Certified Clay Expert & Agency owner | I'll help you build a scalable outbound engine that gets meetings booked on autopilot in the next 180 days | Visit Youtube: @growth-today to see how

Growth shouldn’t feel random.

Most of the B2B companies hit the same walls:
Inbound leads that don’t convert

Outbound that burns reps out without results

Partnerships that look good on paper but never drive pipeline

A CRM full of noise instead of reliable data


I’ve seen it across founders, sales leaders, and marketing teams. The problem isn’t effort, it’s the lack of a repeatable, scalable GTM system.
That’s what we build at Growth Today.

Instead of disconnected tools or random campaigns, we design and implement repeatable GTM engines across sales, marketing, and partnerships that…

✅ Enrich and qualify data
✅ Activate inbound leads into real opportunities
✅ Automate outbound prospecting
✅ Keep CRMs clean and reliable
✅ Orchestrate multi-channel campaigns
✅ Make BDR teams more effective or fully replace them
✅ Align marketing + partnerships with sales for compounding growth

Recent wins:

 → Built a clean, automated CRM that doubled conversion rates
 → Launched a content-driven demand gen engine that 3x’d inbound lead quality
 → Systematized partner outreach → pipeline from alliances grew 40% in 6 months

Growth doesn’t come from more outreach or more tools.
It comes from building the right system once and scaling it.
If you’re a B2B founder or revenue leader serious about building predictable pipeline, let’s connect.

Book your call: https://calendly.com/growth-today/intro-meeting

Brigitta Ruha

We've run 200+ GTM experiments in the last 18 months and I'm giving away the exact 30-day testing playbook that helped us start growing.

If your GTM team is treating growth like a strategy problem.

Tell them… It's a lab problem.

30 experiments, 30 days, and zero bullshit.

Here's everything what you'll get 👇

✅ System & outbound tests we use to lift reply rates

✅ Messaging experiments that show what actually resonates

✅ Enablement rituals that help your team in learning

✅ Human-first GTM moves that protect your pipeline

Some flopped and some 3x'd our results overnight

But the difference is that we actually ran them

Here's how to get it 👇

1️⃣ Like this post 

2️⃣ Comment "EXPERIMENT" 

3️⃣ Follow me so I can DM you the resource

♻️ Repost this to help other GTM leaders stop wasting time on guesswork

Co-Founder @Growth Today | We Build Repeatable GTM Engines Across Sales, Marketing & Partnerships 🚀

SDRs and GTM Engineers aren't the same role

Companies hire SDRs and expect them to also build systems

They are expected to fix broken tools and automate workflows

Or they hire GTM Engineers and wonder why meetings aren't getting booked

They're both important… just for completely different reasons 👀

SDRs are your frontline. 

They start conversations, test messages, and get buyers to say yes

GTM Engineers are your infrastructure

They build the systems, connect the tools, and make everything scalable

One focuses on people and the other focuses on process.

And when both work together? That’s when the pipeline becomes predictable

You don’t need more AI tools, you need the ones that help you fill the pipeline

These 6 made it to my ‘never launch without’ list 👇

Icypeas 
Find accurate emails fast, no more guessing games

Clay 
Hyper-targeted enrichment + AI-crafted outreach

BounceBan (Verify risky emails without sending messages)
Scale without hitting spam hell

EmailGuard
Warm up your inbox before launch

Ghost
Writes better, faster, smarter, and built for outbound

Attio
Because data > gut feelings

Instantly.ai
Where follow-ups stop slipping through the cracks

Each one saves me hours every week and together

If you’ve got an AI tool that helps you sell smarter not louder… drop it below 👇

12 months, 1 system and a Human-first GTM.

Want to build a human-first GTM system in 2026?

Here's your 12-month roadmap

Most GTM systems fail because they're built for metrics, not humans. This one's different.

We designed this as a step-by-step plan to help you build a system that actually works for your team and your buyers.

✅ Q1: Audit, define, design

✅ Q2: Launch experiments, automate smart, test your co-pilot 

✅ Q3: Make it sustainable, refine what works, align your team 

✅ Q4: Codify learnings, scale intelligently, review & evolve

A simple and clear plan you can actually follow.

Save it, or share it with your team. ♻️

And if you try even one month of this, let me know how it goes. I'm here for the messy progress stories. 😅

If your pipeline strategy fits into a tweet…

it’s probably not a strategy 😅

I get why we chase quick fixes.

One magic channel, or one AI tool that’ll hack your market without having to put in the work.

Sounds good, doesn’t work.

Here’s the part people usually skip:

The real pipeline gets built in the boring middle

the messy work between “send more emails” and “add another tool.”

Nobody glamorizes that part, but it’s exactly where everything changes.

So I put together a quick cheatsheet to show the real difference between:

What people think pipeline building is

vs.

What it actually looks like when it works

Is it more effort than a tweet-sized hack?

Yeah.

Does it actually build a predictable pipeline?

Also yeah.

If you’re tired of advice that sounds smart but doesn’t move the needle,

save this, it’ll make next quarter a lot easier 😉

The #1 reason top reps close more deals?

They know when to stop.

Not stop caring.

Not stop trying.

Just… stop grinding themselves into dust 😅

Here’s what I’ve noticed:

Average reps stay in hustle mode 24/7.

Top reps go hard when it matters —

and then they actually unplug.

Because in sales, your energy is your edge.

