The Next Input — Issue #111

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⚡ The Briefing — 60 sec

• AI engineers now sit at the top of Australia’s highest-paid roles list
  AI engineers right at the top. Not exactly shocking—but it does confirm where leverage lives right now.

• Sony Honda Afeela adds PS Remote Play and Gran Turismo-style motor sounds
  I love CES week. As a Sony fanboy, it’s impossible not to nerd out just a little here.

• xAI says it raised $20B in Series E funding
  Twenty billion. At this point the funding rounds sound fake—but the compute definitely isn’t.

🛠️ The Playbook — The AI Talent Multiplier

Mission Turn one strong AI engineer into the output of five by surrounding them with the right agent stack, tooling, and guardrails.
Difficulty Medium
Build time 2–3 hours
ROI Massively increases leverage per hire and reduces the pressure to “just hire more.”

0) Why This Matters

When AI engineers top salary charts, the constraint isn’t ambition—it’s people.
The teams winning right now aren’t just paying more. They’re designing systems where a single engineer can move absurdly fast without breaking things.

This playbook shows how to build that multiplier.

1) Architecture

2) Workflow

1. Engineer defines the goal and constraints—nothing else starts without this.

2. GPT-5-mini breaks work into discrete, testable tasks.

3. Claude 4.5 Sonnet handles:

   • implementation

   • refactors

   • documentation drafts

4. Test agent generates unit and integration tests automatically.

5. CI enforces quality gates before merge.

6. Engineer reviews decisions, not boilerplate.

3) Example Prompts

Task Decomposition (GPT-5-mini)

Break this feature into:
- implementation tasks
- test requirements
- risk areas
Keep it concise and ordered.

Implementation Agent (Claude 4.5 Sonnet)

Implement the task cleanly.
Prioritise readability and maintainability.
Assume a human will review decisions, not syntax.

4) Guardrails

• Humans own architecture. Always.

• No auto-merge without tests passing.

• Log all AI-generated changes clearly.

• Prefer fewer engineers with higher leverage.

5) Pilot Rollout — 2 hours

1. Pick one active feature or backlog item.

2. Run full decomposition + implementation loop.

3. Measure time saved vs solo build.

4. Identify friction points.

5. Standardise prompts and checks.

6. Roll out to the rest of the team.

6) Metrics

• Output per engineer per sprint

• Review time per PR

• Bug rate post-merge

• Test coverage delta

• Engineer burnout indicators

Pro Tip: Pay top dollar—but design for leverage. Salary without systems is just expensive chaos.

🎯 The Arsenal — Tools & Platforms

• Claude 4.5 Sonnet · High-quality code generation and refactors · https://anthropic.com

• GPT-5-mini · Planning, reasoning, and code review support · https://openai.com

• GitHub Actions · Enforce quality gates automatically · https://github.com/features/actions

• Cursor · AI-native IDE for high-leverage engineers · https://cursor.sh

Copy-paste prompt block:

You are supporting a high-leverage engineer.
Optimise for clarity, speed, and correctness.
Leave decisions to the human.

💡 Free Office Hours

Want help implementing anything? Book a free 15-minute Office Hours slot—no sales pitch, just workflows solved.

→ https://calendly.com/aaron-cylentis/the-next-input-office-hours

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🕹️ Game Over

The future isn’t bigger teams—it’s sharper ones.

— Aaron Automating the boring. Amplifying the brilliant.

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