Insights

Notes from
the build.

How production AI actually gets made — models, agents, web data, and the unglamorous engineering that keeps it standing. No hype, no AI-generated filler. One deep piece a week.

01

Why most AI agents die in production

They demo beautifully and break on contact with reality. The five failure modes nobody designs for, and the math of multi-step reliability.

ReliabilityAgents
Jun 13
8 min
02

Which LLM should you actually use in 2026?

A builder's decision tree — by task, latency, and cost, and where each model quietly falls apart.

ModelsDecisionComing
Jun 20
10 min
03

Businesses only buy two things from AI

More customers, or less cost. Every agent worth building ladders to one of them — here's how to tell which.

StrategyComing
Jun 27
6 min
04

RAG that doesn't hallucinate

Retrieval, citations, and evals — how to make a knowledge agent your legal team will actually trust.

RAGEngineeringComing
Jul 4
9 min
05

The legal way to scrape the web

ToS, robots.txt, rate limits, and where the lines actually are — without becoming someone's lawsuit.

Web DataLegalComing
Jul 11
9 min
06

How bot detection works — and how to protect your site

Fingerprinting, behavioral signals, and the defensive playbook for keeping bad traffic out.

SecurityDefenseComing
Jul 18
11 min
07

Why your AI tools should be bring-your-own-key

Who controls the key, who pays the model bill, and why BYOK is the trust unlock for 2026.

StrategyCostComing
Jul 25
5 min
08

Predict, then cut: forecasting as a cost-killer

Demand, churn, and failure prediction — acting before the cost lands instead of cleaning up after.

MLCostComing
Aug 1
7 min