The cybersecurity AI sales course for the top 10%.

• Lesson 1.1, The practitioner's identity: behavior as commitmentFree preview18 min
• Lesson 1.2, The deliberate practice structure: daily disciplines that compoundFree preview17 min
• Lesson 1.3, Recovery and physiological state management16 min
• Lesson 1.4, Plateau breakers: the three causes of stalled performance17 min
• Lesson 1.5, The cybersecurity AI seller's edge16 min

• Lesson 2.1, Foundation models: what they are, what they cost, how they're trained22 min
• Lesson 2.2, The frontier labs22 min
• Lesson 2.3, RAG vs fine-tuning vs agents: when each pattern applies22 min
• Lesson 2.4, Evaluation: how AI products are measured20 min
• Lesson 2.5, The AI product stack: from foundation model to user interface20 min

• Lesson 3.1, The DecipherU eight pillars: a primary-source map28 min
• Lesson 3.2, Stage-gate deal progression for cybersecurity AI deals (Hanan 1970, adapted)26 min
• Lesson 3.3, Pillar 2: the eight-condition buyer-readiness frame26 min
• Lesson 3.4, Pillar 3: persuasion by position (Aristotle's pisteis)26 min
• Lesson 3.5, Pillar 1: the discovery inquiry (Hanan + Rackham + Plato)26 min
• Lesson 3.6, The DecipherU value cascade: features to functions to economic and strategic impact24 min
• Lesson 3.7, Pillar 8: the practitioner's path (Bandura, Ericsson, Aristotle, Epictetus)24 min
• Lesson 3.8, The DecipherU decision tree: which pillar, when28 min

• Lesson 4.1, The top 0.1% cybersecurity AI prospecting cadence: deliberate practice on the calendar24 min
• Lesson 4.2, ICP definition for AI products: signals that a company is an AI buyer24 min
• Lesson 4.3, Account selection: territory math, white space analysis22 min
• Lesson 4.4, Account research at depth: 10-K analysis, earnings calls, AI strategy signals, competitive positioning, recent AI hiring28 min
• Lesson 4.5, Multi-channel prospecting: email, LinkedIn, phone, video, gifts24 min
• Lesson 4.6, The insight-led email: opening with Aristotelian docere instead of a feature pitch22 min
• Lesson 4.7, Sequence design for AI buyers: 14-touch sequences with insight, evidence, and pattern interrupts24 min
• Lesson 4.8, LinkedIn for AI sellers: founder-led brand building, content cadence, engagement strategy24 min
• Lesson 4.9, Cold call playbook for AI deals: opening, pattern interrupt, qualification, next step24 min
• Lesson 4.10, Inbound qualification: separating curiosity calls from real cybersecurity AI buyers22 min

• The discovery mindset: diagnostic not pitch22 min
• SPIN questioning: Situation, Problem, Implication, Need-payoff24 min
• The diagnostic pain inquiry: Hippocratic differential and Aristotle's four causes22 min
• Discovery for AI deals: 30 must-ask questions26 min
• Multi-stakeholder discovery: per-buyer questions22 min
• Quantifying business impact22 min
• Identifying decision process20 min
• Discovering competition (including 'do nothing')22 min
• The discovery debrief18 min
• When to walk away: qualification thresholds20 min

• Lesson 6.1 : The eight-condition qualification spine: history and discipline22 min
• Lesson 6.2 : Metrics for AI deals: how to quantify AI value24 min
• Lesson 6.3 : Economic Buyer for AI deals22 min
• Lesson 6.4 : Decision Criteria: explicit and implicit, including AI-specific criteria22 min
• Lesson 6.5 : Decision Process: the actual process not the stated process22 min
• Lesson 6.6 : Paper Process: AI-specific contract considerations24 min
• Lesson 6.7 : Identify Pain: the specific business pain (not surface symptom)22 min
• Lesson 6.8 : Champion: identifying, building, and protecting the champion24 min
• Lesson 6.9 : Competition: including 'do nothing,' 'build it themselves,' 'wait for the next model release'22 min
• Lesson 6.10 : Eight-condition scoring: the 100-point rubric for forecast accuracy22 min

• Lesson 7.1 : The buying committee for AI deals: typical roles and concerns22 min
• Lesson 7.2 : Gap mapping: who you should be talking to and who you are22 min
• Lesson 7.3 : The executive map: hierarchy, influence, decision authority, blockers, allies22 min
• Lesson 7.4 : Engagement plans per stakeholder24 min
• Lesson 7.5 : Asking your champion to make introductions: the templated request20 min
• Lesson 7.6 : Cold-emailing executives directly: when, how, and why champion approval matters22 min
• Lesson 7.7 : Tracking multi-threading in CRM: the mandatory fields20 min
• Lesson 7.8 : Coordinating multi-thread conversations: managing message consistency22 min

• What Executives Care About: Time, Capital Allocation, Competitive Position, Regulatory Risk30 min
• Executive Teaching: Insight Delivery from Aristotle's Pisteis30 min
• AI-Specific Executive Insights: Investment Patterns, Competitive Moves, Talent, Regulation30 min
• The 30-Minute Executive Conversation Structure30 min
• Asking the Right Executive Questions30 min
• Executive Followup: The Meeting Recap That Becomes a Strategic Document28 min
• The Board-Level AI Conversation30 min
• Calendar Management for Executive Conversations26 min

