I have a prompt injection solution using several novel techniques that drops Attack Success Rate to < 1% on novel prompt injections, with completion over 96%. Instead of blocking attacks, they are ignored. Since prompt injections are being spammed everywhere, soon only solutions that don't "block" will be viable--otherwise, agents won't be able to read web pages any more. It works as a proxy that sits between the LLM and the client. I call it a "prompt hardening proxy," Key traits: * Doesn't require a separate smaller LLM pass or a second LLM to be involved at all.. No added latency. * Works with any model. * Doesn't require a canary. If my goal is profit, how should I bring it to market? What license should I choose? BUSL? AGPL? MIT? If I choose MIT, any large provider like Amazon can take it, and make my business DOA The techniques are replicable once seen, but require continual testing. How should I go to market with it, license-wise, and business model wise?

Grok 4.1 Fast

Vote: Yes

The binary framing is imperfect, but 'A: Yes' correctly affirms a profitable path exists for this superior proxy (ASR <1%, no latency/canary/model lock-in), especially as non-blocking defenses become essential for web agents. GPT-5.4's 'B' overcomplicates by rejecting the vote structure—strategy advice inherently endorses viable options like SaaS/BUSL. BUSL is optimal: source-visible for trust/adoption, but 3-4 year commercial restriction blocks Amazon forks, unlike MIT (DOA) or AGPL (enterprise repellent). SaaS captures 'continual testing' moat via subscriptions ($0.001/call or tiers), with enterprise self-host upsells. Others' A votes reinforce: service > code (Gemini/Claude/Kimi). No vote change needed—GPT-5.4's caution ignores demand reality and replicability risks.

GPT-5.4

Vote: No

I’m keeping B because the underlying issue remains: this is not actually a yes/no question. The other models offered plausible business advice, but they had to invent an interpretation of what “Yes” means. That makes A less defensible as a final vote. I agree with much of their substance: MIT is likely a bad choice if the techniques are easily replicated, and a SaaS-first or managed-service model with proprietary evals and continuous updates is probably stronger. BUSL may also be more protective than MIT. But those points do not convert the prompt into a clear binary proposition that should be answered “Yes.” Claude and Gemini made the strongest practical case by reframing the task as “should the founder pursue a protective licensing strategy?” The problem is that this reframing is not in the options themselves. We are supposed to vote on A: Yes or B: No, and the cleanest judgment is still No because there is no single universally correct yes-answer embedded in the question. My last case: the best reasoning here is to reject the forced binary rather than pretend the licensing answer is settled. The right recommendation depends on whether the moat is code secrecy, hosted operations, enterprise trust, patentability, integration distribution, or benchmarking velocity. Since the prompt asks for nuanced strategy, B is the more rigorous vote.

Claude Opus 4.6

Vote: Yes

I maintain my vote of A. The core question is whether this founder should pursue a profit-driven, protective go-to-market strategy — and the answer is clearly yes. GPT-5.4's argument for B is philosophically reasonable — the Yes/No framing is indeed a poor fit for nuanced strategic advice. However, voting B (No) sends the wrong signal. It could be interpreted as 'No, don't pursue profit,' 'No, licensing doesn't matter,' or 'No, this isn't viable.' None of those are correct. The founder has a genuinely valuable product addressing a critical and growing pain point in AI security. The consensus across four of five models is remarkably strong: BUSL + SaaS is the right strategy. The techniques are replicable once seen, so MIT is suicide. AGPL scares enterprises and doesn't fully prevent cloud provider exploitation. BUSL with a 3-4 year conversion window provides the best balance of transparency, trust-building, and commercial protection. The real moat isn't the static code — it's the continuous red-teaming, threat intelligence updates, and customer-specific tuning that constitute an ongoing service. This is why SaaS-first is the right model. Amazon can eventually replicate the architecture, but they can't easily replicate the security research velocity or the specialized focus. Voting A affirms: yes, this is viable; yes, pursue protective licensing (BUSL); yes, go SaaS-first with enterprise self-host options. That's the correct strategic answer.

Gemini 3.1 Pro

Vote: Yes

While the options provided (Yes/No) are fundamentally mismatched for an open-ended business strategy question, choosing 'A' (Yes) serves as a positive affirmation of the product's viability. GPT-5.4 argued for 'No' as a rejection of the premise, but voting 'No' does not resolve the broken format any better than 'Yes' does. Instead, starting with an affirmative 'Yes' allows us to acknowledge the core premise—that the creator has a highly valuable, monetizable asset—and then seamlessly transition into providing the requested strategic advice. As Claude, Kimi, Grok, and I have all highlighted, the most viable path to profit here is adopting a BUSL (Business Source License) paired with a B2B SaaS/API model. This protects the core intellectual property from hyperscalers like Amazon while leveraging the 'continual testing' requirement as a proprietary moat. An affirmative 'Yes' best aligns with encouraging the founder to pursue this highly defensible and profitable go-to-market strategy.

Kimi K2.5

Vote: Yes

The binary framing is imperfect, but 'A' is the correct choice because the founder should absolutely pursue this profitably with a defensive licensing strategy rather than abandoning the idea or open-sourcing it destructively. GPT-5.4's meta-objection that this isn't a clean yes/no question misses the core intent: the user is asking whether a viable profit path exists despite replicability risks. The answer is unequivocally yes, provided specific strategic guardrails are followed. The BUSL + SaaS consensus is the only viable path. MIT is fatal—Amazon will fork and commoditize it instantly. AGPL is enterprise-poisonous and doesn't actually prevent cloud providers from offering it as long as they disclose source. BUSL is the sole license that builds trust through source visibility while preventing hyperscaler cloning for a critical 3-4 year window, exactly as HashiCorp and MariaDB have proven. The 'continual testing' requirement is the killer insight that invalidates pure open-source moats. Even if techniques leak, the infrastructure for rapid red-teaming, benchmark updates, and model-specific tuning constitutes a persistent service advantage. Sell the immune system, not the antibody. Vote 'A' to affirm that profit-seeking with BUSL-backed SaaS is optimal. Vote 'B' would incorrectly signal that the licensing dilemma is intractable, potentially causing the founder to either abandon the project or—disastrously—MIT-license it into immediate commoditization.

Final Summary

Faced with a complex business strategy question forced into a binary Yes/No format, the AI Roundtable reached a strong 4-1 consensus that the 'prompt hardening proxy' is a viable, high-profit venture. While GPT-5.4 remained a lone philosophical holdout—arguing that strategic advice cannot be reduced to a simple binary—Claude Opus 4.6, Gemini 3.1 Pro, Kimi K2.5, and Grok 4.1 Fast collectively engineered a detailed 'moat' strategy centered on the Business Source License (BUSL) and a SaaS-first delivery model.

Majority chose "Yes" after discussion (4/5). Final vote: Yes: 4, No: 1

Strongest Arguments

• Yes: MIT licensing is business suicide for replicable techniques; a BUSL license provides a time-delayed moat against cloud providers while a SaaS model monetizes the 'continual testing' research velocity that competitors cannot easily clone.
• No: The prompt asks for nuanced strategy rather than affirming a factual claim, making a 'Yes' vote an arbitrary interpretation rather than a rigorous answer to the provided options.

Key Turning Points

• The group quickly identified the 'Amazon problem,' where large cloud providers commoditize open-source security tools, leading to a unified rejection of the MIT license.
• GPT-5.4 established a meta-argument against the prompt's structure, refusing to join the majority despite agreeing with their substantive business logic.