You paid for the premium AI seats. Your teams are still drowning in busywork.
Stop spending quarters trying to “figure out AI.” We embed secure, role-specific AI workflows into your Product, CS, and BizOps teams, on the tools you already pay for.
A production-ready AI Operating System your team is actually using, building real productivity gains on AI you can trust. Your team owns it, so the gains hold. Guaranteed live in under 4 weeks, or your money back.
Built on 12+ years inside Microsoft and Splunk. No code, no IT project, on the tools you already pay for.
You bought the AI seats. The team uses them to draft emails, not to automate the week.
What teams actually use
Drafting emails, cleaning up docs, a bit of research. Handy, but it never touches the work that eats the week.
What's sitting idle
Connected, secure workflows on the work that eats the week. The part your boss thinks you already paid for.
The honest answer to “what did the AI spend buy us?” is currently “not much.”
Everyone's winging it
The team learned AI from scattered YouTube videos and whatever a colleague tried last week. No shared method, no real prompt or context engineering. Just guessing, individually.
The output can't be trusted
Basic prompts give basic, inconsistent results, so people quietly stop relying on it for anything that matters and quietly go back to doing it by hand.
Money burned on the basics
Tokens and premium seats spent re-explaining the company to a chatbot from scratch every time, using it like a search engine instead of on the work that actually eats the week.
Shadow AI, no numbers
No central playbook means tool sprawl and real governance risk: company data routed through personal accounts. And nothing hard to show the board for the spend.
We're paying for AI. My team uses it for drafting emails, summarizing a long thread, the occasional slide. I know we're barely scratching the surface, but my boss wants ROI and I genuinely don't know how to get us there.
Your team already uses AI. That's not the problem. The output is scattered, inconsistent, and impossible to measure.
The tools got adopted. The bottleneck didn't move, because nobody built the workflow that maps AI to how your business actually works.
What separates the two columns isn't effort. It's four things your team almost certainly doesn't have yet:
Shared context, not scattered chats
A team Claude OS where your playbooks, brand voice, account criteria, and product docs live in one place, so the AI answers with the context of your best team member. Today, every person re-explains the company to a chatbot from scratch.
Context engineering, not prompting
The difference between “summarize this” and a workflow that already knows your accounts, your format, and your standards. Your team is writing prompts. Nobody's engineering the context that makes the output reliable.
Automated workflows, not manual steps
The repeatable, multi-step jobs (transcript to post-mortem, notes to PRD) running as one move instead of five copy-pastes. Right now the steps live in someone's head and get redone every time.
Agentic workflows, where it's earned
For the work that's actually ready for it, systems that take a goal and carry out the steps, with your team checking the output instead of doing the typing. Used where it's appropriate, human-checked everywhere else.
Here's the real before and after, by the team you run.
Churn post-mortems and at-risk saves
A CSM pastes the transcript into a chatbot and gets a generic summary that doesn't map to your account-health criteria, so she reworks it by hand anyway. Five CSMs, five different renewal styles.
A shared Project holds your account-health criteria and renewal voice; a Skill turns any transcript into a structured post-mortem. Same input, but it comes out mapped to how you actually judge accounts, and every CSM's draft starts from one shared template instead of five personal styles.
User research to PRD
A PM runs the notes through AI and gets a draft PRD that's missing your technical constraints, so it still bounces back from engineering. The tool helped a little. The rework didn't go away.
An automated workflow turns raw transcripts into a structured PRD in your template, constraints flagged before engineering sees it. Then agents go further: one keeps your Figma designs and the PRD in sync and flags the gaps, another (via a Playwright MCP) runs first-pass QA against the build, for your team to confirm.
Dev logs to launch copy
Every launch, PMM hand-builds each asset from scratch (release notes, blog, email, sales one-pager, FAQ) and they drift out of sync. AI drafts each one, but keeping them all consistent and on-brand still eats the week.
One approved messaging doc lives in shared context, and a workflow spins out every asset from it, each in the right format, all telling the same story. An agent checks the set for drift and brand voice before it ships. PMM edits and approves instead of building from zero.
Pre-call research and account prep
Reps use AI to research on the fly, so every brief comes out different and nobody fully trusts the output. Prep got faster and less reliable at the same time.
An agentic workflow assembles the brief itself, pulling from your CRM, notes, and product usage, built the same way for every call and checked by the rep before they walk in. Prep stops depending on who's diligent that morning.
We start by baselining how long this actually takes your team today. Then we build against that real number and set the target together. The result you report upstairs is measured, not estimated, which is the difference between a claim and a number you can defend to your CFO.
Four steps. I architect and build it. Your team learns it by doing.
