🎮 The Next Input — Issue #168

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⚡ The Briefing — 60 sec

• Google updates Workspace to make AI your new office intern Upgrades all around. Google is pushing harder on the boring-good stuff here: Workspace Intelligence across Gmail, Calendar, Chat, Drive, faster Sheets building and filling, and stronger Docs writing support.

• Microsoft deepens commitment to Australia with A$25 billion investment in AI infrastructure, security, and skills Big money from MSFT. Albo’s handshake game is quite strong these days. Microsoft says this is its largest-ever investment in Australia, with A$25 billion earmarked for AI infrastructure, security, and skills by the end of 2029.

• Introducing ChatGPT Images 2.0 OpenAI is pushing the visual layer harder again. The examples alone tell the story: stronger precision and control, multilingual rendering, polished layouts, aspect-ratio flexibility, and more “visual thought partner” energy than plain old image gen.

🛠️ The Playbook — The Embedded AI Engine

Mission
Turn AI from a separate tool people “go use” into an embedded layer inside the workflows they already live in.

Difficulty
Intermediate

Build time
3–5 hours

ROI
Higher adoption, lower friction, and a much better chance AI improves real work instead of sitting in a tab people promise they’ll open later.

0) Why This Matters

This is where AI gets sticky.

Not when it is the flashiest. When it is embedded.

Google is threading AI directly into the office suite people already use all day: inboxes, calendars, chats, docs, and spreadsheets. Microsoft is making a major Australia bet around the same future, putting real money behind infrastructure and skills. OpenAI is continuing to widen the creative surface, pushing image generation closer to something people can use for polished assets, not just novelty prompts.

That means the real move is no longer:

• get people to try AI

• send them to a chatbot

• hope they build a habit

The move is:

• put AI where the work already happens

• reduce the number of extra steps

• make the output immediately usable

• remove friction before asking for adoption

1) Architecture

2) Workflow

1. Pick one workflow people already do daily inside an existing tool stack.

2. Identify which part of that workflow is repetitive, slow, or structurally annoying.

3. Insert AI at that exact point instead of introducing a separate “AI task.”

4. Ensure the output lands back inside the system where work already happens.

5. Add review where the output is customer-facing, strategic, or sensitive.

6. Measure whether the workflow now feels lighter, faster, and more usable.

3) Example Prompts

Workflow Embed Prompt

You are helping embed AI into an existing workflow.

For the workflow below:
- identify where AI can reduce friction
- identify where AI should stay invisible to the user
- identify what context sources are required
- identify what output should be generated directly inside the workflow

Workflow:
[insert workflow here]

Office Tool Prompt

You are redesigning a workflow inside common office tools.

Given the process below:
- identify what should happen in email
- identify what should happen in docs or sheets
- identify where AI can draft, summarize, or structure work
- identify where human review is still required

Process:
[insert process]

Visual Asset Prompt

You are generating a polished visual asset for operational use.

Task:
[insert task]

Requirements:
- keep branding clean
- prioritize clarity
- make the output immediately reusable
- avoid novelty styling unless requested

Adoption Friction Prompt

You are diagnosing why an AI workflow is not being adopted.

Check:
- whether AI sits outside the normal workflow
- whether users must take too many extra steps
- whether outputs are actually usable
- whether the workflow needs embedding rather than more training

Return 4 bullet points only.

4) Guardrails

• Do not add AI as a separate ritual if it can live inside the workflow.

• Prefer embedded usefulness over flashy capability.

• Keep outputs editable by humans.

• Review any workflow that touches customers, money, or reputation.

• Avoid turning every office task into an AI event.

• Measure friction removed, not just features shipped.

5) Pilot Rollout — 3 hours

1. Choose one workflow already happening in email, docs, sheets, or slides.

2. Map the exact point where users lose time or attention.

3. Add one AI-assisted step at that point only.

4. Keep the output inside the same tool chain.

5. Run 10–15 real tasks and compare before vs after friction.

6. Expand only if the workflow is materially easier to complete.

6) Metrics

• Time saved per workflow

• Number of manual steps removed

• First-draft acceptance rate

• Human correction rate

• Adoption rate inside the existing tool

• Output reuse rate

• User-reported friction reduction

Pro Tip: The best AI workflow often feels less like “using AI” and more like the software finally pulling its weight.

🎯 The Arsenal — Tools & Platforms

• Google Workspace Intelligence · embeds AI across Gmail, Calendar, Chat, Drive, Docs, and Sheets instead of leaving it as a separate destination.

• Microsoft AI infrastructure in Australia · a real reminder that the local AI buildout is getting heavyweight backing, not just polite press releases.

• ChatGPT Images 2.0 · OpenAI is clearly pushing toward more polished, multilingual, layout-aware image generation with stronger control and visual reasoning cues.

• Google Sheets / Airtable · simple places to track whether embedded AI actually reduces friction instead of creating another layer of admin · Google Sheets · Airtable

• Docs / slides / visual outputs · because the point is not just generation; it is producing something people can use immediately

Copy-paste prompt block:

You are helping me build an Embedded AI Engine.

For the workflow below:
1. identify where AI can reduce friction
2. identify where AI should be embedded inside existing tools
3. identify what context sources are required
4. identify what outputs should be produced directly in the workflow
5. identify where human review is needed
6. list the top 5 adoption risks
7. propose a 2-week pilot

Workflow:
[insert workflow here]

Return the answer in markdown with sections for:
- Workflow summary
- Friction points
- Embedded AI opportunities
- Context sources
- Review points
- Pilot rollout
- Metrics

💡 Free Office Hours

If you want AI to feel less like an extra app and more like a real layer inside your team’s everyday workflow, I run free office hours to help map the process, embed the right touchpoints, and keep the rollout practical.

Book here: https://calendly.com

Stop babysitting your coding agents

Agents can generate code. Getting it right for your system, team conventions, and past decisions is the hard part – you end up wasting time and tokens in correction loops.

MCPs give agents access to information but not understanding. The teams pulling ahead use a context engine to give agents exactly what they need.

Join us April 23 (FREE) to see:

• Where teams get stuck on the AI maturity curve

• How a context engine solves for quality, efficiency, and cost

• Live demo: the same coding task with and without a context engine

Register now

🕹️ Game Over

The winners won’t just ship smarter models. They’ll quietly wire them into the places people already work.

— Aaron Automating the boring. Amplifying the brilliant.

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