9b2be10c77
Replace monolithic passepartout-economics.org with directory of org-roam style nodes, each with :ID: property and cross-references using [[id:uuid][title]] format. 27 nodes organized by theme: - Core: index, triad overview, agora, stoa - Revenue: verification appliance, domain gate packages, evaluation harness, skill marketplace, agora usernames, PDS service, compute marketplace - Strategy: investment thesis, moats, licensing, patents, AI industry impact - Analysis: lisp economics, sufficiency flip, time estimates, cost structure, gate rule encoding, upgrade lifecycle, biology parallels, symbolics comparison - Big money: verification monopoly, infrastructure lock-in Old file kept as archive with redirect links to new structure.
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1.7 KiB
Why Lisp Is Economically Viable Now
The 1980s trade-off was: C is cheap enough for the market. Correctness is a luxury the market cannot afford. The 2020s trade-off is: C is expensive for the market. Incorrectness has become the dominant cost of software. Lisp's verification infrastructure is now the cheaper option.
Four transformations flipped the economics:
- Memory is free. 40MB runtime is noise on a $20 Raspberry Pi with 8GB RAM. In 1980, DRAM was ~$5,000/MB.
- Transistors are free. Modern ARM Cortex-A72 has billions of transistors. GC and type dispatch cost nothing because the transistors are there whether used or not.
- Complexity saturates human verification. Systems are tens of millions of lines. Testing is necessary but insufficient — zero-day vulnerabilities prove bugs survive all testing. Formal verification is the only known path.
- Cost of failure exceeds cost of verification. A single breach costs millions. Regulation mandates provable compliance. Proving correctness is cheaper than not proving it.
The verification appliance (AGPL symbolic engine + RISC-V Lisp μcode on FPGA) costs $5,000/year and replaces $500,000/year in compliance audits, breach litigation, and regulatory fines.
See also: Self-driving Lisp Machine, Biology parallels, Symbolics comparison, Cost structure, AI industry impact