// FIELD NOTES

Engineering notes for teams that need to ship.

AI role design, vetting, RAG, forward-deployed engineering, and the practical tradeoffs behind hiring production AI engineers.

AI & DELIVERY

AI-native delivery, agents and engineering ownership.

Field notes on AI features, offshore delivery, workflow automation, and the engineering model behind Devlyn.

HIRING GUIDES

Role, rate and vendor decisions without vague promises.

Guides for choosing the AI role, pricing tier, trial structure and vetting signal that fit the roadmap.

PRODUCT BUILDING

First proofs, stack fit and production ownership.

Practical writing for founders and CTOs who need AI work shipped in the actual product, not parked in a demo repo.

PLAYBOOK | 7 min

Forward-deployed engineering, explained for AI teams

The model Palantir and OpenAI made famous - an engineer embedded in your team, owning outcomes - and how to know when you need one.

Read the breakdown
ENGINEERING

RAG is a hiring problem before it is an infra problem

Most retrieval failures trace back to who built the pipeline, not which vector database they chose. A field guide.

6 min
HIRING

The 8 AI roles every team actually needs in 2026

A practical breakdown of the disciplines AI products depend on - and which one to hire first depending on where you are stuck.

8 min
VETTING

What "AI-native" means when we screen an engineer

A look inside our multi-stage vetting: shipped features, eval discipline, cost reasoning, and why most resumes do not survive it.

6 min
AI HIRING

How to choose the right AI hiring model

A practical way to choose between a dedicated AI engineer, a larger talent network, a services partner or an internal hire without turning the decision into brand comparison.

6 min read
PRICING

How published role pricing helps AI teams plan

Published pricing is useful because it makes planning easier before the first call. The real value is matching the role level to the work, not turning price into the whole story.

5 min read
AI HIRING

Why pricing clarity matters in AI staffing

AI roles are already hard to scope. Pricing clarity helps buyers plan, but it works only when the role definition, seniority level and first proof point are equally clear.

6 min read

Field notes, no spam.

Talk through your stack, role, timeline or AI feature. We will tell you what kind of engineer actually fits.

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