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Deep dives on AI, engineering best practices, startup strategy, and the future of technology from our team.
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Why we don't buy the hype around "democratized" AI infrastructure
A year of lessons, mistakes, and things I wish someone told me
Beyond the resume and the coding test
What we learned building 40+ products from scratch
Boring tech, fast results
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Why the biggest AI players are buying nuclear plants and what it means for everyone else
Why we don't buy the hype around "democratized" AI infrastructure
A year of lessons, mistakes, and things I wish someone told me
Beyond the resume and the coding test
What we learned building 40+ products from scratch
Boring tech, fast results
From chatbots to document processing, what actually works
How we actually choose models for production
Beyond the demo, what actually works at scale
What I tell engineers who ask me for career advice
How we helped an appraisal company automate with AI in 12 weeks
The gap between proof-of-concept and production isn't technical. It's everything else.
Spoiler: It's not your ability to reverse a binary tree on a whiteboard
The practical patterns we've learned from building AI systems that actually work in production
The infrastructure complexity trap that kills more startups than bad code
The sprint methodology that gets AI from concept to production
It's not about money, remote work, or perks. It's about something much deeper.
Stop overthinking it. Here's the decision framework that actually works.
From MVP concept to production-ready patient portal in record time
Hard-won lessons on which projects to avoid (and why we sleep better at night)
From millisecond fraud detection to 24/7 customer support, autonomous agents are handling tasks that used to require armies of analysts
The security, infrastructure, and data choices that actually matter
Why your recommendation engine isn't working and what actually drives sales
Why 70% of predictive maintenance projects fail and how to build models that work in production
Most companies break up their monolith too early or too late
From two-hour appraisals to instant valuations: how AI is reshaping real estate
Stop building your MVP with your nephew
How to design payment infrastructure that processes transactions in milliseconds
Building healthcare apps that patients actually use requires rethinking everything
Most B2B APIs are built for engineers who will never use them
Most retailers have the wrong data infrastructure for AI
The gap between rule-based automation and adaptive intelligence is costing banks millions
Why most healthcare cloud migrations fail and how to architect around the compliance trap
The technical decisions that make or break your path to product-market fit
Building financial apps that users actually trust with their money
Why most supply chain visibility projects fail and how to build dashboards that don't crash when you need them most
Stop treating contractors like outsiders and start building one cohesive team
Moving beyond monolithic platforms for enterprise-grade commerce experiences
Simple engineering tactics that slash AI inference costs without touching model performance
Stop wasting months on the wrong choice—here's how to decide fast
Why that "quick fix" is slowly killing your engineering velocity
The energy requirements for AI are creating an infrastructure arms race that's reshaping the entire tech landscape
Stop guessing at AI value. Here's how to measure the metrics that drive real business decisions.
Your legacy architecture isn't just slowing you down—it's killing your AI initiatives before they start
It's not scope creep or bad estimates—it's something much more fundamental
Individual heroics don't scale. Collective resonance does.
How to Actually Talk to Your Users (Before You Waste Six Months)
From millisecond fraud detection to 24/7 customer support, autonomous agents are handling tasks that used to require armies of analysts
Why the MVP mindset is killing your startup's chances
Why the best software systems mirror consciousness itself
The hidden infrastructure that makes or breaks AI projects in production
Moving beyond demos to bulletproof AI that actually works when it matters
A battle-tested framework for untangling decades of integration debt without breaking production
After building AI systems for 12+ healthcare companies, here's what actually moves the needle
Our insights come from real-world experience building products. Let's talk about how we can help with yours.
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