diff --git a/presentation/2026-04-25-gdg-kolachi-cli-claude-code-gemini/index.html b/presentation/2026-04-25-gdg-kolachi-cli-claude-code-gemini/index.html index 880a928..2aea131 100644 --- a/presentation/2026-04-25-gdg-kolachi-cli-claude-code-gemini/index.html +++ b/presentation/2026-04-25-gdg-kolachi-cli-claude-code-gemini/index.html @@ -444,39 +444,9 @@ - +
Claude Code isn't just Claude. It's Claude (the model) wrapped in a harness with a set of tools — and that wrapper is what turns a chatbot into an agent.
-The brain. Knows everything up to its training cutoff. Doesn’t know today’s date, can’t read your files, can’t search the web.
-The body around the brain. Manages memory, permissions, how long conversations run, and how the brain talks to tools.
-The hands. Read files, edit code, search the web, run commands, spawn helper agents.
-Claude Code = Model + Harness + Tools
-Ask a bare model “what’s the capital of Pakistan?” — it answers from training data. Ask it “what time is it in Karachi right now?” — it can’t know. That second question needs a tool, exposed through a harness. That’s the difference Claude Code makes — and the rest of this session teaches you how to configure it.
-Model (Brain 🧠 — e.g. Opus, GPT) + Harness (Body 💪 — e.g. tools, MCP, memory)
@@ -486,7 +456,7 @@ -The raw model has no real-time access — no internet, no files, no clock.
The harness reaches out via WebSearch and fetches a real answer from live sources.
But does the harness always work this cleanly?
+Really?
Same question, different prompt — sometimes the harness asks first instead of acting.
+Similar prompt — but this time the model decided not to use the tool.
External tools can time out, return errors, or fetch stale data.
+The model first tried one source — it failed (403) — so it fell back to another.
A harness gives the brain hands — but not a fixed routine.
@@ -654,7 +624,7 @@ -Even before you set up any structure, how you prompt matters. Specific beats vague. Context beats assumption.
We're going to learn five concepts using one running example: a weather reporter agent that fetches Dubai's temperature and renders a weather card. Same person — five different angles.
An agent is Claude playing a specific role. Meet the weather reporter — a specialist hired to fetch and report weather data for Dubai. Same Claude, different hat.
The difference in one picture: prompting is asking a stranger on the street; using an agent is asking your dedicated specialist.