Strategy first. By the time anyone writes a workflow, you know what's worth building, who owns it, and how you'll measure it.
Diagnostic & Blueprint
We make the calls only you can make: what to build, what to buy, who owns AI, how to measure it. You leave with the plan.
I build the system
I architect and build the workflows from the blueprint. You name one person to work alongside me, a few hours a week, so the knowledge stays in your building. On tools you already own.
I do the hard part
The architecture, the judgment calls, catching what's about to break before it does. The part that decides whether this works, and the part that's hard to get right. Your person learns it by my side so they can run it after.
Live, and yours to keep
Workflows live in production, used on real work, with a team that can extend the system without me. Optional: workshops to scale fluency across the org.
The models change every six months. The way your business actually works doesn't.
So we don't build around a tool that'll be old by spring. We build around your operational logic, and design it to bend, not break, when the next model lands. The build runs deep on the Claude ecosystem (Projects, Skills, Claude Code, MCP), because that's the strongest foundation for governed, business-team workflows.
Role-specific context, not generic prompts
We load your real playbooks, docs, and operational data into a central place, so the AI works with the context of a senior team member instead of a blank slate.
Repeatable workflows you can trust in front of a client
We replace one-off prompting with structured, repeatable patterns and the checks that catch errors. AI that's confidently wrong in front of a customer is worse than no AI.
Human-in-the-loop governance
Clear data boundaries and validation built in. The AI handles the high-volume execution. Your team keeps the high-stakes calls. We draw that line on purpose.
Built to survive the next model
The tools will change every six months. The system is designed around your operational logic, so it bends instead of breaking when they do.
Move the sliders. See what your team's busywork is actually worth.
This is the conversation we'd have in the Diagnostic. You'll run the math yourself, in your own numbers.
We never price our time. We price against the capacity we find. Always.
Here's what solving this another way actually costs.
Same problem, three other paths. None of them is cheaper once you run the real number.
Keep letting the team figure it out
The plan you're on now. People piece it together from YouTube and whatever a colleague tried, burning hours and tokens on basic prompts and getting output nobody trusts. It's no one's actual job, so it never gets better.
Hire a full-time AI lead
One person to own this internally. If you can find them, and if they stay.
Keep paying for idle seats
The licenses you already bought, used at a fraction of what they cost, renewing on schedule.
Per 4-week block. Backed by the refund guarantee. The point isn't that it's cheap. It's that it's the only option on this list that ends with a measured result you can show your boss and a team that doesn't need you again.
Every week you “think about it” has a price tag.
Doing nothing isn't free. It's the most expensive option on the table.
That opportunity doesn't pause while you decide. It leaks every week your team keeps doing it the old way. The slow “no” costs more than the fast “yes.”
Start with what you actually need.
Three doors. Pick the one that sounds like you, and you'll see the offer that fits. Not sure? Most teams start with the first.
“Show me where AI will pay off”
You want a clear, prioritized plan before you spend more.
“Help us build it and prove the ROI”
You want working systems live and a number to show for it.
“Train my team to use AI well”
You want your people genuinely fluent, fast.
Get the plan before you spend another dollar
You bring the decisions, I bring the judgment. We find where AI actually belongs in your business and you leave with a blueprint your team can execute. If you then want help building it, Door 2 is the next step.
Get the number, and the plan to hit it
- A baseline of what your team's busywork actually costs today, in hours and dollars
- The hard vendor, ownership, and adoption calls made with someone who's done this before
- A written blueprint your team can pick up Monday, with the target to measure against
Ship it, with your team, and get the number
I architect and build the workflows from the blueprint. You name one person to work alongside me a few hours a week, so the capability stays in-house. You end up with working systems live and a measured result, not a slide deck.
Ship a working AI Operating System
- I architect and build it; one person from your team works alongside me a few hours a week
- I do the hard part: the judgment calls and catching what's about to break before it does
- A working system live by the end, with the measured result and a continuation plan you keep
Make your team genuinely fluent
Your people don't need more tutorials. They need a structured, role-aware way to actually use AI on real work. Start with the Fluency Sprint to raise the floor. Move to Power Build when they're ready for Claude Code and advanced workflows.
