Agentic Advertising & AI Workflow Advisory.
No Fluff Advisory helps AdTech, MarTech, data, AI, and media technology companies move from isolated AI pilots to governed agentic workflows that can be explained, measured, commercialized, and trusted.
Operator-led advisory from Evgeny Popov — 25+ years scaling AdTech, MarTech, and data businesses across four continents, three exits, and a founding member of AdCP (Signals & Measurement working group). The work is not "add AI." It is deciding which decisions an agent should touch, who is accountable when it does, and how the result gets packaged, priced, and sold.
Who this is for.
Companies where AI has moved past the lab and started touching revenue, customer data, or buyer trust. Strongest fit follows the site's ICP: Series B scaleups (75–200 employees · $10–30M ARR) as primary fit, Series A PMF (25–75 employees · $2–10M ARR) as secondary, and selective Series C / Growth (200–500 · $30–75M ARR) on board-grade decisions.
- AdTech platforms — buy-side, sell-side, or infrastructure — adding agentic capability to the core product.
- MarTech platforms turning AI features into workflows buyers will pay for.
- Data collaboration vendors whose product now sits inside AI-driven decision loops.
- Measurement companies that need their outputs to be machine-readable and auditable.
- Identity companies working out where they sit in an agent-to-agent transaction.
- CTV and media technology companies facing agentic planning and buying on the demand side.
- SaaS platforms adding AI workflows that touch customer money or customer data.
- Companies exploring AdCP, AI agents, or governed decision systems and needing a commercial position, not just a technical one.
Not sure the profile fits? Start with who the practice is built for or the problems it takes on.
The sentences that start this engagement.
If one of these sounds like your last leadership meeting, the timing is right.
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"We have AI demos, but not an operating model."
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"Every team is running a pilot. Nobody owns the workflow."
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"We built AI features, but we can’t package or price them."
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"Buyers keep asking who is accountable when the agent acts."
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"We need a position on AdCP before the market sets one for us."
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"Legal and sales are blocking launches because governance is undefined."
Ten workstreams. One governed system.
Scope is set per engagement — most companies need four or five of these, not all ten. The point is that they connect: packaging without governance stalls in procurement; governance without a buyer narrative never gets funded.
- 01
Agentic workflow mapping
Which decisions in your product and your customers’ operations can an agent assist, recommend, or act on — and which must stay human.
- 02
AI use-case prioritization
Ranking use cases by buyer value, feasibility, and governance cost — not by demo appeal.
- 03
Commercial packaging
Turning AI capability into named, priceable product — tiers, units, and boundaries a buyer can evaluate.
- 04
Buyer narrative
The story a CRO, CMO, or procurement team can repeat internally — what the system does, what it doesn’t, and why it’s safe to buy.
- 05
Risk & governance model
Who approves, who monitors, who overrides, and what gets logged — designed before the first enterprise deal demands it.
- 06
Human / machine handoff points
Explicit boundaries: where the agent stops, where a person signs off, and how exceptions escalate.
- 07
AdCP readiness
How your product expresses intent, context, constraints, and accountability in an agent-to-agent market.
- 08
Measurement & auditability
How agentic decisions are measured, explained, and reconstructed after the fact.
- 09
Operating cadence
The internal rhythm — review loops, ownership, and escalation — that keeps agentic systems governed as they scale.
- 10
Product-to-GTM translation
Closing the gap between what engineering shipped and what sales can credibly sell.
What ships.
Working artifacts, not decks. Each one is built to be used by a named owner the week it lands.
- 01 Agentic workflow map — where AI assists, recommends, or acts across your product and operations
- 02 AI commercial packaging recommendations
- 03 Governance & accountability model
- 04 Buyer-facing narrative
- 05 Internal operating model
- 06 Standards / protocol readiness assessment (including AdCP)
- 07 30/60/90-day roadmap
The question is no longer what AI can do.
AI in advertising can already recommend, route, optimize — and increasingly act. The commercial question is not only what AI can do. It is who is accountable when it does it.
That question decides whether your AI capability becomes revenue. Enterprise buyers, procurement teams, and legal departments do not block AI because they dislike it — they block it because nobody can tell them who approves an agent's action, what gets logged, how a decision is reconstructed after the fact, or where the human sign-off sits. A governed workflow answers those questions before they are asked. An ungoverned pilot answers them in a lost deal.
This is also where standards work becomes commercial work. No Fluff Advisory's principal is a founding member of AdCP — the Ad Context Protocol — in the Signals & Measurement working group, and the site maintains a plain-language guide to AdCP. Protocols like AdCP exist because agentic systems need shared ways to express intent, context, constraints, and accountability. Companies that design for that now will have a structural advantage over companies that bolt it on later. The Agentic Transformation playbook lays out the operating framework this advisory draws on.
Three engagement shapes.
Agentic advisory is not a separate product — it runs through the practice's three engagement models, scoped to where you are. The method is the same in each: diagnose, decide, ship, hand over.
- 01
Market Entry Audit
A 2–3 week diagnostic. Right when you need an independent read on where agentic capability fits your market, buyers, and proof — before committing build or GTM resources.
See the Market Entry Audit → - 02
GTM & BD Sprint
6–8 weeks embedded. Right when the AI capability exists and the job is packaging, narrative, and getting it in front of real buyers.
See the GTM & BD Sprint → - 03
Advisory Retainer
3 / 6 / 12 months. Right when agentic workflows touch ongoing decisions — governance, standards positioning, and commercial calls that keep arriving.
See the Advisory Retainer →
FAQ.
What is agentic advertising?
Agentic advertising describes advertising workflows where AI agents can assist, recommend, negotiate, optimize, or act across planning, buying, activation, measurement, and reporting, subject to governance and accountability rules.
What is the difference between AI automation and agentic workflows?
Automation usually executes predefined tasks. Agentic workflows involve systems that can reason across context, choose actions, coordinate steps, or make recommendations that affect commercial outcomes.
Why does AdCP matter?
AdCP, or Ad Context Protocol, is relevant because agentic advertising needs shared ways for systems to communicate intent, context, constraints, and accountability across the advertising workflow.
Can No Fluff Advisory help package AI features commercially?
Yes. The advisory work can help translate AI capabilities into buyer-facing use cases, packaging, GTM narrative, governance, and operating workflows.
Who is this advisory best suited for?
It is best suited for AdTech, MarTech, data, AI, SaaS, and media technology companies that need to move from AI experimentation to credible commercial deployment.
Deeper background: the essays on agentic advertising, signals, and measurement, the operator track record on the proof page, and who runs the practice. Currently Global Head of Enterprise at Samba TV; NYC-based. Adjacent practice area: AI visibility & GEO advisory — being found when buyers ask AI, not just when agents transact.
Moving from AI pilots
to a governed system?
Bring the pilot list and the buyer objections. The work turns them into a workflow map, a governance model, a commercial package, and a 30/60/90-day roadmap — with a named owner for each.