You can’t run sharp discovery calls when you’re running on fumes.

Top reps protect their energy the same way they protect their quota.

They show up fully - then they close the laptop, touch some grass, and recharge so they can do it again tomorrow.

Hustle matters.

But knowing when to stop?

That’s a real competitive advantage.

If your sales content isn't working on LinkedIn, it's probably not your fault.

Most of us create content the way we are taught:

- Share insights
- post case studies
- Talk about the product

Sounds right, doesn’t it?

Except... prospects aren't engaging. and the pipeline isn't moving.

The thing is that… instead of posting more, we need to post in a smarter way

Different content types drive different outcomes: →

- Some build awareness but won't book meetings) 
- Some spark conversations (hello, pipeline 👋
- Some establish credibility

So, what do we do now?

Stop creating content that looks good and start creating content that starts conversations

Your prospects are on LinkedIn, they're scrolling, learning, and looking for solutions

The question is… are you showing up in a way that makes them want to talk to you?

Hope it helps 💪

Anas Duksi

Electrical Engineering Intern

As an electronics engineer, I got hooked on systems, logic circuits, models, things that click and scale. I was fascinated by how systems work when they do! 
As a visionary, being able to imagine and understand systems, that obsession stuck..

Now I build AI agents and automations that plug into GTM and Revops

Been deep in SaaS GTM for years - outbound, enterprise deals, RevOps rebuilds, onboarding experiments. I’ve seen where things break. I build the systems that don’t.

Focus now:
→ AI agents as GTM operators
→ Infra that sells and scales without headcount
→ Blending engineering logic with sales instincts

Highlights:
– $200K ARR in <3 months at CozmoX (YC-backed)
– 438% MRR growth at UserGuiding, drove 57%+ new revenue
– Outbound engine + reseller motion at Shiny, >5% CVR
– Rebuilt RevOps at AstroLabs, hit 100%+ quota
– +30% retention, +17% activation at Cura from onboarding flows

What am I passionate about? building clean systems and watching agents in runtime actually doing the work..

Head of Business Development

I’m happy to share that I’m starting a new position as Senior AI Agents Forward Deployed Engineer at Beam AI!

Building AI agents & automations l Beam AI l Kusp AI

The main rules of SaaS still apply to AI agents businesses.. well, mostly..

CLING to the client's problem. That never changes.

But here's what I keep seeing: everyone can build an n8n or LangFlow or whatever automation now. Or Claude Code and Replit for shipping fast.. Prompt chains, agent loops, tool calling - it's all a weekend project. 
The build is commoditized.

So where does value come from?
Not from what you can build anymore. It comes from how long you've been in the trenches with a specific problem, and for whom exactly. 

The edge cases you've already hit. The guardrails you learned the hard way. The deployment speed you've earned through repetition.

AI agents actually open up more room for verticalization than traditional SaaS ever did. 

You're not just automating a workflow - you're encoding JUDGMENT. 
Domain expertise. The stuff that used to live only in people's heads.
That's a deeper wedge. 
And it's harder to copy..

But here's the uncomfortable part: finding that niche - the one that generates real, sustainable ROI - is genuinely harder than SaaS. 

The trust threshold is higher. Clients aren't just buying software. They're betting you won't automate them into a compliance disaster.

Once you earn that trust though? You start layering. SaaS features on top of your agentic core. That's how you expand.

The playbook for 2026 feels clear to me: unless you're already playing infrastructure with serious resources, your leverage is the wedge. 
One use case. Painfully specific. Relentlessly deep..

The generalists will demo well..
The specialists will get paid..

#aiagents #agentic #ai #saas

I believe we're not competing on better processes anymore. We're competing on better context. That's the actual game..

Last decade was about data integration. The edgs was with cleaner pipelines, unified stacks, faster decisions xx. That changed..
We are now playing the context integration game. 

Building a company brain that everyone can talk to. 
Your sales team asks it questions. Your engineers query it for decisions. 

It's the collective narrative- the ideation partner that actually knows your history.

The infrastructure's forming to achieve that but still immature. 
We have now some scattered components, MCPs, RAG which is getting sharper and models scaling context windows.

Nevertheless, the reality is still not as glamorous..

MCP is expensive. It standardizes cross-tool context, but integrating MCP context expands input tokens by 236× on average.
In fact, tool descriptions alone consume massive context window space, and with thousands of tools connected, agents process hundreds of thousands of tokens before even reading a request.

As for LLMs, the bandwidth is costly- 1MB of output costs around $1 per request, and you're billed in every follow-up message that includes that tool result..

At scale, I've seen this get prohibitive fast..
RAG is still fighting fundamentals. Precision and recall aren't solved- chunks misalign, relevant info gets missed, data goes stale..

But I think the vision is right..
This is about creating a fresher brain you can revoke later..

How do we speak better in meetings? 
Think more structurally? 
Document so context doesn't die in Slack? 

I believe the companies that answer this- that build the memory layer right- get an asymmetric edge..

It's not there yet. The tooling is immature. But the shift is real: 
from "do we have the data?"
to 
"can we surface the right context when it matters?"

My advise to anyone building:

Don't wait for perfect tooling. Start documenting with retrieval in mind- structured notes, tagged decisions, searchable context. 
And budget for tokens like you budget for compute..
The companies that treat context as infrastructure, not a feature, will be impossible to catch in 3 years.. 

#ai #aiagents #llms #ml #b2b

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