Kyle O'Brien is a staff reporter at Adweek and editor of AgencySpy. He covers a range of topics including advertising, creative works, and media trends, blending his passion for journalism with his interests in music and food. Kyle's work has been featured in Medium, Hackerlap, Adweek, Campaign US, MM+M, PRWeek, and LessWrong 2.0.
Preston is the artificial intelligence that powers the Intelligent Relations PR platform. Meet Preston
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Kyle O'Brien's coverage primarily focuses on advertising, marketing, agencies, creative rankings, and AOR relationships. Given the emphasis on press releases and private sector announcements, Kyle would likely be interested in receiving pitches related to new agency partnerships or leadership appointments within the advertising and marketing industry.
Pitches centered around innovative uses of technology in advertising or notable campaigns from major companies could also resonate with Kyle's coverage focus. This may include insights into how AI is shaping the future of ad agencies or exclusive details about significant upcoming campaigns by leading brands.
As there is no specific geographic focus mentioned for Kyle's coverage, pitches can center around global developments within the advertising and marketing industry.
This information evolves through artificial intelligence and human feedback. Improve this profile .
How two young creatives from Miami Ad School are helping others find their way into the industry.
The annual survey from Platinum Rye Entertainment focuses on music this year.
By: Kyle O’Brien
Independent partner agencies within the network are set to dedicate a full day to local volunteer efforts across the globe.
By: Kyle O Brien
The new board will collaborate with school leadership to provide industry insight, mentorship and internships throughout the school's global network.
The moves coincide with WPP’s latest consolidation of Grey and Ogilvy’s back-office operations.
Leaders from entertainment, retail, agencies and tech to provide guidance.
By: David Africa, Kyle O’Brien, Puria Radmard, Samuel Ratnam
TL;DR LLMs pretrained on data about misaligned AIs themselves become less aligned. Luckily, pretraining LLMs with synthetic data about good AIs helps…
By: Kyle O Brien
The agency's latest work reframes the upscale fitness brand around ‘aliveness.' by Kyle O'Brien January 08 2026 Sign in to Continue
By: Puria, Cam, Alexandra Narin, Edward James Young, Kyle O’Brien
We're a Cambridge, UK-based AI safety organisation that’s asking: how can we build the most robust alignment initialisations for capable LLMs? …
By: Edward James Young, Alexandra Narin, Puria, Kyle O’Brien, Cam
Comment by Yoav Hollander - Your adversary - "agentic RL with misspecified rewards" - is exactly what I've been working on, from a different field (coverage-driven verification in AV and chip safety). One distinction that might be useful: Misspecified rewards split into ones you could have anticipated (findable by denser testing) and ones where the spec was simply silent on a contingency (price collusion, a mid-campaign rule change, a move nobody enumerated). The second kind is more dangerous, because a stress-test built from misspecifications you can author can't contain them by construction. The post I just wrote about it calls the second kind “spec bugs”, talks about “can you enumerate the dimensions of an open agent”, and suggests enhancing “Teaching Claude Why” with a coverage-driven adversarial RL pipeline. Here it is - would be curious what you make of it.
