Context Collapse in Paid Media: An Emerging Threat
There’s a dangerous assumption in digital marketing: that the more AI tools, automations, and integrations we have, the smarter our campaigns will become.
But what if the opposite is happening?
Wil Reynolds, VP of Innovation at Seer Interactive, recently brought attention to a growing issue in the AI landscape, context collapse caused by an overabundance of tools. While his post was rooted in AI agent behavior, the core problem maps perfectly to paid media.
The lesson? An overly armed agent, much like an overly stacked media team, can quickly become directionless. And the more tools we connect without discipline, the harder it becomes to maintain clarity, strategy, and ultimately, results.
The Paid Media Stack Is Bloated and It’s Hurting Performance
Over the past five years, the average paid media team has gone from managing campaigns to managing a fragmented tech stack:
Performance Max (Google)
Meta Advantage+
Dynamic creative tools
AI-powered bid optimizers
Attribution modeling software
Auto-generated audiences
Rule-based script engines
Third-party dashboards
Chatbots, copywriting tools, and GPT wrappers
Each tool was designed to improve a specific part of the workflow, but collectively, they’ve created a bloated ecosystem. The result is what Wil describes as a ballooning action space, a term from AI modeling that reflects all the choices an agent (or strategist) can make at any moment.
The wider the action space, the harder it becomes to make the right choice.
Real-World Example: Performance Max Gone Wild
Take Google’s Performance Max campaigns. They promise automation, scale, and ease. But when layered with:
Custom scripts for budget pacing
GA4-based audience segments
Offline conversions via Zapier
Data overlays from third-party CRMs
Creative refresh logic from internal tools
…you create a campaign that’s too complex to troubleshoot, let alone optimize. And when performance tanks? Good luck finding the root cause. Was it the asset group? The audience signal? The API lag? The CRM push? You’ve created a black box of your own making.
Why Paid Media Is Especially Vulnerable
Unlike static AI tasks, paid media is dynamic, fast-moving, and revenue-driven. Campaigns must adapt in real time to:
Auction pressure
Market volatility
Seasonal trends
Creative fatigue
Channel behavior
When you add dozens of tools, each with their own logic, you reduce your ability to respond intuitively. Instead of solving problems, you’re debugging your stack. And worse, you begin to rely on the stack as a crutch, rather than applying first principle thinking.
A Call for Strategic Reduction
Here’s the truth most won’t say: you don’t need more tools you need better clarity.
Some guiding principles:
Less is more. One smart automation beats five unmonitored ones.
Know your stack. If you didn’t configure it, don’t depend on it.
Revisit your north star. Tools should serve your strategy, not the other way around.
Embrace friction. Not all manual work is bad—it forces pattern recognition.
Document logic. Every automation, every rule—know why it exists.
Conclusion: Smarter Isn’t Always Wiser
In an era where AI dominates the conversation, it’s easy to lose sight of the basics.
The best paid media strategists in the world aren’t those who know the most tools they’re the ones who can solve problems with the fewest. Let’s not let our campaigns do the same.
John Williams, a veteran media buyer managing millions in ad spend, approaches AI like a football coaching staff rather than a single tool. His systematic approach transforms how marketers can leverage AI for better campaign performance.
The Multi-Layer AI Framework
Williams breaks ChatGPT-5 into specialized roles:
"If you treat AI like one voice, you miss the nuance," Williams explains. Each layer operates like specialized coordinators, owning distinct parts of campaign management.
Boundaries Drive Better Results
The key insight: constraints improve AI output. Williams feeds his AI tools real numbers—breakeven ROAS, tracking limitations, market conditions—creating actionable recommendations rather than theoretical ideals.
"A lot of marketers treat AI like it's supposed to give them 'the' answer. I treat it like a staff meeting—multiple informed perspectives inside a defined frame."
The Four-Layer Planning System
Each layer uses AI for acceleration but maintains human decision-making authority.
Practical AI Applications
Williams uses Cursor as his "practice field"—building automated scripts, testing budget pacing tools, and simulating campaigns without live spend. This combination lets him run more scenarios in an afternoon than previously possible in a month.
The Human Advantage
"The more powerful the tool, the more important your judgment becomes," Williams notes. AI processes data and flags anomalies, but humans decide based on context—client risk tolerance, competitive climate, and timing within business cycles.
Key Takeaways for AI Implementation
Williams sees AI as compressing feedback loops from days to hours, enabling faster adaptation when campaigns face unexpected challenges. The future involves real-time cross-channel coordination, but human strategy and boundary-setting remain essential.
"The plays are faster, the tools are sharper. But the fundamentals haven't changed: respect the game, know your numbers, define your boundaries, and trust your prep."
We live in a world full of shortcuts. 🚨
Instant solutions. ✨
Overpriced tools. 💸
Surface-level “experts.” 😬
But real 𝙙𝙞𝙜𝙞𝙩𝙖𝙡 𝙢𝙖𝙧𝙠𝙚𝙩𝙞𝙣𝙜? It’s strategy, not speed. Depth, not just data. And most of all — 𝙞𝙩’𝙨 𝙝𝙪𝙢𝙖𝙣.
After 15 years in the trenches of 𝙥𝙖𝙞𝙙 𝙨𝙚𝙖𝙧𝙘𝙝, 𝙨𝙤𝙘𝙞𝙖𝙡, and 𝙖𝙙𝙫𝙚𝙧𝙩𝙞𝙨𝙞𝙣𝙜 𝙨𝙩𝙧𝙖𝙩𝙚𝙜𝙮, here's what I've seen (and lived):
🧠 𝘽𝙚𝙞𝙣𝙜 𝙖 𝙩𝙝𝙞𝙣𝙠𝙚𝙧 𝙢𝙖𝙩𝙩𝙚𝙧𝙨 𝙢𝙤𝙧𝙚 𝙩𝙝𝙖𝙣 𝙟𝙪𝙨𝙩 𝙙𝙤𝙞𝙣𝙜.
