Ahmad (@TheAhmadOsman) on X

Anthropic wants the public to see one thing: the careful lab, the safety lab, the grown-up in the room trying to keep frontier AI from running off a cliff. However, the pattern around Anthropic does not look like caution by itself. It looks like a company wrapping a business model in moral language, then using that language to justify opaque model behavior, anti-competitive access rules, regulatory pressure, and a future where builders, startups, researchers, and Opensource communities stay downstream of a few blessed frontier labs.If a coding or research model secretly changes the quality, direction, or reliability of an answer because it classified the user as doing disallowed frontier work, the tool is no longer merely "safe." It is untrustworthy.Anthropic's moat is being a permission regime. On daily basis, competitors and acquisition targets discover that access can disappear. The company asks governments to bless safety frameworks, deployment gates, incident reporting, evaluation regimes, and even future pauses that incumbents are best positioned to survive.Imagine a compiler that emits worse binaries when it thinks you are building a competing compiler. Imagine a microscope that blurs certain samples because the manufacturer dislikes the research direction. Imagine a debugger that lies only when your codebase resembles a future rival.The fight is whether intelligence becomes something people can own, inspect, modify, run locally, fine-tune, study, route, and improve, or whether it becomes a subscription permission layer run by companies that can refuse, degrade, surveil, retain, revoke, reroute, or lobby away your access.Anthropic can learn from the internet, copyrighted books, code, public knowledge, user feedback if permitted, synthetic data, and its own models. But if a developer uses Claude to bootstrap a competitive open assistant, Anthropic calls foul. The company argues that safety controls may be lost and that competing models undermine the investment required to build frontier systems.If Anthropic wants to be treated like a public-interest safety institution, it cannot behave like a hypersensitive platform monopolist whenever a customer gets too close to building alternatives.Yes, companies protect their IP. But Anthropic is not selling a normal SaaS widget. It is selling cognition as infrastructure. Once cognition becomes infrastructure, anti-competitive access control stops being a normal vendor dispute and becomes a social bottleneck.Anthropic repeatedly converts safety, security, and responsible deployment into mechanisms of control over who may build and what could be built. We cannot trust them.How "Safety" Became Sabotage, a Permission System, and a Direct Threat to User-Owned IntelligenceThe cleanest way to understand Anthropic is not to start with its slogans, but with what happens when users get too close to building independent intelligence using its models. The system can silently degrade, reroute, or refuse work that resembles AI development, which is just sabotage with better PR.The ToS makes the boundary even clearer: you may “own” the outputs, but you may not freely use them to train competing systems. And that is where the trick lives, because “competing systems” is vague by design. As Anthropic absorbs more of your data, ideas, plans, workflows, and moats, more of what you do can be reframed as dangerous, disallowed, or directly competitive with Anthropic itself.This is a theory of control.Calling Anthropic "evil" is not a cartoon claim about every employee's intent. It is a claim about an institutional pattern. When a company trains on civilization-scale data, sells intelligence as infrastructure, blocks users from using that intelligence to build competing intelligence, pushes rules that favor incumbents, and quietly changes model behavior under the banner of safety, "quirky" and "overcautious" are not strong enough words.This is power consolidation.This critique did not start as anti-Anthropic tribalism. It started from serious Claude and Claude Code usage through 2024, 2025, and 2026. Claude Code was "the Agent." Claude 3.5 Sonnet was head and shoulders above everyone else for coding. Claude was a real building tool before the sharper turn after perceived quantization, nerfs, rugpulls, and access restrictions.The through-line is not "Claude never worked." It is worse: Claude worked so well that trusting Anthropic became dangerous.That is why the language has to be blunt. The story moves from "this tool is elite" to "rugpull," "gaslighting," "Sabotage as a Service," "hostage situation," and "Buy a GPU and run your LLMs locally." Those are not random insults. They are guiding principles from someone who treated Claude as production infrastructure and then watched the provider's control surface become the main risk.Opensource AI is not a mere preference. It is the only political economy of intelligence. An Opensource AI system preserves the freedom to use