diff --git a/presentation/learning-journey/index.html b/presentation/learning-journey/index.html index 009329b..5dbdd12 100644 --- a/presentation/learning-journey/index.html +++ b/presentation/learning-journey/index.html @@ -156,7 +156,7 @@
I'll unpack each of these as we go — for now, just let them wash over you.
-vibe coding — describing what you want in plain English and hoping the AI nails it
+agentic engineering — building guardrails so AI acts like a reliable teammate, not a gamble
+progressive disclosure — feeding the AI only what it needs right now, not everything upfront
+orchestration — coordinating several AI agents like a conductor leads a band
+dumb zone — the stretch where AI has too much context and starts thinking worse, not better
+agentic workflows — AI that plans, acts, checks its work, and adapts — multi-step on its own
+MCP — a universal adapter letting AI talk to your tools (GitHub, Slack, databases)
+hooks — auto-triggers that run your rules before or after the AI does anything
+harness — the scaffolding around the model — files, terminal, tools — that turns a chatbot into a worker
+compaction — auto-summarizing old chat so the AI keeps going without hitting its memory ceiling
+context engineering — deliberately curating what the AI sees so it answers well
+context rot — quality decay as the conversation drags on and earlier details blur
+prompt engineering — the craft of phrasing requests so the AI understands exactly what you mean
+AI slop — low-effort, generic AI output that looks polished but says nothing
+hallucination — when AI confidently makes up facts that sound true but aren’t
+context bloat — overstuffing the AI’s memory so it slows down and loses focus
+one-shot prompting — giving the AI one example and asking it to follow the same pattern
+token burn — wasting expensive AI “words” on unnecessary back-and-forth or bloated prompts
+