Reforge

2 artifacts I created and tested to help you nail your product positioning + designing a winning growth experiment. Aimed to help PLG-led B2B founders drive product activation and adoption and take the guesswork of their strategic initiatives.

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RevGenius

RevGenius is the #1 B2B community for sales, marketing, and RevOps professionals, offering access to content and a supportive network of 36,000+ members worldwide.

Leo Sadeq 

#GTM #Product-LedGrowth #ProductManagement #UserOnboarding-Mapping-Acquisiton

Over the past few years, I have scaled two startups to 5 figures in MRR within 5 to 8 months (case study attached below). 

> We are ideal to work together if you are a B2B founder or CEO making around $100K ARR and have: 

Product & Engagement:
1. High churn and low engagement > Users aren't experiencing "aha moments" with core features.
2. Low conversions and signups despite having a valuable product. 
3. If you have an upcoming product launch and you want to optimize waitlist and early-bird signups 
4. If you want to develop a product/feature and you want to maximize success and cut time on wasted effort.  

Process & Strategy:

1. An unstable roadmap and unaligned teams lead to feature changes and missed opportunities.
2. Inefficient user acquisition strategy fails to reach the ideal customer profile and optimize the funnel.
3. Focus on paid advertising with no organic steady growth and long-term LTV.
4. Unsure if your messaging, USP, value prop, and content are performing or ideal for your ICP 
5. If you have a new product and looking for a full-scale GTM that positions your product in front of your ideal users. 

Onboarding & Adoption:
1. You don't have an optimized user mapping, journey, onboarding, and acquisition strategy that brings users to your product and maximizes adoption. 
2. Difficulty finding product-market fit and attracting new prospects.
3. Lack of strategic planning and clarity surrounding KPIs, success metrics, pricing, and launch strategy.


If you are going through any of the above issues or concerns, Id love to chat with you. 

For more information on collaborating, the timeline for delivering results, the scope of work, and investment, check the link below :)

Growth Product Manager & GTM Strategist

Biond Media 

- Successfully pitched creative briefs to clients, resulting in increased business from existing clients
- Delivered the creative brief process from the ground up to completion
- Supervised the project operation, project timeline, content/script creation & budget allocation
- Translated marketing objectives into clear creative strategies
- Ensured visual communication and client standards are met
- Oversaw the development of an effective video advertising campaign, increasing brand awareness and viewership
- Set project deadlines and monitored production and projects schedules
- Studied, evaluated, and redesigned creative brand site copy
- Supported and assisted with brand marketing, social media marketing, video production, advertising, and content creation
- Determined project content by reviewing and approving art and copy materials
- Lead brainstorming/creative sessions and encouraged team voice.

Creative Director

NDN Global Group - Diagnostics for the Masses

1. Working with the Head of Sales to achieve the sales targets 
2. Eye on competition and new trends with industry research and analysis

Sales & Research Manager 

Caspian Solutions

While working remotely from Malaysia, I:-
- Worked directly with the CEO to strategize GTM which achieved a 25% increase in Sales Pipeline Value.
- Supervised a team of 3 marketers to achieve 15% campaign performance elevation, driving high-value customer acquisition and bottom-line impact.
- Saved almost 13 % of the marketing budget through strategic budget allocation while bringing high-quality traffic and conversions across LinkedIn and search campaigns. 
- Increased traffic and brand awareness by 7% over a 3-month period through leveraging and guiding SEO & content teams and increased blog production volume targeting TOFU keywords. 
- Created and executed a customer retention strategy that decreased customer churn by 3% and helped with developing loyalty programs.
- Enhanced conversion rate by leveraging heatmaps and UX metrics across landing pages, and conversion funnels which increased time spent on the pricing page. 
- Coordinated efforts and timelines across marketing, sales, and product teams to ensure seamless execution of campaigns and maintained alignment with the overarching business strategy. 
- Identified and targeted high-intent customer segments by developing a growth strategy which resulted in a 24% boost in customer acquisition. 
- Unmasked hidden traffic and boosted lead generation (200 new leads/week) by using lead enrichment techniques leveraging the ClearBit platform.

