Bridgehead Prepared for Zubin at Raindrop
Raindrop For Zubin

LLM Observability Sales Playbook

Zubin, we’ll build your new AE’s first 100 accounts in 10 days. The first 25 are below, and they’re yours either way.

If your AE seat stays open another quarter, ignore this. If it doesn’t, the next two minutes are worth it.

What we noticed

You raised a $50M total Series A on September 17 and launched Simulations the same day.

Your Account Executive and SDR roles have been open since August 13, and both are still posted.

  1. August 13 Account Executive and SDR roles first posted
  2. September 17 Series A, $50M total funding, and Simulations announced
  3. November 5 Simulations opened to more teams
  4. November 9 Both roles still open; the first 25 accounts are on this page

What changes for your new AE

Your new AE starts day one with 100 accounts you approved and drafts written to the first five, instead of spending their first weeks finding them. Your posting already tells them how to talk to engineers; this tells them which companies to call first, and why now.

Your first 25 accounts

Picked from how you describe your buyers in your interview and your Series A announcement. Each one has the reason it’s here and the source.

Yours either wayKeep these 25 whether or not we ever talk.
Cut any you wouldn’t callTell us why, and we replace it. We keep going until you’d keep at least 80 of the 100.
  1. Stuut New York · 150+ customers, including Fortune 50 and Fortune 500
    1

    Its agents email, text and call customers about unpaid invoices and log into payables portals. When one sends the wrong dunning notice or posts a payment to the wrong invoice, nobody gets an error. The company says it is growing over 90% quarter over quarter, which is the volume where that stops being visible.

    Signal: Oct 7, 2026 Source
    Buyer: VP Engineering or Head of AI
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.
  2. Kalepa New York · Insurers including W.R. Berkley, Bowhead Specialty and AmRisc
    2

    Its agents decide which risks fit an insurer's appetite. A wrong call there reaches an underwriter's pricing, not an error log. It says work through the platform grew fourfold in the past year and it plans to double headcount in 2027.

    Signal: Nov 6, 2026 Source
    Buyer: CTO or Head of AI
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.
  3. Suki Redwood City, California · 450+ healthcare organizations
    3

    Clinical documentation and clinical reasoning agents serve more than 450 healthcare organizations. You told the Creative Conviction interviewers that when agents are deployed in healthcare, failures are catastrophic. A new Ask feature a week before a raise is a new behavior to watch in production.

    Signal: Oct 13, 2026 Source
    Buyer: VP Engineering or Head of AI
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.
  4. Legora Stockholm and New York · ARR above $200M
    4

    Law firm agents draft and review work a lawyer signs. The raise is explicitly for Legora aOS, an agent operating system, so agent runs will multiply across firms. Wrong clause, missed document: it reads as plausible work product, the failure you called silent.

    Signal: Oct 21, 2026 Source
    Buyer: Head of Engineering or Head of AI
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.
  5. Instinct location not stated in source · Downloaded millions of times
    5

    Its agent books travel, pays bills and cancels subscriptions with its own phone number and computer. A task done wrong costs a user real money. It launched in August and added phone calls and agent-to-agent coordination within weeks, the pace at which behavior changes between releases.

    Signal: Sep 28, 2026 Source
    Buyer: CTO or Head of Engineering
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.
  6. Serval San Francisco · Enterprises including Ramp, Notion and Perplexity
    6

    Catalyst agents reset passwords, grant app access and file requests for employees at large companies. Wrong access granted or a request dropped looks like a normal ticket. It says ARR has doubled every quarter since its Series B, so run volume is climbing faster than anyone can sample it.

    Signal: Oct 29, 2026 Source
    Buyer: CTO or Head of Engineering
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.
  7. GenHealth.ai location not stated in source · $30M total funding
    7

    Its agents carry a prior authorization through EHRs, payer portals and phone calls. A step that silently fails there delays treatment and revenue, and the company says its customers get paid 30% more. That claim only holds if the agents are watched across every portal they touch.

    Signal: Oct 8, 2026 Source
    Buyer: CTO or Head of Engineering
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.
  8. Encore AI location not stated in source · 40+ enterprise customers, mostly financial institutions
    8

    Its agents speak to bank customers using playbooks learned from human relationship managers. Whether a conversation drifts from the playbook is a pattern across thousands of calls, not an exception. Most customers are financial institutions, where that matters.

