The No-Code Founder Podcast

Episode Description

Fraud and abuse are quietly eating into your margins and most founders don't realize how bad it is until it costs them tens of $.

In this episode, you'll learn:

• Where D2C brands actually lose money
• How to control promo and loyalty abuse without alienating good customers
• Returns prevention, detection, and recovery tactics (before and after the sale)
• Payment fraud baselines (AVS, CVV, 3DS, CE3.0, and risk tiers)
• A 30/60/90-day action plan
• KPIs and dashboards to prove it's working

By the end, you'll know exactly where to start, what to measure, and how to protect your margin while keeping great customers happy.

Key Topics

• Fraud costs $13.70/$100 returns, $3.75/$1 fraud.
• Types: promo abuse (leaks, stacking),
• loyalty fraud (ATO, points farming),
• returns abuse (wardrobing, empty-box),
• payment fraud (card testing, friendly fraud).
• Risk tiers: VIP (frictionless), medium (light step-up), high (3DS).
• Chargeback defense: reason codes, CE3.0, dispute win rates.
• 30/60/90-day implementation.

Sources Mentioned

• National Retail Federation + Appriss Retail, "Consumer Returns in the Retail Industry" (2023): Return rate ~14.5%; $13.70 fraud loss per $100 of returns
• LexisNexis Risk Solutions. Each $1 of fraud costs retail/ecom ~$3.75 all-in
• Visa/Mastercard chargeback monitoring programs.
• PSD2 and 3-D Secure 2 guidance.

Key Definitions (For Listener Reference + Adjacent Terms to Know)

• ATO (Account Takeover): Fraudster gains control of a customer account
• AVS (Address Verification Service): Checks if billing address matches card issuer records
• BIN/IIN: First 6-8 digits of a card number that identify the issuer
• BNPL (Buy Now, Pay Later): Financing services like Affirm, Klarna, Afterpay
• CE3.0 (Compelling Evidence 3.0): Visa program to dispute friendly fraud with proof of legitimate transactions
• CVV (Card Verification Value): 3-4 digit security code on card
• OTP (One-Time Password): Temporary code sent via email/SMS for verification
• PSD2 (Payment Services Directive 2): EU regulation requiring Strong Customer Authentication

Connect with Leo:

• X: ⁠Leo Sadeq⁠
• LinkedIn: ⁠Leo Sadeq⁠
• Want to 2X-5X your ROI in 90 days? Let us help you >>> ⁠Ascend AI⁠
• DM me for any resources or checklists mentioned in the episode and Ill forward them your way.

Until next time :)

Episode Promise:

Cookies are fading, privacy rules are tightening, and CAC keeps climbing.

This episode gives you a concrete, first‑party/zero‑party data playbook to collect better signals, unify them without a big data team, activate profitable segments across email/SMS/paid, and measure real lift while staying compliant and protecting deliverability.

Topics Discussed:

Definitions that matter

The 4-stage growth framework: Collect, Unify, Activate, Measure

• Collect: High-quality first/zero-party data without tanking conversion
• Unify: Minimum viable data layer
• Activate: Lifecycle segmentation and paid media powered by first-party data
• Measure: Post-cookie attribution that leadership trusts

Quick game plan within the nwxt 30 days.

Risk controls and compliance

Red flags and quick fixes and other information for your D2C growth with AI.

____________________

Connect with Leo:

• X: ⁠Leo Sadeq⁠
• LinkedIn: ⁠Leo Sadeq⁠
• 2X-5X your ROI in 90 days with our AI automation agency. ⁠Ascend AI⁠
• DM me for any resources or checklists mentioned in the episode and Ill forward them your way.

Until next time :)

Show description:

D2C founders: before you post that $200k “AI hire,” listen to this.

We break down why panic hiring fails and what to do instead so you ship real wins fast without bloating payroll.