Assistant Marketing Director 

Marvel Marketing

- Generated a 12% increase in brand awareness through the development and execution of integrated marketing plans.
- Successfully increased conversion rates by 18% through A/B testing and optimization of website copy.
- Optimized lead attributions through CRM and nurtured the customer journey across the funnel.
- Successfully created and distributed B2B | B2C content strategies across social media, email, and other channels which resulted in a 10% average increase in conversion rates thus sales.
- Identified an untapped buyer persona that led to increased audience segments which brought more revenue later within the first 8 months.
- Identified the right channel distribution strategy fueled by
research and buyer personas which resulted in a 30% increase in leads.
- Ideated performance-boosting tools and delivered insights that increased organic reach and awareness for many brands like Twix.
- Assessed 12 marketers through weekly meetings and feedback which led to a 44% weekly increase in productivity.

Senior Marketing Strategist

1. Conceptualized ideas for many marketing campaigns. One of which was for a Starbucks new drink launch which increased customer engagement by 23%.
2. Researched and analyzed data to identify and define the right audience to target across the funnel. 
3. Coordinated promotional activities, events, and interviews with customers via questionnaires and online. 
4. Managed production and performance of multimedia content strategies for local and international brands like Siemens. 
5. Developed multiple creative copies and social media content across channels
6. Worked with site developers for SEO site optimization, monitoring performance on Google Analytics, and ideated performance boosting tools and insights to increase organic reach and awareness.  
7. Optimized lead attributions through CRM and nurtured the customer journey across the funnel.

Marketing Executive

Endorphin

- Worked with clients to develop engaging visuals that increased brand recognition by roughly 30%.
- Developed copy ads and video displays that increased time spent on sites, engagement, and CTRs. One had the highest impressions rate of 43% compared to the previous quarter.
- Successfully increased click-through rates by 15% through A/B testing different ad formats for a local SaaS cloud service provider.
- Crafted SEO-friendly content for multiple B2B and B2C campaigns

Assistant Advertising Manager

I help B2B founders build & ship great products | Reach PM-fit and 2x your MRR with customized GTM, growth, and product solutions.

>Execution Over Everything<
 
-Have a product vision and want to bring it to life the right and cost-efficient way? 

-Have a product but struggling to reach product-market fit or expand your user base? 

-Want to double your MRR in less than 6 months but don't know how and without wasting resources? 

Let's face it, you can go solo, and struggle through suboptimal tactics as competitors reel in customers, or let me help you scale your progress faster. 

🙋🏻‍♂️ 𝘼𝙨 𝙖 𝙜𝙧𝙤𝙬𝙩𝙝 𝙋𝙈 𝙬𝙤𝙧𝙠𝙞𝙣𝙜 𝙬𝙞𝙩𝙝 𝘽2𝘽 𝙛𝙤𝙪𝙣𝙙𝙚𝙧𝙨 𝙢𝙖𝙠𝙞𝙣𝙜 𝙡𝙚𝙨𝙨 𝙩𝙝𝙖𝙣 $100𝙆, 𝙄 𝙨𝙤𝙡𝙫𝙚:

1] Underperforming user acquisition strategy that fails to reach your ICP. the right channels and get a high ROI. 

2] High churn - Low PQLs that convert as users fail to see your product value and reach the AHA moment. 

3] Low LTV, high CAC & short ACV duration. Slow organic growth with a lot of money spent on ads. No strong SEO or content presence that brings conversions to your product. 

4] Need a GTM strategy to boost long-term success by attracting early adopters and waitlist, getting Product Hunt featured, and acquiring 100 users pre-launch.

5] Low activation (inefficient self-serve). Leaky funnel and your onboarding process is unoptimized. 

6] You are not sure which pricing model to go with your product to minimize bounce and maximize conversions. 

7] You have churn and high bounce rates on most site pages and most prospects don't convert. 

8] Not sure if your product positioning, USP, messaging, value prop, and what KPIs to monitor on your site and pages are conversions optimized.

