The Applied AI Handbook
A six-stage handbook for shipping applied AI: decide, design, build, evaluate, operate, cost, each linked to the reference material behind it.
Read → Topics
Strategy & Architecture
Build, buy, or skip; lock into one model provider or stay agnostic — these architectural calls compound over the life of a system. This is our work on making them deliberately instead of by default.
Start with The Applied AI Handbook if you're deciding what to build. It's for leaders weighing build-vs-buy and architecture calls that compound over the life of a system.
Guides#
Choosing an AI Delivery Partner
How to interrogate any AI delivery partner, us included, across every gate that matters, and the cases where we're the wrong call.
27 min read Read →The Agent Adoption Playbook
The pilot worked. Here is how the rest of your engineers start using it, and the numbers that separate real adoption from seat activation.
33 min read Read →Architectures#
An assistant inside a product you already ship
An assistant embedded in a product you already ship. It is scoped to the signed-in user's own data and permissions.
6 min read Read →Model-agnostic inference gateway
One call site in front of every model provider. A price change or an outage becomes a config change.
6 min read Read →A coding-agent delivery fleet
A control plane for running many coding agents at once. The agents do not collide on the same files. You can see what each one costs.
6 min read Read →Comparisons#
Open-Weight Models vs Frontier APIs: The Real Cost/Control Tradeoff
Self-hosting an open-weight model looks cheaper on paper than it behaves in practice. The real tradeoff against a frontier API, and when each one is right.
7 min read Read →RAG vs Fine-Tuning: Which One Solves Your Problem
Retrieval and fine-tuningFine-tuning trains a model's weights on your own examples, changing its behavior directly. solve different problems but get reached for interchangeably. How to tell which one your case needs, and why we default to retrieval.
7 min read Read →Insights#
Model-Agnostic by Design
Models change under you every few months: price, quality, and capability. So we never hardcode a single provider into a client's feature.
7 min read Read →Build, Buy, or Skip: A Framework for AI Decisions
A technically honest framework for deciding whether an AI initiative should be built in-house, bought off the shelf, or skipped entirely this year.
7 min read Read →Case studies#
The AI-Native Target That Wasn't: A Two-Week Diligence
A growth-equity firm's term sheet on an 'AI-native' SaaS target got repriced after a two-week check found $1.4M of hidden re-platform cost.
7 min read Read →Cutting Inference Spend 40% Without Betting on One Vendor
A Series B fintech's LLM spend outran revenue on one provider. Model-agnostic routing cut unit cost, vendor risk, and closed a data-residency gap.
7 min read Read →Tools#
AI Readiness Scorecard
A fast, honest read on whether your data, infra, and process are ready to ship AI.
Read →Architecture Picker
Which system shape to build, from seven questions about the problem.
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