Key talking points and sections

• The $200k panic hire: what the AI Talent Trap is and why it’s costly
• Why the “genius hire” fails: data (no kitchen), context (ivory tower), strategy (no use case)
• Role decoder: who you actually need (AI translator vs data scientist/engineer/analytics/ML)
• Data readiness gate: simple checks before any hire
• The Buy–Upskill–Partner playbook (with D2C tool examples)
• Partnering the right way: SOW, governance, and CFO lens
• Agency-led 8‑week pilot: how we’d run it for a small/mid D2C brand
• Stage-based roadmap: pre-hire, first hire (when + what to prioritize), scale
• Governance and metrics that matter
• Red flags to avoid.

Connect with Leo:

• X: ⁠Leo Sadeq⁠
• LinkedIn: ⁠Leo Sadeq⁠
• 2X-5X your ROI in 90 days with our AI automation agency. ⁠Ascend AI⁠

Episode Talking Points

Picking the wrong AI path can cost you quarters and millions. Get a dead-simple framework to decide: build in-house, buy a platform, partner with specialists, or acquire a team, plus real costs, risks, and playbooks.

You'll get:

• 7-question scorecard to choose your path in minutes
• Year-1 and 3-year cost realities (TCO, payback, "caretaking" budget)
• How to avoid lock-in: abstraction, export rights, multi-model failover
• Clear playbooks for Build, Buy, Partner (BOT), and Acquire
• Ecom case clinics and 90-day rollout plan with POC gates

Concepts: Build for moats, Buy for speed, Partner for acceleration, Acquire when time is the bottleneck. Price the downside, keep your off-ramp real, scale only what's boringly reliable.

Chapters

• The decision that makes or breaks your next 12 months
• Why this matters now: AI spend surging; most struggle to monetize. Investors diligence AI readiness. Commoditization accelerating.
• The four paths: Build (AI is your moat, 6–12 months), Buy (supports product, weeks to value), Partner (speed + customization), Acquire (instant team + IP, highest risk)
• 7-question scorecard to know which path to take for your brand.
• Money talk: Build (multi-million 3-year TCO, 10–20% ongoing ops), Buy (2–8 weeks, watch usage creep), Partner (6–8 week pilots, BOT by month 3–6), Acquire (cash-heavy, integration critical). CFO lens: payback, run-rate, +30% contingency.
• Flexibility & risk: Open-weights vs closed APIs.
• Abstraction layers, contract must-haves (data ownership, export rights, SLAs), multi-model failover, 30/60/90 POC gates

Playbooks:

• Build (scope one workflow, staging, retries, evals, observability),
• Buy (2-week POV, negotiate exit, phased rollout),
• Partner (SOW with knowledge transfer),
• Acquire (diligence, retention, integration plan)

Case studies:

• D2C skincare (Buy + Partner + Build guardrails = 30–40% deflection, −15–25% AHT).
• Marketplace (Build ranking, Buy tooling, Partner MLOps)

90-day plan:

• 0–30 (pick use case, scorecard, define gates),
• 31–60 (pilot with guardrails),
• 61–90 (scale to 20–30% or switch)
• Red flags to pay attention to

Who this is for:

• Non-technical founders,
• D2C/ecommerce teams,
• anyone weighing speed vs control vs cost

Connect with Leo:

• X: ⁠Leo Sadeq⁠
• LinkedIn: ⁠Leo Sadeq⁠
• 2X-5X your ROI in 90 days with AI. ⁠Ascend AI⁠

The Hidden Costs of Bad AI: When Automation Becomes Your Biggest Expense

Bad AI is expensive, because you pay for the mess it leaves behind. This no‑fluff tactical episode is for non‑technical D2C founders and ops leads who want real results from AI, not hype.

With a focus on sales outreach, Leo (Founder, Ascend AI) breaks down the hidden costs draining your margins and gives you a playbook you can run this week.

