Session 1: Foundations - the reliable reasoning component
13 lessons · Back to full syllabus
What you keep
How to turn a model call into a dependable, observable piece of software - plus context engineering, token optimisation, and a free-resources bridge to mastery.
You ship
A working `/ask` endpoint that answers reliably, plus a Streamlit UI that demos it - the reasoning core of your capstone.
Watch through (async)
Think Like an AI Engineer (free 10-part series)
Watch this YouTube playlist before or alongside Week 1. Plain-English foundations - how LLMs work, prompting, models, context, agents, workflows, and evals - so the live FastAPI and reliability work clicks faster.
- 1How LLM Actually Works (in Plain English)Watch
- 2How to Prompt AI Like a Pro: The 5-Part FormulaWatch
- 3How to Pick the Right AI Model for the JobWatch
- 4Using AI With Your Files, Images and DataWatch
- 5Context Is Everything: The #1 Skill for Using AIWatch
- 6Vibe Coding for Non-Engineers (and Engineers)Watch
- 7What AI Agents Actually Are (Hype vs Reality)Watch
- 8Build AI Workflows With No Code (n8n, Zapier, Make)Watch
- 9AI Evals: How to Know If Your AI Actually WorksWatch
- 10The Fastest Way to Stay Current in AIWatch
Live session resources
Week 1 session deck (12 Aug 2026)
Live Session 1 slides for Cohort 13: WhatsApp join, tool stack, three layers, harness, prompting, and the /ask build path.
Open resourceWeek 1 session deck (31 Jul 2026)
Prior cohort Session 1 slides (same teaching spine).
Open resourceWeek 1 `/ask` demo code (5 stages)
FastAPI starter repo: bare /ask through structured output, guardrails, model routing, and cost readout. Includes Streamlit demo UI and stage smoke tests.
Open resourceWeek 1 assignment build guide
Step-by-step Path A / Path B guide with copy-paste prompts for the basic live /ask submission, Streamlit UI, and optional add-ons.
Open resourcePrompting lab (bad vs good)
Five OpenAI Playground pairs: specificity, structured output, few-shot, chain of thought, constraints. One-tap copy for each weak and strong prompt.
Open resourceSoftware components for beginners
APIs, REST, POST, FastAPI, Docker, horizontal vs vertical scaling, and the rest of the building blocks Session 1 assumes. Read before or alongside the live build.
Open resourceLessons
From model call to reliable component
Production means the right shape, at a known cost, with a plan for when it fails - every time.
The OpenAI API and the Playground
Experiment in the Playground first: system vs user messages, temperature, max tokens, and the token counter.
Module 1.1 - Build your first LLM service
Stand up a real POST endpoint with typed models before any theory - the living thing everything else improves.
Module 1.2 - Prompting that ships
Structured outputs, few-shot, and decomposition - three techniques to make output deterministic enough to build on.
Module 1.3 - Output guardrails and validation
Schema, semantic, and safety validation - plus retry patterns - between the model and everything downstream.
Module 1.4 - Token economics and context budgets
Tokens are money and latency. Treat the context window as a budget, not free space.
Module 1.5 - Choosing the right model
Match capability, cost, and latency - and route different steps to different models in one system.
Module 1.6 - Context engineering: the throughline
Prompting, cost, and model choice are all facets of one skill: engineering what the model sees.
Module 1.D1 - Advanced structured outputs and function-calling schemas
Nested schemas, enums, and function calling - when the shape must be airtight and feed code directly.
Module 1.D2 - The provider landscape beyond OpenAI
Anthropic, Gemini, open-weight models - per-task fit and portability across providers.
Module T - Token Optimisation
Nine concrete techniques to cut cost and latency without trading away quality you need.
Module B - Mastering AI Engineering: the free-resources bridge
A curated map from bootcamp graduate to self-directed mastery - almost everything is free.
Session 1 assignment support: Ship Your First AI Endpoint
A grouped guide with copy-paste prompts for the basic Session 1 submission (including Streamlit UI), plus optional add-ons.
Lessons in this module