YakData FDE Lab

FDE Lab · YakData

What does a Forward-Deployed AI Engineer actually do?

Follow one real production AI system from business decision through requirements, architecture, build, evaluation, deployment, monitoring, handoff, and improvement.

Project File 001 follows 77 Rules, a real human-in-the-loop AI system that reviews executive dashboards using multimodal AI, explicit rules, deterministic scoring, and human verification.

Built for experienced technical practitioners and technical leaders who want to own more of the production problem, not just one component of it.

Explore FDE Lab Preview Episode 1
Have a live production problem?Request a Fit Review
7Production episodes
~6 hrsEnd-to-end case walkthrough
1Real production system
5Overlapping role lanes
1 pathDecision to client ownership

Who this is for

Two ways into the same production discipline.

You do not need to become five engineers. You need enough depth to make sound decisions and enough breadth to see how the whole system fits together.

Hands-on buildersOwn more than your component.

Senior or staff software engineers · AI/ML engineers · data engineers · solutions architects

You may be asking

“How do I get beyond the model, service, or feature and own the production result?”

You’ll learn to

  • Turn a fuzzy business problem into a bounded system and clear definition of done.
  • Design the end-to-end architecture and a thin vertical slice across every critical layer.
  • Evaluate, harden, deploy, recover, and hand over AI systems on the actual work.
See the builder path →
Technical leadersLead the whole system without pretending to be every specialist.

Engineering managers · technical PMs · data/AI leaders · architects · experienced adjacent practitioners

You may be asking

“How do I make the right production decisions across product, UX, frontend, backend, AI, and QA?”

You’ll learn to

  • Define the decision, scope, owner, and proof specialists are building toward.
  • Challenge architecture, integration, evaluation, and release decisions across the whole system.
  • Know when the evidence says build, redesign, narrow, deploy, transfer, or stop.
See the technical-leader path →

Not beginner coding instruction. FDE Lab is for experienced practitioners who want more cross-functional production responsibility.

01 · How the work moves

The complete path, not the model call.

Production AI starts with a decision that matters and ends when the system can be tested, run, recovered, and owned.

PM outcome, workflow, scope, acceptance UX human control, review behavior, exceptions FEE application behavior, state, review surfaces BEE APIs, orchestration, rules, security, observability Test/QA acceptance, regression, failures, release evidence

02 · Project File 001

77 Rules: visible production evidence.

77 Rules keeps the series attached to one real system: the decisions, architecture, model boundaries, failures, controls, and handoff stay visible.

77 Rules audit workspace with annotated dashboard review and operating controls
77 Rules audit workspace. Production case used throughout FDE Lab.

What the case exposes

The model is a component. The system is everything around it.

  • Multimodal perceptionKeep model output structured.
  • Explicit rulesTurn expert judgment into inspectable logic.
  • Evidence disciplineSeparate observation, inference, and missing evidence.
  • Deterministic scoringKeep important scoring under explicit control.
  • Human verificationPut correction and override inside the workflow.
  • Client extensibilityHand over a system the client can run and extend.
What this looks like in practice

A persuasive dashboard may not contain enough evidence to prove the claim. The system sometimes has to ask for context or say “insufficient evidence.”

Explore FDE Lab View 77 Rules
Stephen McDaniel, founder of YakData and instructor of FDE Lab
Stephen McDaniel · Founder, YakData

A note from Stephen

I’ll show you the work, including the parts that did not go neatly.

I’m Stephen McDaniel. I’ve spent most of my career in the awkward space between a business problem and the system that eventually has to work. FDE Lab is where I take that work apart in public: the architecture, decisions, tests, revisions, and tradeoffs that usually disappear from a polished demo.

Sometimes the right answer is more AI. Sometimes it is a rule, a better workflow, a simpler system, or not building the thing at all. I’ll show you the evidence and tell you what I think.

Stephen McDaniel · Founder, YakData

03 · The 7-episode journey

Seven production decisions, from definition to ownership.

Each episode opens on a real artifact, shows the decision at stake and what can go wrong, and closes with the next build, test, release, or handoff decision.

Episode 01

Decide What Deserves to Be Built

Define the decision, owner, scope, definition of done, and build-or-stop choice.

Proof: decision map + scope/acceptance
Episode 02

Turn Expert Judgment Into System Requirements

Turn expertise into rules, evidence, context, workflow states, errors, and testable contracts.

Proof: rule/evidence schema
Episode 03

Design the Production System and the Work

Design the architecture, frontend/backend contracts, constraints, observability, and overlapping work.

Proof: role/dependency graph
Episode 04

Build the Production-Shaped Vertical Slice

Move one representative case through every critical layer before broadening the backlog.

Proof: vertical-slice architecture
Episode 05

Make the AI Earn the Right to Be Trusted

Benchmark the real task, test critical misses and false alarms, and verify human control.

Proof: benchmark + failure matrix
Episode 06

Turn the Working Slice Into a Production System

Harden validation, retries, versions, regression, telemetry, deployment, and recovery.

Proof: production-readiness checklist
Episode 07

Transfer Ownership and Improve the System

Package the runbook, test evidence, recovery knowledge, extensions, metrics, and next decision.

Proof: ownership/handoff package

04 · Project Files

Learn from the artifacts engineers actually use.

Start with the free map and Starter Pack. The $99 Field Library adds the complete 77 Rules case and four specialist working packs.

Free · No email

FDE Production Map

The end-to-end production path with role overlap, release checks, and handoff points.

View Production Map
Free · Email

Project File 001

Expanded 14-step production workflow, role matrix, definition-of-done structure, and production checklists.

Get the free Starter Pack

05 · Why YakData

The lessons come from systems I’ve actually built.

FDE Lab comes from systems I have built through YakData. The detailed proof page shows the work, the numbers, and the boundaries around the claims.

4 weeks77 Rules moved from concept to production and adoption by a large non-U.S. bank.
7 weeksCommercial-intelligence system delivered against a 4 to 6 month comparison baseline.
~30 systemsForecasting, analytics, valuation, sponsorship, and audience-intelligence systems in 2.5 years.
$1B+Acquisition decision supported by revenue verification and P50/P90 scenario modeling.

Review the detailed proof record

For teams building this now

This is the work.

If your team is trying to turn an AI experiment into something people can rely on and own, YakData handles the definition, build, evaluation, deployment, and handoff.

Request a Fit Review Review Production Proof

Choose the next action

Learn how production AI gets built, or put it to work.

EducationExplore FDE Lab7 episodes + Project Files EngagementWork with YakDataProduction engineering for qualified teams