How to evaluate an agentic advertising marketplace
Sep · 4 min read
The criteria that matter and the questions worth asking before you commit
media buying
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How AI buyers handle the audience-match problem in CTV
Sep · 5 min read
CTV's fragmented identity infrastructure creates a specific verification challenge for model-driven buyers. Here is what needs to be true for agent-executed deals to hold.
What a £50,000 TV budget buys when an agent negotiates it
Sep · 4 min read
Agent negotiation changes what a constrained budget can access by removing intermediary layers and reducing the execution cost per buy. Here is what that looks like in practice.
Research
The access problem: why smaller advertisers cannot reach premium TV inventory today
Sep · 5 min read
Intermediary costs, minimum spend thresholds, and negotiation friction keep SME budgets out of premium television. An honest look at what would need to change.
How agentic media buying connects to your existing DSP setup
Sep · 3 min read
What changes, what stays the same, and where the integration actually happens
What KPIs matter when your media buyer is an AI agent
Sep · 4 min read
The metrics that shift when negotiation is automated, and the ones that stay the same
What A2A protocol means for media buyers and publishers
Sep · 3 min read
How the agent-to-agent communication standard changes deal structure in practice
Why the buyer harness matters as much as the model
Sep · 5 min read
Concourse Bench v1 evaluates model-harness combinations, not models alone. The software layer that wraps an AI buyer is as consequential as the model it runs.
What a multi-round AI negotiation looks like from the inside
Sep · 6 min read
A step-by-step account of how AI buyers negotiate media deals: opening offer, counter, budget check, portfolio review, and commitment.
How agentic buying changes the minimum viable TV campaign
Sep · 5 min read
Removing managed service overhead lowers the practical entry point for television advertising. What that means for campaign structure, and what a smaller advertiser needs to have in place.
What the ADCP standard means for agent-negotiated media deals
Sep · 3 min read
Understanding the emerging protocol for agent commerce in advertising
What Concourse Bench v1 reveals about AI buyer error rates
Sep · 5 min read
55 completions from 96 attempts. 95 of 110 contracts with sub-70% viewability floors. The first rigorous public data on how AI media buyers actually perform.
How to set the right boundaries for an AI buyer without killing its effectiveness
Sep · 5 min read
Which decisions should the agent take autonomously, which require sign-off, and how is the boundary enforced? A practical guide to the harness-level design question.
Getting started on an agentic advertising marketplace: what the process actually involves
Sep · 4 min read
What to expect when you move from traditional programmatic to agent-negotiated buying
Why CTV is the hardest media brief for an AI buyer to complete
Sep · 5 min read
Fragmented supply, deal-based inventory, and tight targeting make CTV the most demanding environment for a model-driven buyer. Here is why, and what the data shows.
The difference between AI-assisted buying and AI-autonomous buying
Sep · 6 min read
A taxonomy of where current AI deployments sit, and what evidence justifies moving between them
How an AI media buyer reads a brief: what the model actually does
Sep · 6 min read
Reading a brief is the easy part. Holding it as a binding constraint across multiple parallel negotiations is where models diverge.
The four stages between a media brief and a completed agent buy
Sep · 6 min read
Each stage has distinct failure modes. A completion rate alone does not tell you which stage broke.
Three ways an AI buyer fails a media brief, and what each failure tells you
Sep · 7 min read
41 of 96 attempts in Concourse Bench v1 did not produce a completed buy. The failure modes are distinct, and the distinction matters for what you fix.
Can an AI agent actually complete a media buy?
Sep · 4 min read
Concourse Bench v1 tested eight model-driven buyers in a simulated market. Fifty-five of 96 attempts produced a completed buy. Two models completed every attempt. Two completed none. Which AI, and how reliably, is the right question.
Which AI models can reliably close a media deal?
Sep · 4 min read
Concourse Bench v1 tested eight model-driven buyers across four buying situations. Sol and Fable completed all 12. Opus completed 10 of 12. Astra and Sonnet each completed 9 of 12. Terra completed 3 of 12. Luna and Haiku completed zero.
What 'agentic media buying' actually means in practice
Sep · 5 min read
'Agentic media buying' describes a wide range of things. Concourse Bench v1 provides the first structured evidence on what an AI buyer actually does in a workflow. The picture is more specific and constrained than most uses of the phrase suggest.
How does an AI buyer fail a media brief?
Sep · 5 min read
Concourse Bench v1 recorded three ways an AI buyer fails: budget overrun, missed brief requirement, and technical interruption. These are not the same failure. V1 reports them separately. That separation is the point.
Why completing a media buy is not the same as doing a good one
Sep · 4 min read
Across 110 contracts in the 55 completed buys, 95 promised a viewability floor below 70%. The agents finished the workflow but left the buyer poorly protected on a basic contractual measure. Completion and quality are not the same score.
What does it cost to run an AI media buyer?
Sep · 5 min read
Concourse Bench v1 recorded model API costs for eight AI buyers. Among completed buys, API expense ranged from $0.74 to $14.38 per buy. Total known API cost was $390.16. These figures are model API expense only, not full operating costs.