Lean Into Your Spike
In the AI era, double down on your unfair advantage and stack disciplines to become a unicorn
- Difficulty
- Moderate
- Time to result
- ~months to results
- Steps
- 5
- Confidence
- 80%
Amol's career advice for thriving as AI reshapes product roles: stay on top of the tools, then lean hard into where you have a genuine unfair advantage rather than patching weaknesses. Identify the one skill where you spike, become the best at it, and stack a second discipline on top — a PM who can also design, or an engineer who's deeply product-minded, becomes an 'absolute unicorn' whose value jumps an order of magnitude. Combined with staying adaptable and throwing out old playbooks, this is how you stay indispensable.
Origin
Amol Avasare's synthesis from his own path (founder + investment banker + near-sales + growth) and examples like Anthropic's Nick Lin (ex-banking/PE building financial-services products); echoes the 'sideways-E' / interdisciplinary idea also cited from Marc Andreessen.
Core principles
- 01Staying current on the tools is table stakes — use each model release to find what's newly possible for your job
- 02Double down on your spike and almost forget your weaknesses; being the best at one thing is very valuable
- 03Stacking disciplines makes you a unicorn — a PM who designs, or an engineer who PMs, is dramatically harder to let go
- 04The interdisciplinary edge is where you deliver outsized impact others can't
- 05Adaptability is the meta-skill: throw out 50-70% of your old playbook or face constant friction
How to run it
- 1
Stay on top of the tools
Use Claude Code, co-work, and every new model release to find what's newly possible for your work. A capability that failed last month may work now — if you don't retry, you'll miss it for months.
Pro tip Tool fluency builds product sense around AI products, which is increasingly important regardless of your role.
Watch out A model does something badly today and well next release; failing to revisit means silently falling behind.
- 2
Identify the skill where you spike
Find the major skill set where you're genuinely differentiated and that ties directly to driving impact in a product role — whether craft, or mediating a room of strong-opinioned stakeholders into alignment.
- 3
Double down and almost forget the weaknesses
Rather than shoring up weak areas, invest in becoming the best person at your spike. Depth on a valuable skill beats being evenly mediocre.
Watch out Don't over-index on fixing weaknesses at the expense of a differentiating strength.
- 4
Stack a second discipline to become a unicorn
Layer an adjacent skill onto your spike so you cover a role that's currently stretched — a PM who can design, or an engineer who's highly product-minded. The combination makes you far more useful and much harder to let go.
Pro tip Amol's own stack — founder + finance + near-sales + growth — is what lets him have outsized impact in specific situations.
- 5
Stay adaptable and drop old playbooks
Assume 50-70% of how you operated before is no longer relevant. Meet the changing job by changing with it rather than forcing old playbooks, which only creates friction.
Watch out Anyone who keeps applying old playbooks will make life much harder for themselves.
In the wild
Nick Lin, who came from investment banking and private equity, leads Anthropic's financial-services products (Quip for Sheets and Excel). He builds with a competitive advantage — 'I know this, I know this' — because his prior discipline maps directly onto the domain.
→ Amol expects the products to 'take the market'; Lin's interdisciplinary background gives him outsized impact others can't replicate.
Common mistakes
Spreading thin to fix every weakness
Trying to be adequate at everything produces no differentiation; the leverage comes from being the best at one spike and stacking a complementary discipline, not from patching gaps.
Clinging to old playbooks
Assuming your prior methods still apply in an AI-first environment creates constant friction and irrelevance — Amol says 50-70% of how you operated before must be thrown out.
Is it for you?
Best for
PMs, growth operators, designers, and engineers trying to stay indispensable and high-impact as AI reshapes product roles
Not ideal for
Very early-generalist stages where breadth across many functions matters more than a single deep spike
From the transcript
“leaning into where you have a competitive advantage and an unfair unfair advantage.”
“is a unicorn is an absolute unicorn.”
“probably yeah, 50, 60, 70% of how you operated in the past just throw it out the door.”
From the episode
Head of Growth (Anthropic): “Claude is growing itself at this point”
Amol Avasare