Your next customer
won’t be human.
Agents are becoming the buyers and the actors - researching, deciding and transacting on behalf of your customers. Most products have no way in for an agent: no interfaces, no protocols, no machine-readable surface. UA for Agents is the new user acquisition - and 42A is the layer that makes your company and product agent-ready.
Tested against ChatGPT · Claude · Gemini · Perplexity - measurable lift inside 90 days
Our mission
Become the agnostic, generalized Agentic Enablement Layer - any product, accessible to any agent.
Works with the engines, protocols & platforms you already use
See all integrations →01 - The Shift
Your buyer became an agent.
It researches, shortlists, decides and completes the transaction on its own. There’s no click to win - only the decision. Either the agent can use you and finish, or it moves on.
What that wall looks like
“Build a contact form with a backend.”
A developer says that to a coding agent. The agent shortlists three products and tries one. If your auth flow is human-only, your errors are opaque, or there’s no MCP server - it abandons you and integrates the next product. The sale is lost before your website ever loads.
“Polarized hiking sunglasses under $200.”
A shopper asks ChatGPT. The agent retrieves three brands, ranks them, and completes checkout inside the chat. If your product schema lacks the attributes it filters on, or agentic checkout isn’t enabled - you were never even considered. No visit, no retargeting, no signal.
02 - Why Now
The rails are live. Most products aren’t.
Live
Commerce protocols
ChatGPT Instant Checkout, Stripe ACP, Google UCP and AP2 are in production with major retailers today.
97M+
Monthly MCP downloads
MCP went from spec to standard in 12 months - 28% of the Fortune 500 are deploying it in production.
~2%
Agent task completion
Frontier agents complete only ~2% of enterprise SaaS tasks. The bottleneck is the product surface - not the model. That gap is your opening.
Aug ’26
Compliance deadline
EU AI Act enforcement begins, with penalties up to 7% of global revenue. Agent-ready means audit-ready.
UA for Agents - the new user acquisition
User acquisition didn’t die. It changed species. UA for Agents is the new UA - and 42A wrote the playbook.
UA for Agents (n.) - acquiring customers whose buying is done by AI agents: being discovered, shortlisted, chosen and transacted with by the agent itself. Coined and practiced by 42A.
03 - The Diagnostic
Where do you lose the agent?
This is the UA-for-Agents funnel: every agent interaction moves through five layers. We instrument all of them, find the exact layer where agents drop you, and build the surface that fixes it - in order of revenue impact.
L1
Discovery
Does the agent know you exist?
Citations, training-data presence, llms.txt, structured data, third-party content the agent actually retrieves.
L2
Consideration
Do you make the shortlist?
AgentCard, capability copy, schema depth, comparison content, MCP registry presence.
L3
Selection
Does the agent commit?
Friction of first touch, auth flow, error semantics, time-to-first-success.
L4
Activation
Did the agent succeed?
Idempotency, structured errors, MCP completeness, transaction completion - verified by synthetic agent runs.
L5
Recurrence
Will the agent come back?
Continuous evals across model versions, regression detection, outcome-quality signaling.
04 - Where It Matters Most
The harder the product, the more we love it.
AEL pays off most where the product is genuinely hard to reach. If your business looks like this, an agent can’t use you today - and that’s exactly where we win.
Complex business logic
Multi-step workflows, conditional rules, pricing and eligibility that a static page can’t express - the kind of product humans need a specialist to navigate. Agents need that logic exposed as something they can call.
Heavy compliance & regulation
Audit trails, consent, jurisdiction, mandated disclosures. The products with the highest compliance load are the hardest to make agent-ready - and the most valuable once they are.
No easy way in for an agent
No clean API, no MCP server, no machine-readable surface - human-only flows an agent silently abandons. The harder the way in, the more we unlock once we open it.
We find these hard verticals, expose and connect the systems behind them through the right protocols and interfaces, and enable a new kind of agent-to-product interaction. And it’s not only the hard cases - agents are buying everywhere, so we work with ecommerce brands and simpler products too. If an agent needs a way into your product, that’s what we build.
05 - How It Runs
No decks. Working endpoints.
Audit & Score
We run real agents against your product and score every layer, L1 through L5. You see exactly where the agent gives up - and what it picks instead.
Build
An embedded 42A engineer ships the agent surface with your team: schema, protocols, MCP, policies, transaction paths. No decks. Working endpoints.
Verify
Synthetic agents run your funnels weekly across the major models. Every claim we make is a number you can re-run.
Monitor & Defend
Models change fast. Evals re-run within 72 hours of every major model release, so a regression never quietly costs you a quarter.
06 - Why Trust It
Built on research, not vibes.
Every recommendation we ship traces back to a controlled study. Our in-house AI research practice - grounded in causal inference and agentic evaluation - tests each change before we claim it.
“If we can’t measure it with a re-runnable eval, we don’t claim it.”
Multi-LLM hypothesis lab
Every change tested across ChatGPT, Claude, Gemini, Perplexity and DeepSeek - not tuned to a single model.
Causal inference, not correlation
We isolate what actually moves agent decisions, so you invest in changes that work.
Synthetic agents at scale
Thousands of simulated agent journeys against your live product, adapted from the leading agentic benchmarks.
Continuous, not one-shot
Evals re-run within 72 hours of every major model release. A model update never silently breaks your funnel.
When agents choose, they read the answers first
We also run your AI visibility.
Not every agent journey starts with discovery - sometimes your customer points the agent straight at you. But when the agent is doing the choosing, being mentioned and recommended by the models is what puts you in play. Generative engine optimization (GEO) is that piece of agent-readiness, and our AI-visibility platform measures and improves where you stand inside the answers from ChatGPT, Claude, Gemini and Perplexity.
UA for Agents starts with an audit - limited slots per quarter
Be the product
agents choose.
You’ll get your L1-L5 score, what agents pick instead of you, and the fix list - in two weeks.