    Signal: Jul 29, 2026 Source
    Buyer: VP Engineering or Head of AI
    Why it’s ranked here

    A strong fit.

    • Ships an AI agent to real customers or users today, not a demo.
    • The agent does multi-step work with tools, so a failure is silent: no exception, just a wrong result.
    • High stakes: money, health, law or insurance, where one bad run costs a customer.
    • A volume nobody reads by hand: the source states customers, users or actions.
    • Something changed in the last 90 days: a raise, a launch or a new market.
    • Budget and a team to spend it: funded recently and building the engineering team.

Your new AE’s first 100 accounts, in 10 days

The first 25 are above, and they’re yours either way.

Email Kash

We build a handful of these a month, for founders hiring now.

10 days

from kickoff to your team running it

  • 100 accounts you approve, each with the reason
  • Drafts to the first five, in your voice
  • Your team runs it without us
  • Any account you cut, we replace

How does Raindrop sell?

An outside read from your Creative Conviction interview, your Series A announcement, your site and your postings, built to be corrected: tell us anything that’s wrong. Tap a clip to play it from that moment.

What your customers sayFrom Creative Conviction interview with Ben Hylak and Zubin Koticha, Series A announcement: $50M total funding, Account Executive posting
  1. ZKZubin Koticha
    “Some of the best AI companies in the world, Vercel all the way to Fortune 500s, are using us.”
    Zubin Koticha · Creative Conviction interview with Ben Hylak and Zubin Koticha
  2. ZKZubin Koticha
    “trusted by some of the largest enterprises on earth across healthcare, logistics, and more.”
    Zubin Koticha · Series A announcement: $50M total funding
  3. RPRaindrop posting
    “Build relationships with AI engineers, engineering leaders, CTOs, and technical founders”
    Raindrop posting · Account Executive posting
  4. ZKZubin Koticha
    “it was actually very hard to get a sense of where our agents were failing in production.”
    Zubin Koticha · Creative Conviction interview with Ben Hylak and Zubin Koticha
  5. RPRaindrop posting
    “AI agents fail silently, leaving engineers with almost no visibility into how their agents are actually performing.”
    Raindrop posting · Account Executive posting
  6. ZKZubin Koticha
    “Traditional evals depend on pre-defined test cases and primarily measure failures a team has anticipated.”
    Zubin Koticha · Series A announcement: $50M total funding
  7. BHBen Hylak
    “Every single platform at the time would just do token counting, maybe a hallucination score, or sentiment, positive or negative, which is completely useless.”
    Ben Hylak · Creative Conviction interview with Ben Hylak and Zubin Koticha
  8. BHBen Hylak
    “Now we have customers with millions and millions a day, and that is where professional observability really matters.”
    Ben Hylak · Creative Conviction interview with Ben Hylak and Zubin Koticha
  9. ZKZubin Koticha
    “agents are being deployed in finance, military, healthcare, and when they fail it is catastrophic.”
    Zubin Koticha · Creative Conviction interview with Ben Hylak and Zubin Koticha
  10. ZKZubin Koticha
    “AI engineers can now see "what their change will change."”
    Zubin Koticha · Series A announcement: $50M total funding

Words you use

  • “silent failures”
  • “unknown unknowns”
  • “humanity’s last problem”
  • “tsunami of capabilities”

How the list learns your calls

In the first session you react to accounts like these: keep or cut, and why, the way you’d tell a cofounder. Each reason becomes a rule you can read, the pool re-scores, and ten more show whether it learned. Keep eight of ten and the hundred is built on your rules.

  1. You cut one on the call, and say why
  2. It becomes a rule
  3. The pool re-scores
  4. Ten more test it

Which questions can only you answer?

Your interview and your posts don’t say which agent teams you’d never spend a meeting on, or what an engineering leader has to see before they buy. About 30 minutes of you reacting to real accounts answers these.

  1. 1

    Which agent shape closes fastest for your team: a consumer agent with millions of users, or an enterprise agent in a regulated field?

    Rows 1, 2 and 4 sell to regulated enterprises; rows 5 and 11 are consumer agents. Your answer reorders the list.

