How three years at McKinsey shaped my second startup

Original Article ↗ Hacker News Discussion ↗

Perceptions of McKinsey and Big Consulting

  • Many engineers in the thread view McKinsey/Bain-style firms as:
    • Primarily conflict-resolution and political cover for executives, not genuine problem solvers.
    • Overstaffed with inexperienced Ivy grads doing “expert” work they’re not qualified for.
    • Structurally wasteful: high fees flowing to partners and overhead while juniors do the real work.
  • Others clarify that:
    • The real “consultant” is the partner/principal; juniors are there for data gathering and slide production.
    • Clients often want external validation for decisions they already intend to make (“no one got fired for hiring McKinsey”).
    • The article is appreciated as a rare, plain-English peek into that model, though some find it LinkedIn-like and mismatched with the “know your enemy” title.

Technical vs Non‑Technical Leadership

  • Strong sentiment from some engineers: avoid startups led by non-technical founders who talk in buzzwords; risk of MBA-heavy leadership sidelining product and engineering.
  • Others counter that:
    • Purely engineer-led firms can also fail (e.g., ignoring markets, NIH syndrome).
    • Successful companies need both market understanding and technical competence; failure modes exist on both sides.

Meanwhile’s Vision: AI + Bitcoin Life Insurance

  • The startup’s pitch (world’s largest life insurer, 1B customers, 100 staff, AI + “digital money”) is seen as:
    • Very bold and heavily couched in corporate speak.
    • Ethically worrying if it implies no meaningful human access for claims and disputes.
  • Some argue:
    • Current human-based insurance service is already bad; AI might not be worse and could be faster or more consistent.
    • Others respond that today’s AI support is unreliable and often deceptive, and that life/health decisions are too high-stakes.

Feasibility and Ethics of Radical Automation

  • Industry-experienced commenters detail why life insurance is staff-heavy: underwriting, actuarial work, compliance across jurisdictions, fraud investigation, reinsurance, and complex claims.
  • Many doubt 100 people can responsibly serve 1B policyholders even with strong automation.
  • Broad ethical debate:
    • One side: efficiency and job displacement are necessary and historically beneficial; “protecting jobs” is harmful protectionism.
    • Other side: rapid displacement without robust safety nets is harmful; quality of service and fair dispute resolution are core ethical issues, not just employment counts.

Bitcoin, Regulation, and Tax Structuring Concerns

  • Heavy skepticism about tying life insurance to Bitcoin:
    • Life insurance is supposed to be safe and boring; Bitcoin is volatile and speculative.
    • Operating from Bermuda and using BTC-borrowing to reset cost basis looks, to some, like a tax-avoidance and regulatory-arbitrage scheme more than consumer protection.
    • Concerns about long-term counterparty risk, potential “rug pulls,” and the opacity of AI-based claims handling in a lightly regulated jurisdiction.

BigCo vs Startup Dynamics

  • Some agree with the article’s implicit thesis:
    • Large regulated incumbents are extremely risk-averse and structurally bad at disruptive innovation.
    • Startups can win by taking business risks incumbents can’t and by exploiting incumbents’ organizational blind spots—not just via better tech.