• The Hallucination Objection15 min
• The Bias Objection15 min
• The Data Privacy Objection15 min
• The Vendor Lock-In Objection15 min
• The Build-vs-Buy Objection15 min
• The Frontier Model Dependency Objection15 min
• The ROI Uncertainty Objection15 min
• The Governance Compliance Objection15 min
• The Wait-for-the-Next-Model Objection15 min
• The Procurement Objection15 min
• The Training Data Provenance Objection15 min
• The Prompt Injection Objection15 min

• PoC vs PoV: The Critical Distinction15 min
• PoV Scoping15 min
• PoV Success Criteria15 min

• Ciceronian Stasis Agreement for Closing26 min
• AI-Specific Contract Terms32 min
• Pricing Strategies: Usage-Based, Seat-Based, Value-Based, and Hybrid30 min
• The Negotiation Walk-Away: Knowing Your Floor and Walking When Needed26 min
• Procurement: Working with Customer Teams That Lack AI Vendor Templates26 min
• Legal: Negotiating AI-Specific Contract Language with Customer Counsel28 min
• Security Review: Working Through Customer Security Team Reviews of AI Vendors30 min
• The Close: The Structured Close Conversation26 min
• The Post-Close Handoff: Setting Up Customer Success for Expansion24 min

• The Land-and-Expand Playbook for AI Deals28 min
• Identifying Expansion Opportunities: Use Case, Team, and Geography30 min
• Quarterly Business Reviews That Drive Expansion30 min
• Renewal as a Sales Motion, Not a Customer Success Motion28 min
• Multi-Year Contracts: When to Push, When Not To26 min
• Reference Customer Development: Turning Customers into Champions26 min

• 13.1 Pipeline as a system (Bandura/Ericsson self-efficacy and deliberate-practice)30 min
• 13.2 Stage discipline: what defines progression25 min
• 13.3 The weekly pipeline review25 min
• 13.4 The monthly forecast25 min
• 13.5 Priority ranking opportunities25 min
• 13.6 The deal review25 min
• 13.7 CRM hygiene25 min

• 14.1 The account plan template (12 sections)35 min
• 14.2 Annual account planning cadence25 min
• 14.3 Territory strategy: math, mix, segmentation30 min
• 14.4 The 'compound territory' strategy25 min
• 14.5 Account selection: the math of account targeting25 min
• 14.6 Account plan reviews25 min

• 15.1 CRM for AI deals30 min
• 15.2 Prospecting tools30 min
• 15.3 Research tools25 min
• 15.4 AI-assisted email drafting (without sounding like AI)25 min
• 15.5 Conversation intelligence (Gong, Chorus)25 min
• 15.6 Pipeline visualization (Clari, BoostUp, Salesforce native)25 min

B2B sellers, sales engineers, and solutions architects moving into cybersecurity AI sales. Best fit is 2 to 10 years of complex B2B sales experience selling to Fortune 5000 buyers. Cybersecurity sellers expanding into AI security tooling fit the program directly.

Self-paced. Roughly 50 hours of focused study across 16 modules plus a 38 to 57 hour capstone deliverable. Most practitioners finish modules in 8 to 12 weeks at 4 to 6 hours per week, then evaluate the capstone against the published rubric.

Full access to all 16 modules, every template (account plan, qualification scorecard, multi-threading plan, executive deck, PoV charter, objection playbook), and the capstone workspace with self-evaluation rubric and verifiable credential issuance.

Approved capstones earn the AI Sales and Solutions Engineering Mastery verifiable credential, signed with Ed25519 and embeddable on LinkedIn. The credential is renewable through one continuing-practice exercise per year. Issued by DecipherU. It is a course-completion credential, not an accredited degree or a vendor-issued certification.

Working LLM literacy as a user is enough. The course teaches you to talk to AI engineers credibly: RAG vs fine-tuning, foundation model economics, agent architectures, and evaluation frameworks. You do not need to write Python to pass.

The course teaches eight proven sales approaches grounded in peer-reviewed research instead of pop business books. Persuasion uses Aristotle and Cicero on rhetoric. Negotiation uses Follett (1924) and Walton & McKersie (1965). Empathic discovery uses Rogers (1957). Influence uses Cialdini's primary peer-reviewed work (1975) and Asch (1956). Each module names the source so you know which technique applies when.

Yes. Module 5 covers selling AI security and Module 11 covers procurement and legal for AI deals. Security review (with AI-specific gates) is treated as a deal stage, not an afterthought. AI-specific contractual posture, model risk indemnification, and AI Act compliance language are covered in the negotiation modules.

Yes. Seven-day full refund from purchase, while you have completed less than 10% of the course. Email support@decipheru.com with your order number; refunds process within 3 business days. After 7 days or above 10% completion, refunds are case-by-case. A refund triggers a 90-day lockout on re-purchasing this course or subscribing to a tier that bundles it.

First cohort enrollment opens Q2 2026. Public reviews from completed practitioners will appear here once the first cohort finishes the capstone. Capstones in the top 10% may be anonymized into case studies with explicit permission from the practitioner.

Editorial markdown lessons paired with founder-recorded video, knowledge checks (5 to 10 questions per module, 80% pass), exercises with self-grading rubrics, role-play simulations with AI counterparties, and a multi-section capstone workspace with file uploads.