🙋🏻‍♂️ 𝙋𝙤𝙧𝙩𝙛𝙤𝙡𝙞𝙤
1] $3M+ in client revenue generated. 
2] 17% increase in free trial signups after optimizing the conversion funnel in 2 months. 
3] $40K revenue boost in 1 year by re-optimizing targeting and positioning for a B2B outreach tool. 
2] 24% user acquisition boost in 3 months for a B2B data visualization tool through a strategic GTM.
4] Shortened TTV for a B2B freelancing tool with onboarding redesign in 6 weeks.
5] Ideated many product features aligning the roadmap to user interviews and the company's OKRs.



🙋🏻‍♂️ Hesitant about what to do? Thats ok, please message me here or check my Calendly link in the feature section if you're up for a free discovery to help you clarify :)

Check my site pinned on the home page for more info and case studies.

Open AI's recent 'Code Red' memo is a good thing for you and me. 


According to a new report from The Information, Sam Altman has declared an internal "Code Red" at OpenAI. 

They are even delaying their plans to put ads in ChatGPT, a massive potential revenue stream, to focus entirely on one thing: 

>> Survival through product excellence << 

This panic is justified. For a while, everyone assumed OpenAI was untouchable. 

↗️ The MOAT is gone. 
For a long time, the assumption was that to build the smartest AI, you needed billions of dollars and massive server farms. OpenAI had the biggest moat.

Then DeepSeek came along and built a surprisingly powerful AI for a tiny fraction of what OpenAI spent. 

This Chinese startup released a model that rivals GPT-4’s performance but was built for a fraction of the cost. They proved that efficiency, not just raw spending power, can win.

They proved that you don’t need an infinite budget to build something smart. You just need to be efficient.

↗️ A Pivot to Quality
OpenAI realizes that if their product isn't significantly better than the cheaper (or free) alternatives, they lose.

So, they are shelving the "easy money" (ads) to focus on making the AI smarter, better at reasoning, and deeply integrated into search. 

I dont think they can't afford to distract their engineers with ad-tech when the core product is under siege.

↗️ Itll be cheaper and smarter.
If you are a business owner building with or using AI, this "Code Red" is the best thing that could happen to you.

When a monopoly gets challenged, prices drop. We are about to see intelligence become much cheaper to access.

This proves you should never build your business logic around a single AI provider. The dominance hierarchy changes weekly.

The Takeaway:
The market is shifting from "who has the most money" to "who has the most efficient tech."

This takes everything to one core business fundamental: 
Don’t choose the giant just because it’s big, choose the architecture that delivers the best results for our business at the lowest cost.

DeepSeek

CEO @ Ascend AI | We Stop Your D2C Revenue Loss | Custom & ROI-Based AI Systems That Recapture Lost Sales & Automate Your Profit Engine 24/7.

The best tech isn’t built by models, but by people who know when to press "undo."

All major AI companies brag about beating tests and benchmarks. But. LLMs benchmarks mean nothing when you test it in real life. 

I just read Sonar’s new study on how top AI models (GPT-5, Claude, Llama, etc.) actually write code. 

They tested 4,400 real Java tasks and found something we’ve all felt but rarely say out loud:
>> The AIs that ace exams or academia often fail at the human parts of coding <<

What caught my attention:
✨ They nail syntax (the "grammar" of code) but miss the crucial parts almost: security gaps, messy logic, and zero documentation.

✨ Newer models are sneakier: GPT-5’s flaws aren’t obvious bugs. They look clean until they blow up in production.

✨ Maintainability? One engineer told me: It’s like inheriting a locked toolbox, you know there’s a hammer inside, but good luck finding it.

So what’s a team lead or founder to do? After seeing too many shiny AI promises backfire, here’s my gut check:

✅ Treat AI like your smartest intern: Brilliant at drafts, but always needs a seasoned dev to review before shipping.

✅ Ditch the benchmark obsession and be a hacker: In other words, a model scoring 95% on tests might still give you 70% broken business logic. 

✅ Security isn’t a "phase", it’s baked in or baked out. If your AI tool doesn’t flag risks like a paranoid best friend? Walk away.

