How do you work with founders?

The main ways I work with founders are MVP development, go-to-market strategy, and AI implementation consulting. Most engagements start with a free call where we figure out what's blocking growth - whether that's shipping a product, finding customers, or integrating AI into an existing workflow. I've built three AI startups myself (Wysera, TradersHub Ninja, and more), so I bring a builder's perspective, not just a consultant's.

How long does a typical MVP engagement take?

Most MVPs go from concept to a working prototype in about two weeks. That includes LLM integration, core UI, and deployment. From there, we iterate based on real user feedback. I wrote a detailed playbook on my blog if you want to see the week-by-week breakdown before we talk.

What's your background in AI and healthcare?

I'm an AI/DevOps Architect at QliqSOFT, where I work on healthcare technology daily - HIPAA-compliant AI systems, EHR integrations, and clinical data pipelines. I've published research on EHR implementations and hold AWS and MongoDB certifications. Before that I spent a decade building enterprise DevOps pipelines. I also wrote 'It Started with a PROMPT', a practical guide for founders building with AI.

What is Wysera (FoundersHub AI)?

Wysera is the startup platform I built to solve my own problems as a founder. It handles the repetitive stuff - lead capture, outreach, pitch decks, project management - so you can focus on building. Think of it as replacing 10+ founder tools with one AI-powered workspace. We also run a community with regular meetups and workshops in Dallas.

What's the best way to get started?

Book a free call through my calendar page - no pitch deck or prep needed. Just tell me what you're building and where you're stuck. If it's a good fit, I'll lay out a plan. If not, I'll point you in the right direction. You can also check out my blog for tactical guides on AI MVPs, GTM strategy, and LLM implementation.

GTM frameworks

The GTM playbooks behind 4 AI products in 16 months.

Not theory: the actual frameworks I used to position, price, launch, and distribute every product I shipped. Battle-tested across enterprise SaaS, PLG, community-led, and regulated healthcare markets.

PositioningPricingDistributionFirst 100 customersLaunch

Book a GTM strategy call See case studies

Five frameworksFrom 4 launches

AI product positioning canvas6 steps

Define how your AI product is different before you spend a dollar on marketing.

AI pricing decision tree6 steps

Usage-based? Per-seat? Free tier? Stop guessing.

Channel strategy matrix6 steps

PLG vs. direct sales vs. community vs. marketplace — pick the one that matches your stage.

First 100 customers playbook6 steps

The playbook for going from 0 to 100 paying users without a sales team.

AI product launch checklist6 steps

The 20-point checklist I run before every product launch.

Same founder, four channels
Community, founder groups, SEO-first and event-led.

The frameworks

Five frameworks, one per decision.

Positioning, pricing, channel, the first 100 customers and launch. Each one opens below with its steps, the key insight and how I applied it.

01Framework 016 steps

AI product positioning canvas

Define how your AI product is different before you spend a dollar on marketing.

02Framework 026 steps

AI pricing decision tree

Usage-based? Per-seat? Free tier? Stop guessing.

03Framework 036 steps

Channel strategy matrix

PLG vs. direct sales vs. community vs. marketplace — pick the one that matches your stage.

04Framework 046 steps

First 100 customers playbook

The playbook for going from 0 to 100 paying users without a sales team.

05Framework 056 steps

AI product launch checklist

The 20-point checklist I run before every product launch.

The frameworks, opened

Steps, insight, proof.

The framework on the left, how to run it on the right.

Framework 01AI product positioning canvas

Use it to: Define how your AI product is different before you spend a dollar on marketing.
Steps: 6, in order

AllBack to the index

The framework

Define how your AI product is different before you spend a dollar on marketing.

Most AI products sound the same: "AI-powered [thing] that [generic benefit]." This canvas forces you to articulate a position no competitor can copy.

The steps

1ICP Who is the buyer? Not "everyone" — one persona, one pain, one budget.

2Problem What are they doing today without your product? What does that cost them?

3Alternative What do they use instead? (Spreadsheet, intern, competitor, nothing.)

4Wedge What is the one thing your AI does that the alternative literally cannot?

5Proof What evidence proves the wedge works? (Demo, metric, case study, testimonial.)

6Position "The only [category] that [wedge] for [ICP]." If this sentence has the word "AI" in it, you are not done.

Key insightYour position is not your product. It is the smallest claim you can make that is both true and impossible for competitors to also claim. If three others can say the same thing, it is not a position.

How I applied this

PostWyse: "The only content dashboard that tracks your brand visibility across ChatGPT, Claude, and Perplexity." Nobody else measures AI visibility — that is the wedge.

Framework 02AI pricing decision tree

Use it to: Usage-based? Per-seat? Free tier? Stop guessing.
Steps: 6, in order

AllBack to the index

The framework

Usage-based? Per-seat? Free tier? Stop guessing.

AI products have unique pricing challenges — inference costs scale differently than SaaS compute. This decision tree matches your GTM motion to the right pricing model.

The steps

1Is usage predictable? Yes → per-seat or flat. No → usage-based or credits.

