Deconstructing AI engineering through the lens of systems thinking.
A public research log exploring the messy reality of building with AI. No hype-just hands-on experiments, cognitive models, and honest lessons from an aspiring engineer learning in public.
Deep insights
Unpack complex AI systems with practical, long-form analysis and frameworks.
Built for builders
Actionable guidance for engineers and technical leaders, not just theorists.
Better outcomes
Make smarter trade-offs, avoid hidden risks, and create scalable impact.
Explore ideas and frameworks for building intelligent systems.
In-depth essays and practical notes on AI engineering, systems thinking, and the real-world trade-offs behind building with intelligence.
Hands-On Experiments
Ghi chép lại những công cụ mình đã thử nghiệm và cách chúng hoạt động (hoặc thất bại).
Systems Thinking
Causal diagrams, feedback structures, and systems logic applied to AI integrations.
Mental Models
Frameworks for reasoning clearly under complexity — from first principles to cognitive biases.
Learning Log
Behind-the-scenes logs of building, shipping, failing, and learning in public.
The signal in the noise.
When AI Becomes a Crutch: The Mental Health Data No One Wants to Talk About
1.2M users/week discuss suicide with ChatGPT. MIT/OpenAI RCT shows AI use correlates with loneliness. A careful look at the evidence — without alarmism or dismissal.
Long-form, obsessively researched.
The Deskilling Ledger: What You Lose Every Time You Let AI Think For You
CHI 2025 found 40% of AI-assisted tasks involved zero critical thinking. A framework for understanding cognitive offloading costs — and when the tradeoff is worth it.
The 5.5% Inconvenient Truth About Enterprise AI ROI
McKinsey found 88% of orgs use AI but only 5.5% achieve real business impact. A structural analysis of why most enterprise AI investment produces no measurable value.
The 19% Problem: Why Your AI-Assisted Code Is Slower Than You Think
METR's RCT found developers 19% slower with AI despite predicting 20% faster. A rigorous look at the 39-point perception gap and what it means for your workflow.
AI in 2026: A Clear-Eyed Map of Real Opportunities and Real Risks
A rigorous, evidence-grounded analysis of where AI creates genuine leverage and where it introduces real risk in 2026 — without the hype or the alarm. Decision frameworks for engineers, founders, and knowledge workers.
The Expanding Attack Surface: Security Risks When AI Agents Run Your Business
As AI agents gain autonomous tool access — browsing, writing, executing code — the attack surface expands dramatically. A rigorous breakdown of prompt injection, data exfiltration, and agentic risk for individuals and organizations.
10 Shifts in AI Operational Mindset You Need in 2025
Most teams use AI wrong—not bad tools, but bad mental models. Here are 10 operational mindset shifts separating teams capturing real value from those stuck
Writing at the
intersection of
machines & minds.
"We don't need more AI hype. We need clearer thinking about what these tools actually do — and what they ask of us in return."
Tech&MindSet Lab is a reader-supported publication studying the overlap of cognitive psychology and production AI systems.