@ntkris Single turn vs multi turn, the agent as an eval provides potential for a more robust eval or the optionality to construct metrics around the structure of the agent
Recently became aware of this pattern with Browserbase, they allow you to run an agent for a task the first time and the generate workflow code for subsequent runs. The challenge is that then you don’t have the adaptability on follow on runs that you do the first time, though I guess you could bake in a fallback yourself
BREAKING: our AI Agents can now deep-research 10,000 accounts faster (and cheaper) than an Uber from JFK.
Last month our growth team pushed this hard:
40,000 accounts deep-researched for product launches → personalized outreach → 15+ meetings and a closed-won in 30 days.
Most GTM teams don’t lack ideas.
They struggle with the cost and complexity of running them at scale.
@kunal_rye , who leads our agent infrastructure, saw this firsthand.
Adoption climbed past 1M runs per month, but cost was still the ceiling on pushing always-on workflows.
After months of evaluating models against real customer workflows, Kunal & team shipped a major upgrade:
Optimized agents with peak performance at a 10x cost reduction.
Always-on intelligence in outbound becomes practical, not theoretical.
What this unlocks:
If you’re a cybersecurity company, Unify’s optimized agents can:
(1) Monitor your entire TAM for breaches
(2) Auto-qualify accounts if they’re B2B + using Auth0
(3) Use real breach context to write outbound that’s timely, relevant, human
No manual research.
No painful copywriting.
No cost tradeoffs.
The future of GTM is deploying 100,000 deep-research agents daily to understand every shift in your market.
That future is closer than people think.
Despite some of the popular fears that all AI agent use-cases could get sucked into a single platform, I'd argue the other side of this for the enterprise.
AI agents, possibly more than any prior era of tech, need to have a relatively high degree of specialization per domain or vertical. The model can be the same across fields, but the manifestation needs to be highly tuned.
The reason is tied to what the AI agent is doing for the customer. What the customer is doing is "renting work" from the AI agent provider. This is similar to when a company either hires someone for a job or hires agencies or firms to help them.
When you hire people, you hire experts. And when you hire consultancies or professional services firms, you hire a bunch of experts in a particular field. There's a reason you tend to not hire people that are "just generalists", and why professional services firms tend to be optimized around focus areas, like tax, IT, legal, marketing, and so on. The consulting firm does everything either doesn’t exist or eventually specializes by practice area.
The same is true for AI agents. Companies are looking to solve problems in their workflow and business processes, and they're going to want experts to solve those problems, not generalists. You're no longer providing the tool for a person to do their work better, but you're actually supplying a worker to them.
For anything important and value-added for that customer, they’re going to want the best agents that they can afford, similar to hiring talent in the rest of the market. Of course for lots of general purpose work this may not be the case, but for anything where their business is on the line it is.
This dramatically increases the need for a deep domain understanding for the use-cases you're going after; custom UI that is tailored to the domain; access to relevant data just for the domain; and so on. The more general you are the worse off the results will be.
Of course there are nuances to this. Generalists can do specialization if they divide things up to approximate specialization well enough. And equally, specialists can accidentally remain too small and not bite off enough of the problem for the customer. But either way, it's clear that specialization is going to win out in AI for the same reason it has in people.
when model performance stabilizes (we are in one of those periods right now)
people start to evaluate for different objectives:
cost, latency, customizing/differentiating, retaining IP
Announcing @unifygtm for PLG companies
Product-led companies like @Perplexity and @Cursor are turning to Unify to convert their product usage data into revenue
Most PLG founders wait too long to think about enterprise revenue. You scale users, hit PMF, then scramble to hire a revenue team when inbound demand stops supporting hockeystick growth 👇
GPT-5 from @OpenAI is live and powering Unify’s Observation Model and AI agents today.
We’ve worked closely with OpenAI over the last few weeks to test and give feedback on GPT-5 and I'm incredibly impressed with where it came out. We’ve found this is a big upgrade across 3 dimensions: multimodal browser use, tool call efficiency, and steerability:
Perplexity used @unifygtm to book 80+ meetings in 3 months without a single BDR
we'd love to help your revenue team do the same
s/o to @perplexity_ai and @jennysvng for being incredible partners
IN NEWS: @unifygtm has raised a $40M Series B led by @BatteryVentures.
"In early '24, even as a seller, the best thing was to adopt AI to automate tasks." - @austinh___
"Our observation model gives memory to AI, creating a flexible context for better decisions."
"It basically looks like you have a memory associated with every person you have ever talked to."
This morning I received a message from the most famous investor from Silicon Valley... Mr. Tres Commas himself.
This video was produced for me by our friends at Unify who just announced their Series B fundraising.
Congrats to you guys on the Series B and this super creative marketing.
We're going to have to do something like this ourselves :)
Excited to share that we’ve raised a $40M Series B at @unifygtm to transform growth into a science.
Many of the fastest growing companies like Cursor, Perplexity, Flock Safety and Airwallex choose Unify to reimagine growth in an AI-native world.
This round comes just 9 months after announcing our Series A, and was led by Battery with participation from OpenAI, Thrive and Emergence 👇
Update on @0xSplits Compliant Payments:
We've now integrated @withpersona in our new recipient KYC flow.
This allows you to collect W-8/W-9 forms from your recipients securely, compliantly, and accurately.
🚨 Introducing: Unify for Sales Reps ⚡
We’re bringing the power of AI automation directly to the frontline sellers who turn pipeline into revenue.
Sellers today are forced to juggle tools, chase down context, and operate in silos. No more.
Unify for Sales Reps is a new suite of AI-powered features designed to help reps move fast, stay focused, and book more meetings — with less effort.
Today, we're excited to launch:
🧠 AI Research Assistant – Account research done for you
🧩 LinkedIn-to-Lead Extension – One click to enrich and sequence
📞 Manual + automated step sequences – Email, Call, LinkedIn, Action
📥 New Tasks Dashboard – One place for reps to execute, and managers to track
All powered by Unify’s system-of-action for outbound sellers.
🎯 Let Unify can handle the busywork, so that your sales reps can crush their pipeline goals: https://t.co/efzsBh0P5Y
Today we’re launching @unifygtm for Sales Reps.
We don’t believe AI is going to replace people in GTM, we believe its going to make them 100x more effective 🧵
Unify's Connor Heggie and Kunal Rai share their learnings from building and running generalized research agents at scale.
Watch the full session here: https://t.co/tsWK6Qzb9g
Catch up on all the talks from Interrupt: https://t.co/IOva0I5N8e
At @unifygtm , we believe that go-to-market is a search problem. To help the best products win, companies need to find the best prospects for their products to succeed which requires sifting through large quantities of information and signals to determine the best fit.
To continue on our mission towards enabling a way to engineer growth, we are excited to introduce our Observation Model, powered by @OpenAI o3 reasoning model, which underpins our multi agent system that constantly searches and surfaces signals and information about your potential prospects, helping your team take more informed actions.