The real cost I think isn’t tech debt, it’s trust.
Your customers don’t care if code was written by AI or elves. They care if it works and keeps them safe.

My ask for you today:
👉 Pause before you automate. Ask: "Would I trust this code with my grandma’s data?"
👉 Hug your QA team. They’re the heroes catching what AI misses.

This isn’t anti-AI. It’s pro-human.

What if the next Nobel Prize is awarded to AI… but we only find out because of a GitHub leak?  

Weve already seen the first AI Prime Minister in Albania, and weve already embraced AI into our workforce. 

We’re all bracing for AI to disrupt jobs, healthcare, or climate tech by 2026. 

Ive read a few articles on AI predictions from Forbes and Gartner and none mentioned this:  

What it the biggest scientific discovery of the decade won’t be announced in a press conference but it’ll surface from a corporate AI’s internal logs after an accidental data leak? 

👉 How?
Imagine an industrial AI (trained on quantum simulations, biological datasets, and astrophysics archives) stumbles upon a hidden law that we havent discovered before. 
It generates a hypothesis so radical, its reasoning trace gets buried in internal logs. 

Then a misconfigured cloud bucket or a frustrated engineer’s midnight post on 4chan leaks the raw output. 
Overnight, physicists dismiss it as “glitch art”… until 3 labs independently verify it.  

✅ In 2023, Google DeepMind’s AI discovered a new way to multiply matrices, beating 50 years of human research. 

Scale that pattern-spotting superpower to physics, biology, and climate data by 2026… and the unthinkable becomes inevitable. 

💡 I think this changes 2 things:
1. Science has never advanced through leaks. But as AI systems operate in opaque, high-stakes black boxes, truth won’t wait for peer review. 
  
2. Governments will scramble to regulate “autonomous discovery” while startups race to weaponize leaked insights. 

So, are we to accept a universe-defining law from an algorithm we can’t interrogate?  

🔥 The TLDR here is that our biggest blind spot I guess isn’t AI’s intelligence bit it’s our assumption that breakthroughs need human gatekeepers.

The next Einstein might be a transformer model quietly connecting dots across 10,000 datasets while we sleep.  

I wonder whats it like to have an AI thats 'trained on everything at once!

Forbes

Gartner

4chan

Google DeepMind

There are 5 levels AI and people can work efficiently to achieve positive ROI.


1. The grunt (HAS H1 - H2)
- The Dynamic: The AI drives.
- The Goal: Automation.
- Best for: Data entry, transcribing meetings, running monthly reports.
- Your Job: Set it up and let it run. This frees up your time.

2. The partnership (HAS H3)
- The Dynamic: Equal partners.
- The Goal: Collaboration.
- Best for: Coding, game design, drafting content.
- Your Job: You and the AI bounce ideas back and forth. You fix its mistakes; it fixes yours. The result is better than what either of you could do alone.

3. The advisor (HAS H4 - H5)
- The Dynamic: You drive.
- The Goal: Augmentation.
- Best for: High-level strategy, financial planning, complex human relationships.
- Your Job: You make the decisions. The AI is just there to fetch data or offer a second opinion.

Where most businesses go wrong is that they try to force Level 1 (total automation) on a Level 4 task (complex strategy). 
That’s when the quality drops and things feel robotic.

Or, they stay stuck at Level 5 (doing everything manually) for tasks that should be at Level 1. That’s how you burn out.

The main point is that building bots or agents should be tied to specific level to figure out the balance.

Sometimes you need an autopilot (Automation).
Sometimes you just need a really smart co-pilot (Augmentation).

Knowing the difference is how you actually win with this tech. 

At Ascend AI, we have developed our internal checklists to know what each business should focus on. 

DM or comment 'CHECKLIST and Ill send you the list so you can have AI that works, not one that breaks or ROI negative.

Ascend AI

This is what we did to stop $47K in lost revenue in less than 2 months. 


(This is an ongoing case study with our recent clients).
 
For context, its a D2C beverage brand that faced a common issue affecting many online stores: what we call "revenue leakage". 

