PMs owning AI features

AI defaulted to engineering, but the judgment layer where domain expertise lives is where AI features are won or lost. Why prompt and eval work belong with PMs and domain experts, why "evals are the new PRDs" is a trap, and the ownership model that actually holds when the output is probabilistic.

Article16 JUN 2026

AI evals for product managers: the complete guide for 2026

The complete, practical guide to AI evals for product managers in 2026 — what an eval is, why it's a PM skill, and how to evaluate AI quality whether you have a live feature or just an idea.

Madalina Turlea

Article10 JUN 2026

Best AI evaluation tools for product managers in 2026 (ranked by a PM)

A PM's ranking of the 8 best AI evaluation tools in 2026 — Lovelaice, Confident AI, LangSmith, Braintrust, Maxim AI, Adaline, Langfuse, and PostHog — researched from official docs and tested hands-on. Judged on what a PM can actually do without engineering: run experiments before shipping, review outputs blind with domain experts, and build validated metrics.

Madalina Turlea

Article10 JUN 2026

The alternative to Langfuse for product teams (2026)

Langfuse is open-source LLM engineering infrastructure — built for developers first. If your team needs a proven evaluation process fast, with domain experts and PMs contributing to AI quality, here's the alternative: guided validation the whole team can run.

Madalina Turlea

Article10 JUN 2026

The alternative to Braintrust for product teams (2026)

Braintrust is built for engineering-first teams. If you're looking for an alternative platform to guide your PMs and domain experts through pre-shipment AI validation themselves — no engineering ticket required — here's the case for Lovelaice.

Madalina Turlea

Article10 JUN 2026

How to measure AI feature ROI (when half of teams can't)

Half of product teams name unclear ROI as their #1 AI challenge, and a third track no AI metrics at all. Here's a measurable framework for the return on a single AI feature.

Madalina Turlea

Article10 JUN 2026

Who should own AI features in product teams?

AI defaulted to engineering, but the judgment layer where domain expertise lives is where AI features are won or lost. Who should own AI in product, and why the ownership has to move.

Madalina Turlea

Article26 MAY 2026

How to know your AI feature actually works in production

Most teams ship AI features and wait for complaints. Here's how product managers can know — not hope — their AI is working in production.

Catalina Turlea

Article14 APR 2026

Should you still write PRDs when building AI features?

The programming language is plain English. The prompt IS the spec, so why is the PM three handoffs away? Why "evals are the new PRDs" makes things worse, and what PM-owned AI development actually looks like.

Madalina Turlea

Newsletter13 APR 2026

Lessons from one year of AI product building

Key insights from building AI products over the past year.

Madalina Turlea

Newsletter10 APR 2026

The expert test: how to identify high-value AI features for your product

How to identify which AI features will deliver the most value.

Madalina Turlea

Article12 MAR 2026

Evals in CI are only as smart as the engineer who wrote the assertion

Putting evals in CI is good engineering. It is also silent on every failure mode the person who wrote the test did not know to worry about — which in fintech, healthtech, and insurance is the ones that ship the bug.

Catalina Turlea

Article15 JAN 2026

Why shipping a mediocre AI feature is worse than shipping nothing

A mediocre AI feature doesn't just underperform — it erodes trust, trains users to ignore you, and poisons every AI feature you ship next.

Madalina Turlea

Article15 JAN 2026

Why AI features should not be owned by engineering alone

Engineers build the technical part. Domain experts hold the context that makes AI intelligent. Why prompt and evaluation work belongs with the people who understand the problem.

Madalina Turlea

Article15 OCT 2025

3 mistakes PMs make when they let engineers own the AI prompt

Engineers build infrastructure. Domain experts build quality. Here are three costly mistakes that happen when PMs hand prompt ownership to engineering.

Madalina Turlea

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