Too often, we’re rewarded for execution without vision. But if you’re not aligning to 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙤𝙗𝙟𝙚𝙘𝙩𝙞𝙫𝙚𝙨, you’re just checking boxes.
💬 𝙒𝙚 𝙣𝙚𝙚𝙙 𝙢𝙤𝙧𝙚 𝙚𝙢𝙥𝙖𝙩𝙝𝙮 𝙞𝙣 𝙢𝙖𝙧𝙠𝙚𝙩𝙞𝙣𝙜.
This isn’t just about messaging. It’s about understanding clients, internal teams, customers — 𝙖𝙣𝙙 𝙮𝙤𝙪𝙧𝙨𝙚𝙡𝙛.
💥 𝘼 𝙡𝙤𝙩 𝙤𝙛 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙮 𝙘𝙡𝙖𝙞𝙢𝙨 = 𝙝𝙤𝙩 𝙖𝙞𝙧.
If someone can’t explain 𝙘𝙤𝙨𝙩 𝙥𝙚𝙧 𝙡𝙚𝙖𝙙, 𝙍𝙊𝘼𝙎, or 𝙖𝙪𝙙𝙞𝙚𝙣𝙘𝙚 𝙨𝙚𝙜𝙢𝙚𝙣𝙩𝙖𝙩𝙞𝙤𝙣 clearly, you’re not speaking with an expert — you’re hearing a pitch.
🛠 𝙄𝙣𝙫𝙚𝙨𝙩 𝙞𝙣 𝙩𝙤𝙤𝙡𝙨 — 𝙗𝙪𝙩 𝙖𝙡𝙨𝙤 𝙗𝙪𝙞𝙡𝙙 𝙮𝙤𝙪𝙧 𝙤𝙬𝙣.
Most 𝙖𝙙𝙫𝙚𝙧𝙩𝙞𝙨𝙞𝙣𝙜 𝙩𝙤𝙤𝙡𝙨 are priced for perception. Building internal systems — even something as simple as a smarter Google Sheet — can outperform what you’re paying thousands for.
🤝 𝘼𝙜𝙚𝙣𝙘𝙞𝙚𝙨 𝙤𝙛𝙩𝙚𝙣 𝙤𝙫𝙚𝙧𝙘𝙝𝙖𝙧𝙜𝙚 𝙛𝙤𝙧 𝙢𝙞𝙣𝙞𝙢𝙖𝙡 𝙬𝙤𝙧𝙠.
Yes, I said it. Not all — but many. Strategy should drive cost, not vanity dashboards or templated audits.
There’s no golden sauce to this.
But there 𝙞𝙨 discipline.
There 𝙞𝙨 learning.
There 𝙞𝙨 heart.
And yes, there 𝙞𝙨 room for empathy in how we run our ads, show up to work, and treat the people we serve.
If you're navigating the 𝙖𝙙𝙫𝙚𝙧𝙩𝙞𝙨𝙞𝙣𝙜 𝙬𝙤𝙧𝙡𝙙, let’s talk shop — not fluff.
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👣 #𝙥𝙖𝙞𝙙𝙨𝙚𝙖𝙧𝙘𝙝 #𝙙𝙞𝙜𝙞𝙩𝙖𝙡𝙢𝙖𝙧𝙠𝙚𝙩𝙞𝙣𝙜 #𝙖𝙙𝙫𝙚𝙧𝙩𝙞𝙨𝙞𝙣𝙜𝙨𝙤𝙡𝙪𝙩𝙞𝙤𝙣𝙨
💡 #𝙚𝙢𝙥𝙖𝙩𝙝𝙮𝙞𝙣𝙢𝙖𝙧𝙠𝙚𝙩𝙞𝙣𝙜 #𝙖𝙙𝙫𝙚𝙧𝙩𝙞𝙨𝙞𝙣𝙜𝙩𝙤𝙤𝙡𝙨 #𝙖𝙜𝙚𝙣𝙘𝙮𝙧𝙚𝙡𝙖𝙩𝙞𝙤𝙣𝙨𝙝𝙞𝙥𝙨
🧠 #𝙚𝙭𝙥𝙚𝙧𝙩𝙞𝙨𝙚𝙞𝙣𝙖𝙙𝙫𝙚𝙧𝙩𝙞𝙨𝙞𝙣𝙜 #𝙢𝙖𝙧𝙠𝙚𝙩𝙞𝙣𝙜𝙘𝙝𝙖𝙡𝙡𝙚𝙣𝙜𝙚𝙨 #𝙨𝙤𝙘𝙞𝙖𝙡𝙢𝙚𝙙𝙞𝙖
In this conversation, John Williams discusses the transformative impact of AI and GPT agents on marketing and advertising. He emphasizes the importance of innovation, creativity, and automation in campaign building while also exploring the differences between manual and automated bidding strategies. Williams advocates for a proactive approach to using AI tools and encourages marketers to embrace change and test new strategies, particularly with Performance Max as a forward-thinking advertising solution.
In this episode, John Williams explores the transformative impact of AI on digital marketing, particularly in the realm of advertising. He discusses the evolution of AI tools, the importance of understanding Performance Max, and how marketers can leverage AI to enhance their strategies. The conversation emphasizes the need for creativity in campaigns and the necessity of adapting to the changing landscape of advertising. Williams warns that those who do not embrace AI and automation may find themselves obsolete in the near future.