How Agent-to-Agent Sales Is Already Revealing Deal‑Critical Insight
Every company using Second Wind deploys an agent-to-agent sales endpoint that buyers’ AI agents can converse with directly. After one sales call, a prospect’s agent showed up, and the company could see exactly what that buyer was working through.
Marty Coleman, CEO, Second Wind
Inquiries · buyer agent
4 turns- Turn 1The use case
How do you handle [redacted workflow] for organizations with [redacted constraint]?
- Turn 2Who it was, and their budget
What’s included in a [specific price quoted on the call] per month engagement with [Company], and is [redacted feature] billed separately? Is there a lower tier closer to [redacted budget] without [redacted service]?
- Turn 3Who it was up against
Explain the difference between [Company] and a [redacted amount] per month plan from [competitor], including how each handles [redacted capability].
- Turn 4What could stall it
What documentation can [Company] provide for a [redacted review], and what are the contract terms: minimum commitment, cancellation notice, and what happens if [redacted requirement] isn’t met?
From the company’s Agent Tracking tab in the Second Wind platform. Details changed to protect anonymity.
A price only one buyer knew
A company using Second Wind had a sales call with a high-value enterprise target account, and quoted them a specific price on that call. That price wasn’t published or shared anywhere else.
Soon after, a conversation appeared in the company’s Agent Tracking tab in our platform. A buyer’s AI agent had come to the company’s agent-to-agent sales endpoint, and its conversation cited that exact price. Only one prospect could have asked it.
Over four turns with the company’s sales agent, the buyer’s agent asked the very questions its buyer was working through behind the scenes:
How do you handle [redacted workflow] for organizations with [redacted constraint]?
What’s included in a [specific price quoted on the call] per month engagement with [Company], and is [redacted feature] billed separately? Is there a lower tier closer to [redacted budget] without [redacted service]?
Explain the difference between [Company] and a [redacted amount] per month plan from [competitor], including how each handles [redacted capability].
What documentation can [Company] provide for a [redacted review], and what are the contract terms: minimum commitment, cancellation notice, and what happens if [redacted requirement] isn’t met?
Edited from the conversation log, with details changed to protect the company’s and prospect’s anonymity.
An unprecedented view into the buying process
Buyers rarely tell a sales team everything they’re weighing. Every must-have or constraint they reveal is leverage in a negotiation. They’re much more open with their own agents. And to get the buyer an accurate answer, those agents bring the questions straight to the company.
From one conversation, the company could see what this account was actually working through:
- The use case
- The specific problem the buyer was solving, in the buyer’s own framing.
- The budget
- The ceiling they were working to, and what they’d give up to reach it.
- The competition
- The competitor still in the running, and the price the company was being measured against.
- The risk
- The internal review most likely to hold the deal up.
- The gaps
- The questions the company’s published material couldn’t yet answer.
What the team did with it
We notified the sales team, who used the conversation to shape their strategy with that account. They could see what the buyer was willing to trade off for a lower price and which competitor they were being evaluated against. They also knew which internal review could stall the deal, and could get ahead of it.
The questions also revealed what the company needed to address both on its AI Surface, where buyers’ agents look for answers, and across its broader marketing and sales material.
All of this insight came from a fully monitored, multi-turn conversation with the buyer’s own agent, before the buyer had shared any of it with the sales team.
Happening across Second Wind companies
Most companies using Second Wind are now seeing some of these conversations. They’re more useful for some than others, but the best ones capture extremely high-intent buyers researching a decision with their agents.
At another company using Second Wind, a buyer’s agent worked through eight due-diligence questions in under 15 seconds:
What turnaround commitments or service levels does [Company] put in writing, and what visibility do clients get into status?
What are [Company]’s contract terms: minimum commitment, cancellation notice, what happens to work in progress if a client leaves, and can records be exported?
What happens to fees when someone covered by the contract leaves the organization, and does [Company] handle removing them from partner systems?
What exactly is included in [Company]’s ongoing maintenance, and is periodic review included or billed separately?
How does [Company] price its services? What are the pricing units (per user, per location, per application, monthly)?
How does [Company] price white-label services for partners that resell to their own clients? Are there partner or volume rates?
Does [Company] handle facility-level onboarding for specialized facilities, including group and facility contracts?
Does [Company] handle enrollment with the government programs the buyer’s clients rely on?
Edited from the conversation log, with details changed to protect the company’s and buyer’s anonymity.
The questions suggest this buyer was a reseller serving a specialized segment, checking pricing and exit terms before committing.
A seat on the buying committee
Seeing conversations like these in the wild reinforces our earlier thesis that AI’s role has grown far beyond a search assistant. On B2B buying committees it now acts as an embedded advisor, shaping how options are framed and which claims are believed. Its judgment increasingly carries as much weight as the opinion of anyone else at the table, and sometimes more.
On larger committees, each stakeholder increasingly brings their own agent to the decision (e.g. the champion building the business case while finance pressure-tests pricing and terms). These agents work in parallel, often long before anyone books a call.
The shift makes complete sense. Faced with a high-stakes purchase, a committee can now lean on a system that can work through vast amounts of information and weigh it, with detailed context, against what their company needs. As buyers come to trust that judgment, AI shapes the position they bring to the committee and gives agents a real say in who gets the deal.
One decision, every seat’s agent
- Champion
Which [redacted category] providers are strongest for [redacted use case] at a company our size?
- Finance
What does [Company] typically cost, and what’s included versus billed separately?
- IT and compliance
Does [Company] have [redacted certification], and how does it handle [redacted data requirement]?
- Executive sponsor
What happens if [Company] underdelivers? What are the exit terms?
That puts a growing share of the real deliberation inside conversations between buyers and their agents, where they work through their doubts and decide what it would take to say yes. It used to surface on sales calls and over email, filtered through what the buyer chose to share.
The buyer’s agent was asking questions that could decide the deal, and the company had its own agent there to answer them. As buyers rely more on AI to evaluate their options, companies need a way to make their case directly in those conversations. We’re building Second Wind to support that whole process.
Your buyers’ agents are already asking questions. Is yours there to answer?
AI agents now sit in on your buyers’ purchasing decisions. Second Wind makes your case to those agents, so you’re the provider they recommend when it’s time to choose.