You’ll learn:

1. The 100:1 Rule: when one AI mistake wipes out a hundred wins, aka where a human gate is non‑negotiable.
2. The 9 cost buckets that blow up P&L: rework, exception AI babysitting, trust/churn, legal exposure, data leakage, drift/decay, token creep, shadow AI, and vendor lock‑in.
3. What happens when automation misfires: Air Canada’s chatbot ruling and Deloitte’s hallucinated report and why “the bot did it” won’t save you.
4. The outreach playbook that protects margin: start in low‑regret zones, instrument everything, add guardrails, A/B test weekly, and many more for your revenue health.
5. How to price the downside to ensure your ROI projections are obtained with AI.
6. Outreach traps to avoid: deliverability dips from volume spikes, discount leakage, and creepy personalization, and how to fix each fast.
7. The 7 red flags your AI is burning cash right now (flat replies, rising unsubscribes, margin drop and more).
8. And other valuable insights to scale the right way with AI

Connect with me:

1. X: ⁠Leo Sadeq⁠

2. LinkedIn: ⁠Leo Sadeq⁠

3. Let us 2X-5X your ROI in 90 days. ⁠Ascend AI⁠

In this episode of The No-Code Founder Podcast, Leo Sadeq - Founder of the ROI-focused AI automation agency Ascend AI - reveals the exact methodology he uses to identify massive automation opportunities for businesses across every industry.

Leo shares his proven 3-step AI Leverage Audit framework that has consistently helped him uncover $10,000+ automation opportunities for his clients.

This isn't just theory - it's a proven system that Leo has refined to serve as the first AI enablement steps before diving deeper.

In this episode, you'll discover:

1. The exact 3 steps of the AI Leverage Audit process
2. How to identify the highest-impact automation opportunities in your business
3. Real-world examples of automation wins from Leo's client work
4. The common blind spots most business owners have when it comes to AI opportunities
5. A step-by-step walkthrough you can implement in your own business today

Whether you're a complete beginner to AI automation or already exploring AI tools, this episode will give you a clear roadmap to start finding and implementing profitable automation opportunities immediately.

Perfect for D2C entrepreneurs, business owners, and anyone with no technical backgrounds looking to leverage AI to scale their operations and increase profitability without the technical complexity.

Connect with me on

⁠LinkedIn⁠:

⁠X:

In a Nutshell Brief:

Make your AI tools actually work together without sacrificing speed, reliability, or budget.

This episode gives non-technical founders and ops leaders a plain-English playbook for fixing broken AI integrations.

If your “brilliant” bot falls apart the moment it touches Shopify, Klaviyo, your CRM, or warehouse system, you’re not alone. The problem isn’t your AI. It’s the plumbing.

In this episode, we break down the four integration hell scenarios that cause 80% of failures:

1. Voice latency: Fix with sub-500ms budgets, caching, and graceful delays.

2. Disappearing messages: Solve with retries, dead-letter queues, and daily health checks.

3. Memory loss: Preserve context with lightweight session state (Redis/Firestore) and clear agent roles.

4. Data format chaos: Enforce a canonical schema and validate required fields early.

Plus two silent killers:

- Idempotency: Prevent duplicate orders/charges with unique operation keys.

- Time zones: Store everything in UTC, convert only at the UI.

You’ll also get a 5-step debugging flow plus non-technical fixes like clear ownership (RACI), staging with synthetic data, and a simple change process to stop “cowboy edits.”

The goal?

A minimum viable architecture that scales while avoiding the top 4 archetectural mistakes too.

Then, youll get a 6-week roadmap to audit your stack so your AI stops being a demo and starts moving revenue.

__________________________________

Created and approved by Leo, founder of Ascend AI.

This is a practical guide that we use ourselves at Ascend AI with our D2C clients. We hope youll find it useful.

Connect with Leo:

1. LinkedIn or X
2. Want to scale with robust AI solutions? Check Ascend AI.

Happy growth with AI :)