Book Overview by gemini
- Title: SuperSkills: The Seven Human Skills for the Age of AI
- Author: Rahim Hirji
- Publisher & Release: Kogan Page (July 2026)
Summary
1. The Core Premise: Drift vs. Design
Hirji argues that we are quietly transferring authorship of our lives to algorithms that make thousands of micro-decisions on our behalf (called “algorithmic drift”). To combat this, professionals must transition to “intentional design”—using AI as a tool while maintaining human agency.
2. The Evolution of Skills
The book traces a five-generation “skills stack”:
- Survival skills (basic needs)
- Street skills (commercial agility/communication)
- Specialist skills (vocational expertise)
- Soft skills (teamwork/collaboration)
- SuperSkills (judgment and human-centric capabilities built for the AI era)
3. The Seven SuperSkills
To thrive alongside AI, Hirji outlines seven vital traits:
- Curiosity: Framing the right questions when AI automates the answers.
- Change Readiness: Adapting dynamically as technology shifts.
- Big Picture Thinking: Understanding systems and high-level strategy.
- Empathy: Connecting deeply on a human level.
- Global Adaptability: Navigating decentralized, international environments.
- Principled Innovation: Designing ethically and responsibly.
- Augmented Mindset: Adopting a “Human at the Start” (HATS) approach, working as a “centaur” (collaborating with AI) rather than letting AI lead.
4. Judgment vs. Decision-Making
Hirji defines decision-making as what we do with information, whereas judgment is what we do with our values when the information runs out. AI can handle data-driven decisions, but humans must retain judgment.
Critique
Strengths
- Shifts Focus from Tools to Mindset: Instead of writing a manual on how to use specific AI software (which quickly becomes outdated), Hirji focuses on enduring human behaviors.
- Highly Actionable: The book avoids dry academic theory by providing a practical “operating system”—a framework featuring five questions and five loops to guide daily habits.
- Engaging Narrative: Utilizing metaphors (like his family’s historical boat journey) makes complex future-of-work topics highly accessible and emotionally resonant.
Weaknesses
- Rebranded Concepts: Many of the “SuperSkills” (like curiosity, empathy, and big-picture thinking) are classic soft skills. While repackaged effectively for the AI age, some readers may find these ideas familiar.
- Aspirational vs. Systemic: The framework places the responsibility of “staying the author” on the individual. It doesn’t deeply address systemic corporate pressures where workers are forced to rely heavily on automated, high-speed algorithmic metrics.
Questions and Loops by chatgpt
Hirji’s “operating system” boils down to two things:
- 5 Questions → keep you intentional (not drifting with AI)
- 5 Loops → keep you improving through repetition
I’ll break them down clearly and translate them into real-life use.
🧠 The Five Daily Questions (the “anti-drift” check)
These are meant to be quick, almost like a mental dashboard you revisit daily.
1. What matters here?
Cuts through noise.
AI floods you with options, data, suggestions — this question forces prioritisation.
👉 In practice:
- “Is this actually important, or just urgent?”
- “Am I reacting or choosing?”
2. What is the real problem?
Prevents shallow thinking.
AI is great at solving defined problems — but often the framing is wrong.
👉 In practice:
- Instead of “How do I do this faster?”
- Ask: “Should I be doing this at all?”
3. What does good look like?
Defines success before acting.
Without this, you let AI optimise for convenience instead of quality.
👉 In practice:
- “What would a high-quality outcome look like?”
- “Would I be proud of this?”
4. Where should I use AI vs. my own judgment?
This is the “centaur” mindset.
Not everything should be automated — and not everything should be manual.
👉 In practice:
- Use AI for:
- speed
- drafts
- pattern recognition
- Use yourself for:
- values
- trade-offs
- final calls
5. Am I still the author of this?
The most important one.
This directly fights “algorithmic drift.”
👉 In practice:
- “Did I choose this, or did the system nudge me into it?”
- “Would I still do this without AI suggestions?”
🔁 The Five Loops (how habits actually form)
The questions create awareness.
The loops create behaviour change over time.
1. Learning Loop
You continuously update how you think.
👉 Cycle:
- Try → Reflect → Adjust → Try again
Example:
- You use AI for a task → notice what worked → refine your approach
2. Feedback Loop
You actively seek signals (not just outcomes).
👉 Important distinction:
- Outcome = “Did it work?”
- Feedback = “Why did it work or fail?”
Example:
- Ask others (or yourself):
- “Was this clear?”
- “Did this actually help?”
3. Judgment Loop
This is about improving decisions under uncertainty.
👉 Cycle:
- Decide → Observe consequences → refine judgment
Example:
- When AI gives 3 good options:
- you choose one
- later evaluate: was that the right call?
4. Relationship Loop
You deepen human connection (something AI can’t replace well).
👉 Cycle:
- Engage → Understand → Respond better → Build trust
Example:
- Don’t just use AI to draft messages
- Actually:
- listen better
- personalise communication
5. Energy Loop
Often overlooked — but critical.
Better thinking requires better mental/physical state.
👉 Cycle:
- Manage energy → perform → recover → repeat
Example:
- If you’re exhausted, you:
- over-rely on AI
- make poorer judgments
⚙️ How It All Fits Together
Think of it like this:
- Questions = steering wheel
- Loops = engine
The questions keep you aligned.
The loops keep you improving.
🧩 Quick Real-Life Example
Let’s say you’re working on a report using AI:
You apply:
Questions:
- What matters? → clarity, not length
- Real problem? → communicating insight, not just summarising data
- What does good look like? → actionable + clear
- AI vs me? → AI drafts, you refine argument
- Am I the author? → you rewrite key conclusions
Loops:
- Learning → improve prompts next time
- Feedback → colleague review
- Judgment → which insights to include
- Relationship → tailor for audience
- Energy → don’t rush when tired
⚖️ Honest Take
This framework is useful but not revolutionary.
- The questions are essentially structured critical thinking
- The loops are rebranded learning cycles (similar to feedback systems, agile loops, etc.)
What Hirji does well is: 👉 tie them specifically to AI overuse and loss of agency
That framing makes them more relevant right now.
If you want, I can turn this into a simple daily checklist or 2-minute routine so it’s actually usable instead of just conceptual.