuses to become concrete is enough to start.