  2. 2

    Do you sell to the engineering leader who owns the agent, or to the executive who is accountable when it fails?

    Rows 3 and 7 are in healthcare, where the accountable executive is not an engineer.

  3. 3

    Would you open a meeting with a company whose agent only works inside one customer’s systems, like a staffing or billing agent?

    Rows 7 and 9 run inside other companies’ portals and systems.

  4. 4

    Do infrastructure vendors count as buyers, or as partners?

    Rows 23 to 25 and row 22 sell tools to agent builders.

What does your Account Executive’s first morning look like?

Without

The CRM you have now. The early weeks go to learning which accounts you’d call, and why.

With · Account Executive, first morning

  • SStuutDraft written
  • KKalepaDraft written
  • SSukiDraft written
  • LLegoraDraft written
  • IInstinctDraft written

A hundred accounts you approved, the rules behind them and drafts to the first five, so their time goes to buyers.

From week two, your mornings too: one brief, drafts to approve, every message sent by you.

How the 10 days run

What happens in the ten working days?

November 16, 2026 to December 1, 2026. About a day of your time in total.

  1. Before by November 16

    You send the customers you’d clone and three deals that went wrong, plus 10 to 20 emails or posts you wrote. “How you sell” is drafted from your talks and posts.

    You: 20 minutes
  2. Day 1 November 16

    The playbook session: we fill the gaps and correct the draft together. Your CRM is connected.

    You: 2 hours
  3. Day 2 November 17

    Your first rules are written; a few hundred companies are scored against them.

    You: none
  4. Day 3 November 18

    You review the first 25 (talking it through is fine).

    You: 30 minutes
  5. Day 4 November 19

    Your reasons become rules; you see the re-score and judge 10 more. First touches are written in your voice to the accounts you kept, and you read ten. Touches start logging to the CRM.

    You: 30 minutes
  6. Day 5 November 20

    The hundred is built. The research tool is set up; you test it on three accounts you know.

    You: 15 minutes
  7. Day 6 November 23

    The morning run is set up; your first morning, with us.

    You: 30 minutes
  8. Day 7 November 24

    You review all hundred, and any cut is replaced. Team training, session one.

    You: 1 hour 20 minutes
  9. Day 8 November 25

    Your first morning on your own. Training session two, hands-on for each person.

    You: 1 hour plus your morning
  10. Day 9 November 30

    Your second morning on your own. Each person on your team runs the morning alone.

    You: your morning
  11. Day 10 December 1

    Your third morning on your own. A week of touches is in the CRM. Handover sign-off.

    You: 30 minutes plus your morning
Kash Badami

Who builds it?

The person in the video does the work with you, from the first session to the handover.

$100M+in deals sold in a single year
$0 to $10MARR in 12 months, for a company I built
  1. “Kash and I built ERT Credit together in 2021. He took my MVP and turned it into a SaaS that hit $10M ARR in twelve months.”

    Jordan Anderson, CEO, PayStreetgobridgehead.ai/about

  2. “Analytical in approach, technologically-knowledgeable, and earnest in conviction, Kash was able to drive pipeline in a notoriously challenging tech region.”

    JBJason Brandt, Managing Director, Sales, ePlus inc.LinkedIn recommendation, April 2020

Where does this go from here?

Three options. Each one is fine.

Not a fit

Say so in a line, and that’s the end of it.

Not now

Keep the 25 and the read on how you sell, and share them. When the role fills, the offer stands.

Talk with Kash

Ask Kash to call you, or email him. He calls to set up a 30-minute strategy session. Bring your cofounder or your sales leader.

Your new AE’s first 100 accounts, in 10 days

The first 25 are above, and they’re yours either way.

Email Kash

We build a handful of these a month, for founders hiring now.