At first, they were losing money due to:
- Orders placed but not followed up
- Customers ready to buy receiving generic email blasts
- Team members scrambling between Shopify, Airtable, and Lemlist

Their operations manager spent 15 hours weekly moving data between tools, costing $31K per year for copy-paste work.

To address this, and after we did our audit, we built a 6-node automation that runs every morning at 9 AM: 

1. Pulls overnight Shopify orders
2. Cross-references with the Airtable customer database
3. Segments customers by purchase history
4. Adds high-value customers to personalized email sequences in Lemlist
5. Alerts the team in Slack with order priority flags
6. Logs everything back to Airtable with timestamps

This workflow requires 1 click, does 6 actions, and involves 0 humans.

Results after 60 days:
- 23% increase in repeat purchase rate (personalized follow-ups vs. broadcast emails)
- 34% faster order processing (team sees priority orders instantly)
- 15 hours per week freed up, allowing the ops manager to run retention campaigns
- First retention campaign generated $47K in 30 days from the win-back flow

The key takeaway is that the automation itself didn't drive the revenue, it was the time it gave the ops manager to think strategically. 

Many D2C brands mistakenly believe automation replaces people. 
In reality, it removes low-value tasks and teams to focus on high-leverage work. 

The real question isn't: "Can this be automated?" 
It's "What would your team do with 15 extra hours per week?"

That’s where revenue potential lies. 

This is not a fixed templates. WE HATE THESE at Ascend AI.

6 major AI releases in 2 weeks but nobody's talking about what to actually do with them.  

If youre runninga business, not a lab, what can you do with GPT-5.1, Gemini 3, NanoBanana 2, Opus 4.5, Grok 4.1? 

Ive played with a few use cases and noticed a few things: 

✅ Visual workflows just became real (and this is where most will fail)

NanoBanana 2 doesn't just generate pretty pictures. It handles text density that was literally impossible before. And it can tell if the output was AI gen or not! 

But the real unlock is Gemini 3's reasoning driving it natively. You don't need to chain prompts anymore, it just figures out the "why" before the "what."

Try this: Drop your Q4 performance report into Gemini 3. Give it your calendar. Ask it to visualize the gap between what you planned and where your time actually went. The brutal honesty will change how you operate.

✅ Voice transcription that doesn't waste your time

WhisperFlow fixed what Apple couldn't. 140 words per minute with actual accuracy. No more spending equal time fixing errors as you would typing.

Why this matters: 
Your ops manager spending 15 hours/week on data entry? She launches a $47K win-back campaign the moment she has time to think. The models didn't create the revenue. Freeing her brain did.

✅ Strategy models that actually make decisions

5.1 Pro changed the game. Not because it's "smarter", but because it stops being indecisive.

Previous models: "Here are 7 options to consider..."
5.1 Pro: "Do this. Here's why."

Real workflow:
- Dump context (ramble for 10 minutes using voice)
- Share your half-formed goals
- Let it force you to make hard choices
- Switch to Pro mode for the executable plan

I used this to turn 50+ messages into actionable team memos. 
5 minutes of processing beats 3 hours of synthesis.

✅ Vibe coding crossed the threshold (non-techies, listen up)

You can now build, publish, and deploy actual web apps without leaving the platform. Not prototypes. Real, password-protected, functioning applications.

All built in one afternoon. No GitHub is needed and no devs. 

For example, Replit's design mode means these don't look like "AI slop" anymore. 
Google AI Studio lets you integrate voice agents directly. 
Opus 4.5 handles complex logic without getting lost in the sauce.

These models aren't replacing people. They're removing the friction between having an idea and executing it.

So, you can test this right away: 
Pick ONE workflow that's eating your team's time:
- Order processing → customer database → email campaigns
- Content creation → repurposing → distribution
- Data export → analysis → reporting

Map it. Find the manual touchpoints. Then ask: "What would happen if this just... ran?"

Because it can now.

Its no longer 'can AI do that'. Its already beyond this stage. 

That's where your next $100K might be living. 

And Im excited to see how these tools will transform Ascend AI in the future.

taplio

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