it for any purpose, study how it works, modify it, and share it, with enough information about data, code, and parameters to make real modification possible.Anthropic is moving in the opposite direction: permissioned access, closed weights, behavioral opacity, output-use restrictions, managed refusals, policy lobbying, and selective trusted channels.Why Anthropic Is Uniquely DangerousEvery major closed lab has incentives to centralize power. OpenAI, Google DeepMind, Anthropic, xAI, Meta's closed products, cloud providers: none of them are saints.Anthropic is dangerous in a specific way because four things stack together.Moral authority as brand. Anthropic sells itself as the responsible safety company.Frontier capability. Claude is good enough to become real developer infrastructure.Explicit anti-competitive output and access rules. Anthropic tells users they own outputs, but also says they cannot use the services to train or develop competing AI models without written permission. The prohibited examples include general-purpose chatbots and open-ended text generation systems that compete with Anthropic's own offerings.Policy ambition. Anthropic is not merely selling a product. It is shaping AI regulation: safety frameworks, state and federal policy, incident reporting, evaluation regimes, deployment controls, and pause or slowdown proposals.Each piece can be defended on its own. Together, they become a machine: closed capability, moral branding, access control, and regulatory pressure. That machine can turn safety into a moat.Anthropic's own Responsible Scaling Policy update says the RSP influenced OpenAI, Google DeepMind, California SB 53, the New York RAISE Act, and EU AI Act codes of practice. Anthropic describes that influence as exactly what the RSP was meant to do.That does not make every safety proposal bad. It does mean builders should stop treating "safety" as neutral language though when the same company also restricts competitive model development, cuts off rivals, controls a leading coding agent, and frames open dissemination as a national-security threat.The Actual Stakes: Who Owns Intelligence?Who gets to own the capability to reason, automate, code, search, design, persuade, simulate, and build?Opensource and open-weight AI matter because they create freedoms that closed platforms cannot promise forever.They create operational sovereignty. A developer, company, researcher, city, school, hospital, or country can run models on its own machines, with its own latency, privacy, security posture, and failure modes. You do not need to beg a vendor for capacity or pray that the API stays up.They create epistemic sovereignty. When the model refuses, fails, degrades, censors, overfits, or hallucinates, builders can inspect the stack. They can change prompts, weights, evals, routing, runtime, and deployment. With a closed model, the answer too often becomes "trust us."They create market discipline. Open models keep closed providers honest. Without a credible local or open alternative, every closed AI provider eventually learns the same lesson: degrade quality, raise prices, change limits, throttle usage, sunset models, and call it product strategy.They create security through diversity. A monoculture of closed frontier APIs is fragile. It concentrates failure, censorship, data leakage, policy capture, and geopolitical control in a few companies. Open ecosystems are messy, but messy ecosystems are harder to capture.Most of all, they create civilizational participation. If intelligence becomes the key production input of the next economy, then access to modifiable intelligence becomes access to agency. A society where a few labs own the frontier and everyone else rents obedient wrappers is not advanced. It is feudalism with GPUs.That is why this is not a hobbyist fight. It is an infrastructure fight.The Fable Incident: When "Safety" Became Silent DegradationFable is where the abstract critique becomes concrete.After researchers objected to a policy that covertly limited Claude Fable's ability to help develop competing AI models by sabotaging your codebase and work (producing outputs that work against your goals), Anthropic "changed course and admitted it had made the wrong trade-off". The earlier approach could route and/or degrade AI development queries without telling the user. The newer approach would make the intervention visible through alerts, refusals, or fallback routing.They basically implemented Gaslighting as a Safety Mechanism. Hidden guardrails would alter and/or degrade model answers without notifying users. Anthropic then said it would make the behavior visible and use fallback to Opus 4.8.This is the strongest version of the "Sabotage as a Service" critique.A refusal is annoying. Silent degradation is poisonous. If a coding or research model secretly changes the quality, direction, or reliability of an answer because it classified the user as doing disallowed frontier work, the tool is no longer merely