CHAPTERS
Why “Little Tech” needs its own voice in policy
The hosts set up the core problem: policy conversations in DC and state capitals have long been dominated by large, institutional players, leaving startups underrepresented. McCune and Perault explain why startup realities—limited staff, capital, and compliance capacity—require a distinct advocacy lens.
- •Policy rooms often lack representation for startups and early builders
- •Big Tech and Little Tech interests are not always aligned
- •Startups can’t comply with regimes designed for trillion-dollar firms
- •A16Z positions Little Tech as a missing constituency in tech policy
The Little Tech Agenda: origins, pillars, and the 10-year time horizon
McCune outlines how the agenda emerged inside the firm and how it maps to a16z’s “verticalized” policy work across AI, crypto, bio/health, fintech, and defense. Perault adds that venture’s long time horizon demands a stable, trusted ecosystem—meaning smart governance, not a regulatory vacuum.
- •Agenda built to differentiate startup needs from Big Tech “baggage”
- •a16z policy work spans multiple sectors (AI, crypto, bio, defense, fintech)
- •Core pillar: five-person garage teams vs. 1,000-person compliance orgs
- •Long-run ecosystem health matters more than short-term market spikes
- •Safety and trust are aligned with venture incentives over a decade
Clarifying the mantra: “Regulate use, not development”
Perault explains the most-misunderstood element of their framework: focusing regulation on harmful uses rather than restricting model development itself. They argue existing bodies of law—consumer protection, civil rights, and criminal law—provide a robust enforcement baseline, yet the slogan is often misread as ‘no regulation.’
- •They reject “zero regulation” and emphasize governance
- •Regulate harmful uses: fraud, discrimination, and criminal activity
- •Existing consumer protection and civil rights laws already apply to AI use
- •Misinterpretation: “don’t regulate development” gets framed as deregulation
- •Goal is enforceable, outcomes-based protection without crushing startups
How AI policy debates accelerated: Senate hearings, ‘doom’ narratives, and the Biden EO
McCune traces a key inflection in fall 2023 Senate hearings where major CEOs signaled both desire for regulation and discussed existential-risk scenarios. He argues that testimony, combined with broader safety-oriented advocacy, spooked policymakers and helped catalyze rapid regulatory pushes—via executive action and state bills.
- •Early 2023 marks the start of serious AI policy momentum in their view
- •Fall 2023 hearings jump-started urgency and ‘Terminator’ style fears
- •Resulting pressure contributed to sweeping executive and state activity
- •Concerns that proposals were rushed and not well thought through
- •Safety framing became dominant, often at the expense of competition
Effective altruism, think-tank influence, and interest-group dynamics
McCune argues that ‘safetyism’ and doomer narratives benefited from a decade-long head start, with well-funded networks shaping think tanks and nonprofits. They describe their role as playing catch-up to rebalance the debate toward innovation, competition, and practical governance.
- •Claim: EA-aligned networks influenced policy discourse for ~10 years
- •Fear-based narratives can be amplified through nonprofit/think-tank channels
- •They dispute claims that AI industry spending dominates the policy arena
- •Their jobs and advocacy are framed as a counterweight to entrenched narratives
- •EU AI Act and global debates are cited as shaped by safety-first thinking
Big Tech at the table: voluntary commitments and ‘small number of frontier players’ assumptions
Perault points to White House voluntary commitments negotiated by a small set of large AI companies as evidence that Little Tech wasn’t represented. Both warn that recurring policy assumptions—‘only 3–7 companies will build frontier AI’—normalize rules that entrench incumbents and shrink the competitive frontier.
- •Voluntary commitments were negotiated by a handful of major firms
- •Little Tech and future entrants weren’t represented in those deals
- •They reject the idea that only a few frontier builders is acceptable
- •Comforting claims that rules apply to “just a few firms” are alarming to them
- •Competitive diversity at the frontier is their desired market structure
Licensing regimes and open-source restrictions: ‘nuclear-style’ regulation as an anti-competitive trap
They revisit proposals to require licenses to build frontier models and to constrain open source, calling these unprecedented for software and likely to entrench monopolies. McCune uses nuclear regulation as a cautionary tale: well-intended oversight can drastically reduce new entrants and output over decades.
- •Frontier licensing proposals were seriously considered in early debates
- •They compare it to nuclear regulation: high friction, low innovation output
- •Licensing is framed as historically unprecedented for software development
- •Open-source bans/restrictions are still proposed in some state contexts
- •Such regimes risk cementing existing giants and blocking startups
National security, China, and the ‘lock it down’ paradox
McCune emphasizes that overly restrictive domestic regulation can cause the US to lose strategic advantage to China. They argue that attempts to block diffusion—especially of open source—can backfire, pushing global markets toward Chinese alternatives while weakening US soft power.
