Understand what coding agents can genuinely do in real work — not just demos.
Goal 02
Document use cases
Capture real examples others can learn from and replicate.
Goal 03
Accelerate delivery
Use it to speed up real work — not just as a demo, but in production.
01 Agent shell + models
From idea to built — without a coding background
Agent shell
The app that uses an LLM to do things — read files, run commands, call tools, publish pages. Examples: OpenCode, Grok Build, Cursor, Claude Code, Windsurf. Chat plus hands.
Model access
The LLM brain — Claude, GPT, Gemini, Grok, and more. Via an org seat (e.g. Copilot), a personal subscription, or a built-in provider. You can often switch models inside the same shell.
Together + your context and connectors: one instruction can read your tools, draft an artefact, and take action — without you copy-pasting between apps.
The more you give the agent — your templates, your project background, your preferences — the better the output. Generic in, generic out. Your context in, your work out.
🔗
Connections supercharge everything
Each tool you connect multiplies what the agent can do. Seven tools connected means one instruction can span all seven.
⚙️
Any repeatable task can become an agent
If you do it more than once and the steps are the same, you can automate it. The barrier isn't technical skill — it's identifying the task.
Coding agents connect to other tools via MCPs (Model Context Protocol) — live plugs into your existing systems. Once connected, the agent can read from and write to those tools in a single instruction.
"Summarise this week's changes from tickets1 & wiki2 to update the status template3 , and post a summary to the team chat4 space."
✓ Tickets & wiki read
✓ Status template updated
✓ Chat message posted
— one instruction, three tools, zero copy-paste
An agent is an AI you configure to do a specific repeatable task. You describe what it should do, connect it to your tools, and call on it whenever you need it. It's not a chatbot you converse with — it's a specialist you brief once and then hand the work to.
Chat AI (e.g. ChatGPT)
You ask. It answers. You still do the work — copy, paste, send, update.
Agent (coding agent)
You describe the task once. It reads your tools, executes the steps, and hands you the result.
You can build a custom agent for any task you do repeatedly — meeting follow-ups, status updates, recognition awards, onboarding docs. Configure it once. Call it whenever you need it. Same steps, every time.
05 Demo 1
~2 hours saved
Training session → documentation
Transcript
→
Additional Context
→
GitHub page created
06 Demo 2
~8 hours saved
PowerPoint slides → 30 Confluence pages
PowerPoint slides
→
Template
→
Confluence pages ×30
07 Demo 3
~3 hours saved
Meeting transcript → automated actions
Transcript
→
Jira ticket closed
→
Jira dashboard created
→
Jira ticket created with summary
→
Webex message sent
08 Demo 4 · Agent Example
~15 mins saved
Recognition agent
@recognition <name>
→
Webex history pulled
→
Award drafted
→
Workhuman form navigated
→
You review and send
09 What to Watch Out For
Using it well matters more than using it more
Agent sessions cost something (credits, API, or quota). A few simple habits cut consumption by 50% or more with no drop in quality — whether you're on a shared pool or a personal plan.
The working flow
Ideate Chat AI or a light model
→
Plan Sonnet · plan mode
→
Build Sonnet · build mode
→
heavier models Opus
Watch out
Defaulting to heavy models
One Opus 4.7 prompt costs the same as 15 Sonnet prompts. Start with Haiku or a free model. Escalate only when the output isn't good enough.
Watch out
Thinking out loud in the agent
Exploratory back-and-forth is expensive in an agentic app. Do that in a free chat tool. Arrive at the agent knowing what you want to build.
Watch out
Leaving sessions open for days
Every new message re-sends the full conversation history — even the parts from three tasks ago. One task, one session, then close it.
Watch out
Know your meter
Shared org pools and personal plans both need a weekly glance at usage. Drift is easy; a 60-second check keeps you honest.