10 days

from kickoff to your team running it

  • 100 accounts you approve, each with the reason
  • Drafts to the first five, in your voice
  • Your team runs it without us
  • Any account you cut, we replace

Raindrop sales playbook, in brief

Raindrop sells monitoring for AI agents: it finds silent failures in production, traces them to a cause and, since its Series A, simulates changes before they merge.raindrop.ai, Series A announcement: $50M total funding

Zubin Koticha says that when he and his cofounders built their own agents, “it was actually very hard to get a sense of where our agents were failing in production,” and that customers range from “Vercel all the way to Fortune 500s.”Creative Conviction interview with Ben Hylak and Zubin Koticha

The Account Executive role is built for selling to AI engineers, engineering leaders, CTOs and technical founders, and it says the hire will help define the ideal customer profile and sales motion.Account Executive posting

The first 25 accounts for a new Account Executive are companies shipping agents to real customers, each scored on six rules and backed by a dated, sourced signal such as a raise or a launch: fifteen strong fits, six in the middle and four edge cases that test the rules.

Prepared by at Bridgehead · November 9, 2026 · Every source

Questions founders ask

Can’t my AE build this when they start?

They can. But wouldn’t you rather they were selling? Reps spend 28% of their time selling, and the average new AE takes 6.2 months to ramp. This replaces the weeks they would spend building the list and learning what you already know.

28%: Salesforce, State of Sales (7,700+ sellers, 2022) · 6.2 months: Bridge Group, 2026 AE report (158 companies)

How much sooner does my new AE get to work?

From day one, because the accounts you approved and the first drafts are waiting. The average new AE takes 6.2 months to ramp, and at a $200K median OTE that is about $103K paid before they are fully productive. Only 48% of AEs hit quota.

6.2 months: Bridge Group, 2026 AE report (158 companies) · $103K: arithmetic ($200K median OTE × 6.2 months ÷ 12); Bridge Group, 2026 AE report (158 companies) · 48%: Bridge Group, 2026 AE report (158 companies)

We tried an outreach tool and it sounded like a robot. How is this different?

Nothing goes out on its own. Every account on the list is one you approved, every draft is written to one person, and you send each message yourself. It learns your voice from what you’ve written and from every edit you make.

How much of my time does it take?

About a day, spread across the ten working days: the 2-hour session on how you sell, short list reviews you can talk through, two training sessions and your first mornings. The hours your AE gets back go to selling, where reps spend just 28% of their time today.

28%: Salesforce, State of Sales (7,700+ sellers, 2022)

What happens after you leave?

It keeps learning. Each week it proposes rule changes from what your cuts, replies and silences showed, and you approve or reject each in a line.

Where does my data live?

In your own accounts: your Claude, your CRM, your files. Nothing runs on anyone else’s side, and any rule can be changed in plain English.

How is it priced?

The first engagement is one fixed price for the ten days. It depends on how many people we train and which systems we connect, so Kash quotes it on a short call. After handover, you can keep us on a retainer to keep supporting your sales process and refining it, if you choose that route.

The research behind this page 8 sources · 2 postings · 8 customers · 25 stores looked at

Your talks and posts

  1. raindrop.ai
  2. Series A announcement: $50M total funding, September 17, 2026
  3. Creative Conviction interview with Ben Hylak and Zubin Koticha, June 1, 2026
  4. Your Series A post on LinkedIn, September 17, 2026
  5. AI Engineer: Zubin Koticha speaker page
  6. How we built Raindrop: interview with Zubin Koticha and Bucky Moore
  7. Raindrop blog, November 9, 2026
  8. Raindrop careers

Your open roles

  1. Account Executive, first posted August 13, 2026
  2. Sales Development Representative, first posted August 13, 2026

Your customers

Vercel · Speak · Clay · Tolan · Replit · Framer · Avoca · AngelList (santehq.com/customers and your posts). Customer photos are from santehq.com/customers.

How the 25 were picked

25 stores found and scored on 6 rules; the 25 chosen to teach: 15 strong, 6 middle, 4 at the edges. Logos are from each store’s own site.

  • Sources: TechCrunch, AlleyWatch, Law.com, Healthcare IT Today, press releases, PostRound and an October funding tracker, each opened and saved on November 9, 2026.
  • Raindrop customers named on its site, its postings and the seed-round coverage (Vercel, Speak, Clay, Tolan, Replit, Framer, Avoca, AngelList, and the logos on its home page) were removed. Tolan was dropped from the list on this basis.
  • None of the saved pages mention Raindrop.
  • Rows 12, 14, 16, 17, 19, 21 and 22 to 25 rest on a one-line funding source, so their reason is the raise and the category, not product detail.
  • Where the source doesn’t state a location, the row says so.