Anthropic taps IPO lawyers as it races OpenAI to go public

Original Article ↗ Hacker News Discussion ↗

IPO inevitability and motives

  • Many see the “we haven’t decided” line as routine posturing; IPO is viewed as inevitable to fund massive compute spend and give early investors and employees liquidity.
  • Multiple comments frame the IPO as “finding bagholders” before an AI bubble pops, comparing it to late-1990s dot-com listings and meme stocks.

Profitability, costs, and S‑1 scrutiny

  • A major theme: when they file an S‑1, three years of full financials must expose training costs, inference margins, and actual losses.
  • Some argue inference is solidly profitable (claims of >60% margins industry-wide) and that “unprofitability” is largely an artifact of expensing huge R&D rather than amortizing model lifetimes.
  • Others doubt any “pure-play” foundation model company has a clear path to sustainable profit once training, infra, sales, and brutal competition are included.
  • Anthropic’s reported $1B+ from Claude Code impresses some, but critics note revenue ≠ profit and question whether token sales cover ongoing R&D.

Cloud giants, shovels vs miners

  • Amazon’s decision not to acquire Anthropic is read as strategic: better to sell compute (“shovels”) and take equity/credits than own the full burn rate.
  • The AWS/Anthropic credit-for-equity deals spark debate: some see “Enron echoes,” others insist these are standard, low-risk cloud-growth arrangements.
  • Several think Amazon, Microsoft, and possibly Apple are waiting for a post-bubble fire sale rather than overpay now.

Valuation, bubble risk, and index effects

  • Sentiment tilts bearish on AI IPOs: expectations of huge losses, retail speculation, and eventual crashes.
  • Discussion around potential S&P 500 inclusion notes profitability and seasoning requirements; if it ever happened at a very high cap, index funds would become large, price-insensitive buyers.

Mission, AI safety, and public benefit status

  • Commenters question how going public squares with Anthropic’s safety-first branding.
  • One side claims public companies are legally forced to prioritize profit; others counter that as a public benefit corporation Anthropic is explicitly obligated to balance mission (AI safety) with shareholder returns—though skeptics view all such mission language as ultimately marketing.

Product, moats, and competition

  • Many praise Claude/Claude Code, especially Opus 4.5, as the current best agentic coding assistant; others report frustration with quota cuts and “enshittification.”
  • Strong disagreement on moats: some think tools like Claude Code provide real stickiness; others see models as highly interchangeable with thin defensibility and rapid open-source catch-up.
  • Gemini 3 Pro is repeatedly cited as at least competitive, with some predicting Google will eventually dominate given its data, TPUs, and integration into existing products.