Applied AI Engineering
Signature Course No. 171 — A Signature AI Socratic Coaching Course.
A New Kind of Learning
Socratic coaching, delivered by an agentic AI coach.
Not a course you watch. An AI coach you work with.
The Lighthouse Coach begins by discovering how you think about the subject, teaches what is missing, and gives you realistic practice before asking you to prove that you can use it. You may test out of concepts you already understand, while capstones turn the learning into a practical plan, decision, conversation, or other real-world result.
The curriculum is deliberately authored; the AI delivers it through coaching. It is not an AI randomly generating lessons.
A coach that teaches by asking — not by lecturing
The Lighthouse Coach is an AI Socratic coach built on Cognosco Learning's Applied AI Engineering course, in the AI at Work category. It does not play videos at you. It holds a conversation: it asks you a question, listens to your answer, names the misconception it hears, affirms what you got right, and asks the next question — the way a great coach works in the room.
This is the course for software engineers being handed AI features to build, for technical leads and architects deciding how AI capabilities are integrated, versioned, and operated, and for platform and operations engineers who will be paged when an AI feature misbehaves with nothing crashed.
It works on one running business — Briarline Freight Co. and its document assistant, which extracts fourteen billing fields from inbound carrier documents: first, Module 1 — Specify It Before You Build It — work through Concepts 1–9, finishing with The Release Dossier; then, Module 2 — Operate It After It Ships — work through Concepts 10–18, finishing with The Operating Plan.
You finish by proving the whole course — in The Release Dossier and in The Operating Plan. You can type your answers, or talk out loud: the Voice Coach speaks its questions and listens to your spoken replies, hands-free. Defending a threshold to a skeptical lead, or talking an incident commander through a containment, is a spoken act — done live, to a coach who can answer back.
The course is self-paced and always on — roughly 30 minutes per concept, about 9 hours in full, taken in as many sittings as you like. Learners who already know the material can test out concept by concept.
A demonstration proves a model can do a thing once. This course teaches the engineering that proves a system does the thing — within stated limits, at a stated cost, with a stated plan for the day it stops doing it, and the evidence to show its work.
Both capstones produce real artifacts — a release dossier that decides whether a new AI feature may ship, and an operating plan that decides how a live one keeps running — written to be used on the real job, not just filed in the course.
This is the one hundred and seventy-first course in The Lighthouse Signature Series — the online counterpart to the one-day, in-person learning Cognosco Learning has delivered since 2002.
Course Facts
One full concept, coached end to end — free: verify your email and we’ll send you a link to start.
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Diagnose → Learn & Practice → Prove → Capstone
Every learner moves through the same discipline a Cognosco instructor would insist on in the room.
Diagnose
The Coach starts where the course starts: with the frame itself. An AI feature that was never specified cannot be tested — and a feature that cannot be tested cannot be trusted. Every concept opens with three questions that locate where you actually stand, and your answers shape how deeply the Coach works the concept with you. Everyone begins with Module 1 — no skipping the foundations you only think you have.
Learn & Practice
Work each concept in conversation with the Coach — spoken or written — then practice it against realistic situations until it holds up.
Prove
Every concept ends in proof: answer the check cold and demonstrate the skill. Know it already? Test out and take credit immediately.
Capstone
Finish with two capstones — The Release Dossier for Module 1 and The Operating Plan for Module 2 — that pull the whole course together, and earn the certificate.
What You'll Learn
Every AI feature begins life as a demo that works — in the room, on the examples chosen for the room. Then the feature ships, and production begins its cross-examination: messier inputs, far larger volume, a supplier format changed without notice, a confident wrong answer reaching a customer.
The gap is not a model gap. It is an engineering gap — and closing it is a learnable, nameable discipline. This course teaches that discipline end to end, on one running business whose figures you can check at every step.
First, specify it before you build it: frame the feature with scope, non-goals, and priced error costs; write the contract, including the abstain result; build the evaluation set that could convict the system; and set the threshold — overall, per critical field, and a floor beneath which no slice may fall.
Audit the data, watch the live data: examine what the system learned from — provenance, coverage, permission — and govern what it meets in production, with schema checks, freshness clocks, and drift measurement.
Integrate with the failures designed in: treat the model as a replaceable component behind one owned boundary, choose the integration pattern per workload, design each failure behavior in advance, and place human review where judgment changes outcomes.
Then operate what you built: version everything that changes behavior, deploy in stages with a clean way back, monitor quality rather than mere uptime, and run incidents whose cause is a behavior rather than a crash.
Hold the three-way budget: cost, latency, and quality argued as one budget, with the arithmetic in the open — and guardrails built as mechanisms that hold under pressure, on inputs, outputs, and actions.
Close by making the standard personal: retrieval over a governed corpus, agents supervised under a written mandate, and the engineer's standard — what you sign, before a system ships and while it runs, with the limits stated in the same voice as the claims.
What you will learn
- Frame an AI feature as an engineering problem and write its contract — inputs, outputs, guarantees, and failure behavior
- Build evaluation sets and set acceptance thresholds that make go-live a measured decision
- Audit the data a system learns from, and govern the quality of the data it meets in production
- Integrate models as components — choosing patterns, designing fallbacks, and placing human oversight where it protects
- Version, deploy, and change AI systems safely — with staged rollouts and clean rollback
- Monitor AI quality in production and run incidents whose symptom is wrong behavior, not downtime
- Balance cost, latency, and quality as one budget, and build guardrails that hold under pressure
Everything in the course
- All 18 concepts of Applied AI Engineering, in 2 modules
- A starting-point check first — the Coach finds where you actually stand before teaching
- Learn, Practice, Prove for every concept — no passive video watching
- A test-out on every concept: prove you know it and move on
- The Voice Coach: talk with the Coach out loud — it speaks, listens, and replies
- A personal Learner Record of your work across the course
- Two capstone exercises: The Release Dossier and The Operating Plan
- A printable session summary whenever you pause
- The Lighthouse Coach completion certificate (Signature Series)
- Your progress is saved as you go — stop anytime, resume where you left off
Built for the people who build and operate AI systems
Applied AI Engineering is for software engineers being handed AI features to build, technical leads and architects who decide how AI capabilities are integrated, versioned, and operated, platform and operations engineers who will be paged when an AI feature misbehaves, and technical professionals moving into AI work who already think in evidence and edge cases.
This is an AI at Work course. It assumes you can read a system diagram, reason about interfaces, and follow a worked calculation. It assumes no machine learning background: models here are components with contracts, and everything about their behavior is taught as observable, measurable properties — what goes in, what comes out, how often it is wrong, and what wrong costs.
Prefer to learn live and in person? The same material anchors Cognosco's one-day programs — browse the in-person catalog.
Start with The Release Dossier
$195 — introductory price. One payment. No subscription, no password to manage.
Here is exactly what happens when you enroll:
- Pay securely with Stripe — you are taken straight into the course
- Create your learner profile and begin the Module 1 starting-point check
- Save the access key you are given — it restores your enrollment on any device
- Learn at your pace; your progress is stored in your browser on your device
For the full voice experience, use Chrome and allow the microphone when asked. Typing your answers works everywhere, all the time. Questions before you enroll? Email hello@cognoscolearning.com.
More Signature Courses are coming
Applied AI Engineering is Signature Course No. 171. Leave your email and we’ll send you news of future Signature Courses and Lighthouse updates as they are announced — nothing else.