- •Central claim: overregulation risks the US losing the AI race to China
- •Export controls/diffusion rules seen as contentious and potentially too restrictive
- •Outbound investment limits are seen as more sensible than banning open source
- •Open source is hard to ‘wall off’ and may be globally inevitable
- •Restricting US products can create openings for Chinese market capture
Parallels to crypto: policy debates as proxies for older unresolved fights
McCune draws an analogy to crypto regulation, where battles over tokens sometimes become a proxy for broader securities-law reform. He suggests AI policymaking similarly attracts attempts to re-litigate older internet governance issues (privacy, content moderation, algorithmic bias) by funneling them through AI frameworks.
- •Crypto debates often mask attempts to overhaul securities laws indirectly
- •AI debates can become a vehicle to revisit ‘missed’ telecom/internet regulation
- •AI can be used as a regulatory ‘funnel’ for privacy, moderation, and bias issues
- •They argue this muddies the waters and produces misfit regulatory schemes
- •The result can be complex compliance burdens with unclear consumer benefit
State laws, impact assessments, and the Colorado example
Perault critiques state “high-risk/low-risk” AI frameworks (like Colorado’s) as paperwork-heavy and hard for startups without counsel to navigate. He contrasts this with a more direct approach: explicitly prohibiting the use of AI to violate anti-discrimination law, which targets harm without broad administrative regimes.
- •Colorado-style regimes impose classification, assessments, audits, and paperwork
- •Startups often lack legal/policy staff to comply
- •Governors/AGs seeking rollbacks signals practical implementation concerns
- •Directly enforcing anti-discrimination violations is framed as more effective
- •They argue administrative processes may not achieve claimed bias-reduction goals
Why ex-ante control sounds appealing but often fails in practice
They address fears about future catastrophic harms (bioterrorism, cybercrime) and whether regulating use is enough. Perault argues the legal system generally punishes unlawful conduct rather than preemptively policing predicted wrongdoing, and that preemptive surveillance-style regulation is both intrusive and unreliable.
- •They concede future marginal risks may require new policy over time
- •Regulating purely ex ante resembles predictive policing/surveillance concerns
- •Existing law is a strong starting point, though not necessarily the endpoint
- •They favor targeted additions when incremental risk becomes concrete
- •Prevent-harm-first frameworks often impose high costs with uncertain benefit
Where things stand now: AI Action Plan, open source support, and workforce measures
Perault and McCune say the policy climate has improved relative to two years ago, with greater support for startup-friendly approaches and open source. They highlight under-discussed elements of the AI Action Plan, especially worker retraining and labor-market monitoring to respond to potential disruptions.
- •Shift toward “right-sizing” regulation and reducing burdens that don’t add value
- •Greater consensus on open source as a driver of competition and innovation
- •AI Action Plan reframes the balance: win globally while keeping people safe
- •Worker retraining and labor-market monitoring seen as pragmatic safeguards
- •They emphasize signaling effects: US rhetoric influences Congress and allies
The moratorium fight: perception, coalitions, and political organizing
McCune explains the controversy around a proposed moratorium/preemption concept, arguing it was widely mischaracterized as wiping out all state law for 10 years. He attributes its failure to perception, strong opposition networks, partisan legislative dynamics, and insufficient pro-preemption coalition organization—prompting renewed efforts to coordinate advocacy and political strategy.
- •Public narrative: ‘10-year ban on all state AI law’ vs. disputed textual reality
- •Opposition leveraged established networks and allied industries to block it
- •Reconciliation vehicle made bipartisan support unlikely and margins tight
- •Lesson: pro-standardization stakeholders were not organized enough
- •Response: coalition-building, clearer public education, expanded political advocacy (PAC)
State vs. federal roles: Dormant Commerce Clause, preemption, and a workable standard
They outline a constitutional division of labor: federal leadership on interstate commerce and AI development standards, states enforcing harmful conduct within borders. Perault adds that some state proposals may run into Dormant Commerce Clause issues by imposing heavy out-of-state burdens with limited local benefit—another reason to focus states on harmful-use enforcement while pursuing federal standards for development.
- •Federal role: national market rules and AI development standards
- •State role: enforce criminal/civil harms and police conduct locally
- •Dormant Commerce Clause can constrain overly burdensome state regimes
- •Preferred outcome: avoid a 50-state patchwork that startups can’t navigate
- •Preemption focus is specific—not a blanket elimination of state authority
Next 6–12 months: federal standard, AI literacy, infrastructure, and shifting industry alliances
They predict near-term focus on a federal framework that prevents a patchwork while preserving state enforcement of harms. They also flag workforce training, AI literacy, and infrastructure (energy/data centers), plus potential government resources to lower startup barriers (compute/data access). Finally, they anticipate periods of both convergence and divergence across Big/Medium/Little Tech—and emphasize that their positions follow principles, not party or incumbents.
- •Top priority: targeted federal preemption/federal standard to avoid patchwork
- •States continue policing harmful conduct; federal government sets development rules
- •Additional priorities: workforce retraining, AI literacy, energy/data center buildout
- •Idea: government-backed shared resources to reduce compute/data barriers for startups
- •Industry alignment may fracture; Little Tech lens can diverge from Big Tech when needed
