Thursday, October 23 • 7:00 PM EDT – 9:00 PM EDT
A fast, practical on‑ramp to AI literacy. You'll learn what ChatGPT is, how it works, and how to make it produce useful output — with hands‑on labs and zero fluff.
With the information you learn, you can be the person who can explain, steer, and produce with AI — all without clever prompting tricks.
Live, interactive session · Includes slides, tools, and project files
We'll cover LLM basics → the ChatGPT interface → prompt anatomy → safety & hallucinations → simple custom GPTs.
▾ See what you'll learnMyth: "ChatGPT doesn't understand context."
✓ Modern models track context when your request is scoped. We show you how to supply the context that matters. Vague in → vague out.
Myth: "It just parrots the internet."
✓ It reads, predicts, and interprets context. With examples and constraints, it can synthesize faster than most humans — which makes you, and your team, faster.
Myth: "Hallucinations make it unusable."
✓ You'll learn a two‑minute "Can I trust this?" check that catches most errors. Use your knowledge to fill gaps. Keep what's useful; fix or discard the rest.
Myth: "If I use AI, people will know."
✓ With clear requests and light polishing, it reads like you. The stigma is fading as professionals learn responsible use and disclosure.
Translation: the model isn't dumb — unclear asks are. This class fixes that.
How ChatGPT Actually Works (in plain English) — what they are and why they're suddenly everywhere.
Why it matters: you'll be able to explain AI to anyone — and sound credible doing it.
How We Got Here — neural nets → transformers → ChatGPT.
Why it matters: once you see why models behave the way they do, you stop fighting them and start guiding them.
Which Model When Learn what large language models are and what to use (or avoid) for common tasks.
Why it matters: no more guessing. Use the right tool and get better results in less time.
Clear, testable asks — goal, audience, examples, constraints.
Why it matters: modern models don't need magic prompts — they need clear instructions and examples.
Verification & correction loop — ask → check evidence → fix → lock.
Why it matters: you'll catch hallucinations quickly and keep what's useful.
Tiny AI Assistants (no‑code, custom-built) — learn to make custom assistants that excel at one specific task in your workflow.
Why it matters: single‑purpose helpers are easier to trust, reuse, and maintain — and they fit into what you already use.
Plus: access to the Reflexivity AI custom assistant after class.
These aren't demos — they're muscle‑building reps. Each lab turns a core AI concept into a repeatable skill you can use at work tomorrow.
Lab 1
Turn a fuzzy idea into a precise, testable request that delivers a structured, on‑brief output.
Skill: translating fuzzy human intent into machine‑readable asks.
Lab 2
Move your idea from text to image without losing meaning. Keep tone, constraints, and details intact.
Skill: maintaining coherence across modalities (text → image → voice).
Lab 3
Convert your concept into a one‑page execution plan — audience, steps, risks — that you can start implementing immediately.
Skill: structured information synthesis and AI‑assisted planning.
You'll leave with three artifacts you can reuse: a clear‑ask template, an on‑brief image, and a one‑page plan.
This is an interactive coaching session, not a lecture. We structure the session so you leave with finished work, not just notes.
We work from attendee suggestions, so the outcomes map to real problems, not canned demos. Best of all, you get a copy of the session yourself to refer to anytime you'd like.
6–10 minute build cycles so you make progress fast and see the loop (ask → test → refine) in action.
We tighten language, add examples/constraints, and show how tiny changes can shift output quality.
You can't use an untrustworthy tool. You will learn quick verification steps you can run in two minutes before trusting an answer or hitting send.
Explain what AI can/can't do in plain English and set realistic expectations in meetings.
Write clear asks, verify quickly, and lock reliable output — a loop you can reuse anywhere.
Know where to start, what to try next, and how to keep improving without prompt-of-the-day hype.
Recording + slides included so the method sticks.
AI is already part of hiring, marketing, sales, research, and creative work. The people who can steer it don't just work faster — they look smarter in every meeting.
Skip this, and you'll still be staring at a blank box tomorrow.
Ben Smith is a staff‑level software engineer and AI systems architect with 15+ years of shipping real software.
He bridges abstract AI concepts and practical execution — translating models, prompts, and guardrails into workflows you can actually use the next day.
Ben helps small teams and independent operators get real work done with AI. No hacks, no AI mysticism — just practical methods that work when you need them.
Get confident with AI in one evening — and prove it the next day.
Reserve Your SpotShow up curious, leave competent.
Space is limited Live on Zoom • Recording included
Thursday, October 23 • 7:00 PM EDT – 9:00 PM EDT
Interactive, not a webinar — you'll build skills.
We'll send your receipt & ticket information to this email.
Recording, slides, and reusable templates included.