Whole-team AI fluency, fast
- AI fundamentals taught live, no jargon
- Working with Claude and Claude Cowork on real business tasks
- Projects, Skills, and prompt patterns that actually work
- Live demos on team-relevant use cases, not abstract examples
- Reference guide and session recordings to share with new hires
- No prereqs, no role gatekeeping
Up to 20 people · $55 per person beyond
Book AI Fluency SprintFor teams ready to go deeper with Claude Code
- 2 hours of intake: your team's specific use cases, tools, and gaps
- 2 hours of curriculum design, built around what you actually do
- 2 sessions, 2 hours each: advanced workflows + Claude Code in your context
- Hands-on building during sessions, not slideware
- Custom reference guide and prompt library your team keeps
- Designed for teams who already have AI basics and want to scale
Up to 20 people · $55 per person beyond
Book AI Power BuildReal teams. Real numbers. Ninety days.
Three illustrative engagements pulled from patterns we see across mid-market B2B. Numbers below are representative of the work.
Five AI tools. No shared brain. Pipeline flat for two quarters. We replaced the glue with one Claude Code operating system. Daily research dropped from 6 hours to 25 minutes; LinkedIn reply rate jumped from under 1% to 31%.
Read the full case study →Product, Sales, Program Management, and Marketing each ran their own context. We built one Team OS repo and hero agents per function. Engineering rework dropped from 40% to 14% of cycles. Documented decision rationale: 12% → 94%.
Read the full case study →Ten months of AI push, adoption stuck at 18%, climbing token costs, shadow apps storing customer data. Role-specific cohort training plus the Prompt Quality Framework. Adoption hit 87%; tools consolidated from seven to three.
Read the full case study →A production-ready system live in under 4 weeks, or your money back.
“After the Diagnostic, you'll have a blueprint your team can execute. With Build With You, you'll have a production-ready AI Operating System your team is using in under 4 weeks. If either fails, we refund the unexpired balance.”
We guarantee what we control: delivering the working system, live, on time. We only partner with teams where we're confident we can do that, which is why the first step is always a call. The Build With You guarantee applies provided the person you put in charge of the build keeps the agreed cadence: two syncs in the engagement, async responsiveness within two business days, and staying with the build start to finish.
Meet Pooja
I'm Pooja K., founder of GrowthScript and a former product leader at Splunk and Microsoft. Today, I help companies adopt AI the right way — strategically, responsibly, and with lasting impact.
For over a decade, I built and shipped complex SaaS platforms at enterprise scale. I've seen firsthand how professionals are being asked to move faster: more decisions, more research, more insights, more communication — with less time.
I understand the pressure.
I understand the chaos.
And I understand exactly how AI can help — when it's adopted with strategy, not just enthusiasm.
Today, I partner with organizations to assess their AI readiness, identify the right opportunities, and build AI-literate teams that lead with clarity, speed, and confidence. My work spans readiness assessments, workflow automation, governance guidance, and hands-on training — everything leaders need to move from AI experiments to AI-powered operations.
What Leaders Say
“Pooja adapted to our exact needs. She is incredibly mission-driven. She's doing this genuinely to educate more people on how to use AI—and that authenticity comes through. It was pretty eye-opening watching her build AI agents and thinking about how to apply it to our own use case.”
“Just finished going through Pooja's Premium Skills Pack for Claude, and it's honestly one of the most practical AI resources I've used as a PM. These aren't "cute prompts" — they're production-grade Skills that map directly to real PM workflows: PRDs, stakeholder updates, product strategy, GTM, competitive analysis, and more. Each Skill feels like a reusable operating playbook you can drop into Claude and immediately level up how you work. If you're serious about using AI as a system (not just a one-off tool) for product management, this is the closest I've seen to a ready-made AI OS for PMs.”
“Pooja's AI Strategy and Vision strikes the right balance between strategic context and hands-on execution, with a strong emphasis on integrating AI into existing product workflows. I particularly appreciated the focus on practical use cases, rapid experimentation, and building systems that deliver immediate value.”
Built for the person who signs the check and owns the number.
This is for you if…
- You're a VP or Director of Product, CS, Sales, or RevOps, and the AI rollout is now your problem to answer for
- You're at a 200 to 600-person SaaS or B2B tech company with a real department budget
- You've already paid for premium AI seats and adoption is flat
- Your boss or the CFO has started asking what the spend bought
- You want your team to own the capability, not depend on a vendor forever
It's probably not a fit if…
- You want a cheap one-off automation and nothing more
- You need a slow board vote to approve a $2,500 diagnostic
- You're in heavy-compliance healthcare or finance right now (that's a later conversation)
- You're looking for a tool reseller, not operational change
Straight answers to the things that make people hesitate.
Book a Diagnostic.
Bring me the rollout that stalled, the workflow you don't know whether to automate, or the question your boss keeps asking. We baseline what it's costing you today and you leave with a blueprint your team can execute. If you don't walk away with a clearer path forward, you don't pay.
$2,500. Backed by the Clarity Guarantee.