🎮 The Next Input — Issue #165

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⚡ The Briefing — 60 sec

• Anthropic launches Claude Design, a new product for creating quick visuals Anthropic keeps cooking. 🔥 Claude Design is aimed at founders and PMs who want quick prototypes, slides, and one-pagers without opening a full design tool, which is exactly how you quietly widen the moat.

• Vercel breach linked to AI tool compromise raises risk for crypto frontends 👀 One employee, one third-party AI tool, and suddenly internal, employee, and customer data are in play. If your frontend stack touches money, this is the kind of story that should make people sit up properly.

• Property sector leads AI adoption at nearly 70 per cent We love to see it. Property services are now the highest-adoption SME sector in Australia at nearly 70 per cent, which is a pretty clear sign that AI is not just a tech industry toy anymore.

🛠️ The Playbook — The AI Workflow Perimeter

Mission
Expand AI into real workflows without expanding your attack surface, hidden dependencies, or operational chaos at the same time.

Difficulty
Intermediate

Build time
3–5 hours

ROI
Faster rollout, cleaner controls, and a much better chance of scaling AI use without discovering the risk layer the hard way.

0) Why This Matters

This is what maturity looks like.

On one side, Anthropic is moving from chat into more concrete work products. Claude Design creates prototypes, decks, one-pagers, and exports to PDF, PPTX, URLs, or Canva, while also supporting team design systems and availability across Pro, Max, Team, and Enterprise in research preview.

On the other side, the Vercel incident is a reminder that the AI layer can become a security ingress point. The reported breach was linked to compromise of a small third-party AI tool, with Vercel warning about exposure risk around internal systems and unprotected environment variables.

And then there is the market adoption signal. Property services in Australia are already nearing 70% AI adoption, ahead of finance and insurance, with broader SME data also showing time savings and productivity gains among adopters.

So the move is not just:

• add AI features

• celebrate adoption

• hope security sorts itself out

The move is:

• expand AI where the workflow value is obvious

• define the perimeter around every tool and integration

• make adoption and control scale together

1) Architecture

2) Workflow

1. List every AI tool being used across the workflow, including design, writing, automation, and research tools.

2. Map what each tool can access, including files, accounts, codebases, and environment variables.

3. Classify each tool as low-risk assistive, medium-risk connected, or high-risk action-taking.

4. Keep low-risk tools moving fast, but lock down connected tools with stronger permissions and secrets hygiene.

5. Add review and approval steps where outputs become customer-facing, financial, or operationally sensitive.

6. Monitor adoption growth and security exposure together instead of treating them as separate conversations.

3) Example Prompts

Workflow Perimeter Prompt

You are reviewing an AI-assisted workflow.

For the workflow below:
- identify every AI tool involved
- identify what each tool can access
- classify each tool as low, medium, or high risk
- identify the top 5 perimeter risks

Workflow:
[insert workflow here]

Connected Tool Risk Prompt

You are assessing an AI tool with connected account access.

Check:
- what systems it touches
- what permissions are excessive
- whether secrets or environment variables are exposed
- whether the workflow needs stronger controls

Return:
1. risk summary
2. biggest gap
3. recommended fix

Adoption Readiness Prompt

You are helping a team adopt AI safely.

For the workflow below:
- identify where AI will create the most value
- identify what needs training
- identify what needs review or approval
- identify where adoption could outrun control

Workflow:
[insert workflow]

Visual Workflow Prompt

You are designing an AI-powered visual creation workflow.

Given the task below:
- identify what should be generated by AI
- identify what should stay editable by humans
- identify how branding or design systems should be applied
- identify risks if the output is used without review

Task:
[insert task]

4) Guardrails

• Do not connect an AI tool to more systems than it needs.

• Treat third-party AI app permissions as real security decisions.

• Keep secrets, tokens, and environment variables tightly controlled.

• Review customer-facing or business-critical outputs before release.

• Measure adoption and exposure side by side.

• Fast rollout is fine. Blind rollout is not.

5) Pilot Rollout — 3 hours

1. Pick one workflow already using or about to use an AI tool with connected access.

2. Map the workflow, linked accounts, files, and permissions in one sheet.

3. Identify which data, credentials, or outputs would be costly if exposed.

4. Tighten permissions and move any secrets into a proper vault or protected configuration.

5. Run 10 live tasks and note where AI accelerated work versus where it introduced new review burden.

6. Keep only the workflow version that improves speed without widening the perimeter too far.

6) Metrics

• Number of AI tools mapped

• Percentage of connected tools with reviewed permissions

• Time saved per workflow

• Human review rate on sensitive outputs

• Secrets exposure incidents

• Adoption rate by workflow

• Number of perimeter risks closed per month

Pro Tip: The most dangerous AI workflow is not always the smartest one. It is usually the one that quietly got access to more than anyone realised.

🎯 The Arsenal — Tools & Platforms

• Claude Design · fast visual generation for prototypes, decks, and one-pagers, with export support and team design-system alignment.

• Airtable · simple way to map tools, permissions, workflows, and risk ownership · Airtable

• Google Sheets · quick tracking for adoption, exposure points, and review load · Google Sheets

• IAM / OAuth controls · where AI convenience turns into a real access-control decision

• Secrets management · boring, essential, and suddenly very interesting when a third-party AI tool gets popped

Copy-paste prompt block:

You are helping me build an AI Workflow Perimeter.

For the workflow below:
1. identify every AI tool involved
2. identify what each tool can access
3. classify each tool as low, medium, or high risk
4. identify where secrets or environment variables may be exposed
5. identify where human review is required
6. list the top 5 perimeter risks
7. propose a 2-week pilot

Workflow:
[insert workflow here]

Return the answer in markdown with sections for:
- Workflow summary
- Tool map
- Access map
- Risk classification
- Review points
- Pilot rollout
- Metrics

💡 Free Office Hours

If your team is adopting AI fast and you want to make sure the workflow perimeter is as deliberate as the rollout itself, I run free office hours to help map the tools, tighten the controls, and keep the upside intact.

Book here: https://calendly.com

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🕹️ Game Over

AI adoption is great. AI adoption with the doors left open is less great.

— Aaron Automating the boring. Amplifying the brilliant.

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