If you are building AI agents for sales or support, do not aim for "almost as good as our best rep." Aim for work no human could do: reading every account's history in seconds, answering product questions with perfect recall, and following up with every lead, every time. Agents built to imitate people inherit their limits. Agents built to exceed them change the economics of go-to-market.
Where this comes from
SaaStr published a write-up of its SaaStr AI annual AMA with 15 hard truths about B2B and AI. The headline lesson is that the team spent a year building agents to reproduce most of what their best human did, and concluded that was the wrong target. Below are the themes most useful for B2B founders, marketers and sales leaders, with practical steps for each.
Related: Build the Dashboard First, Then the AI Agent
Set the bar above your best person
An agent can hold your entire product catalogue, every past conversation and every support ticket in view at once. No rep can. If your agent spec is "do what Sarah does," you cap it at Sarah's memory and working hours.
- Define tasks by outcome, not by how a human does them today.
- List things your team never has time for, such as researching every inbound lead, and start there.
- Measure agents against your top performer's results, not your average.
Go vertical and deep
The AMA argues that vertical agents beat horizontal ones because you can load them with deep domain knowledge. A general assistant knows a bit about everything. An agent trained on your product, your customers' industry and your past deals can be a better domain expert than most humans on the team.
In practice, that means investing in the knowledge you feed the agent: accurate product documentation, clear pricing rules, real objection handling and examples of good answers. The agent is only as sharp as that material.
Related: Where Clicks Go, What Agents Skip, Who's Leaving Bing – SEO Pulse via @sejournal
Product knowledge is now the edge
Another theme is that the most valuable person in a B2B sale is the one who knows the product cold, especially when products change weekly. That applies to humans and agents alike. Buyers now expect instant, precise answers about integrations, limits and pricing.
- Keep one living source of truth for product facts and update it with every release.
- Feed it to both your agents and your sales team.
- Review agent answers weekly for errors and fix the source, not just the answer.
- Test reps on new features the way you test agents.
Plan weekly, judge tools by their slope
SaaStr says the best startups now plan weekly because markets and tools shift too fast for long cycles. It also advises judging AI tools by how much they improve over a 90-day window rather than by today's rough edges. A tool that is clumsy now but improving fast may beat a polished one that has stalled.
- Run a short weekly GTM review: what changed, what we try next, what we stop.
- When trialling tools, record a baseline and re-test after 30, 60 and 90 days.
- Favour a strong signal and real usage over a long vendor bake-off.
Weekly planning does not mean changing strategy every week. It means reviewing evidence often and adjusting tactics quickly, while the bigger direction stays stable for a quarter or more.
Hire curious builders from inside
Rather than searching for a mythical external "GTM engineer," the AMA suggests looking inside your company for curious people who are already experimenting with automation. They know your customers and processes, and they are motivated. Give them time, tools and a real problem to solve.
Set them up to succeed. Pair each builder with a clear owner in sales or support, agree on one metric the automation should move, and review progress every week. Share what works across teams so a good internal tool does not stay trapped in one department. The goal is a small group who can turn a process problem into a working agent within days rather than quarters.
Make your product easy for buyers' agents
One of the sharper points: if a buyer's agent cannot integrate with your product, it will move on without telling you why. More evaluation work is being done by software on the buyer's side. Clear public documentation, open APIs and plain, crawlable facts about pricing and capabilities are becoming part of the sales process.
The same goes for friction in the buying path. The AMA questions gating everything behind "contact sales." Many buyers, human or agent, want answers immediately. Publishing clear pricing and letting people try the product removes a step where deals quietly die.
Point agents at real intent
Agents make follow-up cheap, which makes targeting more important. Sending more automated emails to cold lists just scales noise. The best use of an always-on agent is responding quickly and precisely to people already showing interest.
That is where website visitor identification fits. Happierleads identifies the person and company behind a share of your website visits, scores them against your ICP, and can trigger email campaigns or CRM and Slack alerts. An agent or rep can then follow up with context about what the visitor actually looked at.
Your next step
Pick one go-to-market task your team never has time to do well, such as researching every inbound lead or answering every product question within minutes. Build or buy an agent for it with a goal above your best person's output, feed it a clean source of product truth, and review it weekly. Judge it on its 90-day improvement, not its first week.
