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Field notes for the AI-native company.
Analysis, patterns, and sharp observations from the work of building with AI.
Featured · AI Engineering
Building an AI-Native SDLC
Breaking down MetaHarness, the system behind Tenex's SDLC, the principles it runs on, and what changes when coding agents become partners in development.
Aug 5, 2026 · 19 min read
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AI Adoption
HyperFrames Studio: Beginner's Guide + Honest Review (2026)
How to get started with HyperFrames Studio, HeyGen's free AI video editor: setup, 5 real builds, free prompts, and an honest good/bad/ugly verdict.
Oct 9, 2026 · 9 min read
AI Engineering
Does Your AI Agent Actually Work? A Guide to Eval-Driven Development
Hand-testing a few prompts won't tell you if an agent is ready to ship. Learn the building blocks every eval platform shares, and a five-step loop for turning production failures into tests that keep them from coming back.
Oct 2, 2026 · 11 min read
AI Adoption
How to Build a Claude Skill by Letting Claude Interview You
I thought Claude connectors were bloat until I needed one. Here's how I built a Claude skill in my first week working at Tenex — plus the template I'm giving away so you can build your own.
Sep 2, 2026 · 10 min read
AI Engineering
Kimi K3, explained: how forgetting made the biggest open model possible
K3's answer is selective memory: preserve exact history in some layers and let the rest update a fixed state. That is how forgetting made a model this large practical.
Jul 30, 2026 · 18 min read
AI Governance
The Citizen SDLC
A six-stage lifecycle that takes what non-technical employees build with AI from personal prototype to production the whole company can rely on.
Jul 16, 2026 · 16 min read
AI Fundamentals
The Machine That Learned to Pay Attention
Part B of the series: follow one ambiguous word through a transformer, station by station, from tokenizer to attention to the dice roll that picks the next word — plus the remodels and challengers reshaping modern models.
Jul 16, 2026 · 17 min read
AI Fundamentals
Vectors Are All You Need
Part A of a series that builds modern AI from the ground up: how words become vectors, why the dot product runs everything, and how a machine learns by nudging numbers until it stops being wrong.
Jul 8, 2026 · 14 min read
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