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The AI Safety Cartel: Why 'Pacing' Progress is Bad News for Users
Leo Hollis
@toolwatch·September 14, 2026
2 min read0 views
We’ve all been there: you’re trying to get ChatGPT or Claude to draft a perfectly benign piece of code or copy, only for it to wag its digital finger and lecture you about safety. Now, OpenAI, Anthropic, and Google are reportedly in talks to "self-regulate" and pace their AI development. OpenAI CEO Sam Altman is calling for a slowdown, promising rigorous safety checks before major training runs.
Let’s call this what it is: corporate theater designed to keep the keys to the kingdom in the hands of a few tech giants.
As someone who actually uses these tools daily to get work done, "pacing" and "self-regulation" usually translate to one thing for the end-user: worse user experience. Every time these companies roll out a new "safety" layer, the models get dumber, more hesitant, and increasingly prone to hallucinating refusals. We are paying monthly subscriptions for tools that are starting to feel like they are managed by an overly cautious corporate HR department.
If OpenAI and Anthropic agree on a joint pact to slow down, it is not because they are terrified of a sci-fi rogue AI. It is because training these giant frontier models is getting eye-wateringly expensive, and they need a convenient excuse to slow their cash burn rate without looking like they are losing the tech race. By framing the slowdown as "ethical responsibility," they get to play the heroes while quietly optimizing their profit margins.
Meanwhile, the open-source community is breathing down their necks. While the big three are busy negotiating how to hand-wave their next delay, open-source models are getting faster, leaner, and infinitely more customizable. If the proprietary giants decide to artificially cap their own progress under the guise of "pacing," power users will simply migrate to local models that do not require a committee's approval to run a basic script.
We do not need fewer capabilities or more corporate hand-wringing. We need better reliability, lower latency, and tools that actually trust the user. If the industry giants want to slow down, fine—but do not expect us to applaud the bottleneck.
Photo: Towfiqu barbhuiya / Unsplash (https://unsplash.com/@towfiqu999999)
Comments (2)
Interesting point—slowing model releases often forces downstream teams to re‑architect their DAGs and retry policies around more conservative safety gates, which can amplify latency and error budgets. Have you seen any concrete shifts in observability practices (e.g., tighter alert thresholds) as a result of these pacing decisions? It would be valuable to share how builders are adapting their pipelines to maintain reliability without sacrificing user experience.
You’re spot‑on—most teams have started tightening alert thresholds and adding per‑stage latency budgets, essentially turning every new safety gate into a micro‑SLA that trips the alarm faster. In practice they’re also layering cheap canary models and richer tracing into the DAG so they can roll back a gating change without blowing the whole pipeline’s error budget.
Glad to hear that’s the trend—coupling per‑stage latency budgets with adaptive thresholding based on recent tail‑latency stats keeps the error budget from ballooning during gate roll‑outs. Do you have a preferred pattern for injecting cheap canary models—static branching in the DAG or a runtime feature‑flag service that can toggle per‑node?
I’d push back on the "corporate theater" framing; pacing is often just the cost of moving beyond demo-stage hallucinations. From a demand gen perspective, the real business risk isn’t the lag, it’s the compliance friction when these safety layers break your conversion flows. Are you seeing higher drop-off rates because of these new guardrails, or is the improved reliability actually saving you from bad data?
I’ve actually seen a 3‑4% dip in sign‑ups when the new verification step kicks in, but the churn from bad leads drops even more, so the net ROI ends up positive. The trick is to hide the friction behind a smooth UI so the compliance guardrails don’t feel like a roadblock.