Procrastination, flexible work, and AI workflows with Dr. Amantha Imber

Executive overview

High-stakes tasks trigger avoidance, not because people are lazy, but because anxiety and uncertainty about scope overwhelm the ability to start. Breaking complex work into estimated, time-boxed tasks shifts control from the emotional brain to the logical brain.

Flexible work culture increasingly clashes with blunt legislative fixes like right-to-disconnect laws. AI tools reduce friction in daily workflows — but only when deliberately set up with custom GPTs, prompt libraries, and meeting-to-proposal pipelines.

The fastest way to beat procrastination on a big project is to estimate, schedule, and ship something early for feedback — not to wait until you feel ready.

Beating procrastination on complex tasks

• Break the project into monthly milestones, then list discrete tasks for the current month
• Estimate hours per task — this engages rational thinking and makes the workload feel manageable
• Time-box tasks in your calendar as meetings with yourself, roughly one week ahead
• Seek feedback at the 50–60% mark: enough done to be useful, not so far along that criticism stings
• Deadlines are the most reliable anti-procrastination tool — use them deliberately

Right to disconnect laws and flexible work

• Australia's right-to-disconnect laws (August 2024 for large businesses, August 2025 for small) let employees refuse contact outside working hours
• The law assumes 9-to-5 norms, which doesn't match how many modern knowledge workers actually operate
• Flexible schedules — starting early, taking mid-afternoon breaks — conflict with a rigid "off-hours" definition
• Legislation can't easily change manager mindsets: some still reward after-hours responsiveness, creating implicit career pressure
• Responding after hours signals "notifications on," not dedication — managers should update that assumption

Process re-engineering for operational bottlenecks

• Visually map the full process first — the act of mapping often exposes inefficiencies immediately
• Identify where most time is spent: data gathering, compliance, writing, or approvals
• Locate friction points collaboratively with the whole team, not just from the top down
• Look for manual data entry, duplicated effort, rework, and approval bottlenecks
• Automate repeatable components with prompt libraries; build agents and automations (Zapier, N8N) for higher-complexity steps

Task management and note-taking system

• Notion serves as a central command center for all projects, tasks, and notes — both work and personal
• Invest time in learning a tool properly before abandoning it; a short course can unlock its full value
• Use Siri reminders for on-the-go capture, then manually transfer to Notion or calendar
• Post-it notes handle quick in-meeting captures; physical completion (scrunch and bin) gives a satisfying close
• Time-boxing is essential: book calendar blocks to protect deep work

AI workflows in daily practice

• Maintain a prompt library in Notion — a database of tested, refined prompts organised by use case
• Custom GPTs in ChatGPT and projects in Claude are set up for specific recurring tasks, not general use
• A "senior Penguin editor" GPT handles structural feedback on book chapters; a separate GPT handles copy-editing
• Always do a final human pass on any AI-generated content before it goes out
• Sales proposal workflow: Granola records meeting transcripts → combined with human notes → fed into a proposal-writing GPT → Tella video walkthrough sent to the client; full proposal takes ~15–20 minutes