2Is your buyer technical? Yes → usage-based (they understand metered pricing). No → flat or tiered.

3Do you need PLG? Yes → free tier with a natural upgrade trigger. No → sales-led with custom pricing.

4What is your inference cost? High → usage-based (protect margins). Low → bundle it in flat pricing.

5Competitive anchor? What do alternatives charge? Price against the alternative, not against your cost.

6Expansion trigger What usage signal means "time to upgrade"? Build pricing around that moment.

Key insightThe best AI pricing model is the one where your customer wins when you win. If they pay more only when they get more value, retention solves itself.

How I applied this

Prompt Pro: free tier for casual users (200 prompts). Power users who hit the refiner 10+ times/week naturally upgrade for unlimited access + team sharing.

Framework 03Channel strategy matrix

Use it to: PLG vs. direct sales vs. community vs. marketplace — pick the one that matches your stage.
Steps: 6, in order

AllBack to the index

The framework

PLG vs. direct sales vs. community vs. marketplace — pick the one that matches your stage.

Channel choice is the highest-leverage GTM decision you will make. The wrong channel wastes 6 months. This matrix maps channel to stage, ACV, and buyer type.

The steps

1ACV < $1K PLG or marketplace. Sales does not make unit economics work.

2ACV $1K-10K PLG + inside sales. Free tier qualifies leads, sales closes.

3ACV $10K-50K Content + events + outbound. Decision-makers need education first.

4ACV > $50K Direct enterprise sales. Relationships, procurement, compliance.

5Technical buyer? Developer relations, open-source, API-first. Let them self-serve.

6Non-technical buyer? Content marketing, events, partnerships. Show outcomes, not architecture.

Key insightYou do not need omnichannel. You need one channel that works, proven with data, before you add a second. Every channel you add before proving the first dilutes execution.

How I applied this

TradersHub: community-led growth (Discord). Wysera: founder communities. PostWyse: SEO-first. QliqSOFT: event-led (AGILE, HIMSS). Same founder, four different channels.

Framework 04First 100 customers playbook

Use it to: The playbook for going from 0 to 100 paying users without a sales team.
Steps: 6, in order

AllBack to the index

The framework

The playbook for going from 0 to 100 paying users without a sales team.

Your first 100 customers teach you more about GTM than any strategy doc. This playbook is the sequence that worked across 4 products.

The steps

10-10: Personal network DM 50 people who fit your ICP. Not cold — people who know you exist. Ask for 15 minutes, not a purchase.

210-25: Community Show up where your ICP hangs out. Give value for 2 weeks before mentioning your product. Build reputation first.

325-50: Content proof Publish the results your early users are getting. Real numbers, real names (with permission). Social proof compounds.

450-75: Referral loop Ask your best users: "Who else has this problem?" Warm intros from happy users close 5x faster than cold outreach.

575-100: Repeat channel By now one channel is working. Double down on it. Do not diversify yet — depth beats breadth at this stage.

6100+: Systematize Document what worked. Build the repeatable playbook. Now you can hire someone to run it.

Key insightThe first 100 customers are not a growth problem. They are a learning problem. Every conversation teaches you something about positioning, pricing, or product that no amount of strategy planning can replace.

How I applied this

Wysera: 10 founders from Startups.com → 25 from LinkedIn founder groups → 50 via published case studies → 100 through referral loop. Total paid ads: $0.

Framework 05AI product launch checklist

Use it to: The 20-point checklist I run before every product launch.
Steps: 6, in order

AllBack to the index

The framework

The 20-point checklist I run before every product launch.

Not a generic checklist — these are the specific items that made or broke my last 4 launches. Organized by phase: pre-launch, launch day, post-launch.

The steps

1Pre-launch (T-14) Landing page live. Waitlist collecting emails. 3 demo videos recorded. 5 beta users giving feedback. Positioning statement locked.

2Pre-launch (T-7) Launch post drafted (LinkedIn, X, blog). 10 people committed to share on launch day. Product Hunt listing prepped (if relevant). Email sequence loaded.

3Launch day Ship at 9am ET. Post everywhere simultaneously. Reply to every comment within 1 hour. Monitor sign-up flow for breaks. Send personal DMs to 20 ICP targets.

4Post-launch (T+3) Publish first "what we learned" post. Follow up with every sign-up who did not activate. Fix the #1 user-reported friction point.

5Post-launch (T+7) Collect 3 testimonials. Publish results/metrics post. Start building the repeat channel (SEO, community, whatever worked).

6Post-launch (T+30) Retention check: how many of launch-week users are still active? That number tells you if you have product-market fit or just launch hype.

Key insightLaunch day is not the goal — it is the starting line. The best launches are the ones where day-30 retention is higher than day-1 signups would predict. Optimize for that, not for launch-day vanity metrics.

How I applied this

PostWyse launch: free AI visibility audit as the hook → 59 posts in month 1 → PowerBot chatbot capturing leads 24/7 while we iterated on the full dashboard.