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DecipherU · Course

AI Sales and Solutions Engineering Mastery

The cybersecurity AI sales course for the top 10%.

For the enterprise AE, SE, or solutions architect watching mid-tier sales roles compress into AI-supervision work. This 16-module program is for the top-decile cybersecurity and Applied AI sellers who still close $1M-plus deals: qualification, discovery, multi-stakeholder navigation, AI-specific objection handling. Built on published sales and negotiation research (Aristotle and Cicero on rhetoric; Follett 1924 + Walton & McKersie 1965 on negotiation; Rogers 1957 on empathic discovery; Cialdini et al. 1975 on influence; Asch 1956 on social proof), applied to enterprise AI deals. ~50 hours of study plus a 38-57 hour live-deal capstone scored against the published rubric.

What this course is built toward

Target role after completion

AI Solutions Engineer

Pay for the role is on its career guide, with its source. The course does not promise a raise.

Time investment

~60 hours

Self-paced. Most learners ship the capstone within 8–12 weeks of focused study.

What this replaces

  • · Brand-name sales methodology certifications ($2K+ each)
  • · Vendor-specific SE bootcamps that lock you into one stack
  • · Conference-circuit AI-sales tracks ($3K + travel + lost selling time)
CC available

Course author

Julian Calvo, Ed.D.

Founder of DecipherU. Twelve years in enterprise software sales; MBA, Lynn University; Ed.D. in Learning Sciences, University of Miami; M.S. candidate in Applied AI, Northeastern University. The lessons are drafted with AI from the sources they cite. No outside reviewer has signed off on this course yet.

What you will learn

After the course you can run a Fortune 500 cybersecurity AI deal cycle with the rigor of a top 0.1% AE plus the technical credibility to clear AI-specific buyer concerns.

  • Run a complete enterprise AI deal cycle

    Prospect to close to expansion using the synthesized methodology, applied to cybersecurity AI products selling into Fortune 500 buyers.

  • Qualify with the discipline of a top 10% AE

    Eight-condition qualification spine, force-ranked pipeline, clean walk-away criteria. No more deals closing on hope.

  • Conduct discovery that surfaces business pain

    Diagnostic conversations that quantify economic impact and produce decision-grade qualification, not pipeline theater.

  • Multi-thread enterprise deals across 5 to 10 stakeholders

    Economic, technical, AI ethics, security, procurement, legal. Engagement maps that compound across quarters.

  • Run C-suite engagement with insight, not pitch decks

    Executive insight presentations grounded in the customer's filings, AI strategy, and stated priorities.

  • Handle the full AI-specific objection set

    Hallucination, model bias, data privacy, vendor lock-in, frontier model dependency, governance compliance, prompt injection, training data provenance.

  • Negotiate AI deals with the right contractual posture

    Usage-based pricing, model risk indemnification, data ownership, output ownership, deprecation clauses, and AI Act compliance language.

  • Build account plans and territory strategy that compounds

    Quarterly account planning, weekly pipeline review, monthly forecast hygiene. The operations layer that makes the rest of the course pay off.

Curriculum

Sixteen modules cover the full cycle: practitioner identity, AI buyer market, discovery inquiry, buyer-readiness qualification, multi-threading, executive engagement, AI objections, proof of value, principled negotiation, expansion, pipeline, and account planning. Module 16 is a live deal capstone evaluated against the published rubric.

01Module 1, Mindset and identity of the practitioner cybersecurity AI seller5 lessons
  • 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
02module-25 lessons
  • 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
03Module 3, The DecipherU cybersecurity AI sales method, from primary sources8 lessons
  • 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
04Module 4, Cybersecurity AI prospecting and pipeline building10 lessons
  • 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
05Discovery: the diagnostic conversation10 lessons
  • 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
06Module 6 : Eight-condition qualification for AI deals10 lessons
  • 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
07Module 7 : Multi-threading enterprise AI deals8 lessons
  • 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
08Executive Engagement and the C-Suite Conversation8 lessons
  • 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
09AI-Specific Objection Handling12 lessons
  • 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
10Proof of Value: The AI-Specific Deal Stage3 lessons
  • PoC vs PoV: The Critical Distinction15 min
  • PoV Scoping15 min
  • PoV Success Criteria15 min
11Negotiation and Closing AI Deals9 lessons
  • 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
12Account Expansion and Renewal6 lessons
  • 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
13Module 13, Pipeline management and forecasting for cybersecurity AI sales7 lessons
  • 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
14Module 14, Account planning and territory strategy for cybersecurity AI sales6 lessons
  • 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
15Module 15, Sales operations for cybersecurity AI sellers6 lessons
  • 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
16Module 16, Capstone: the live deal practicum0 lessons

    Methodology synthesis

    The DecipherU Method synthesizes eight pillars from primary sources rather than from contemporary trademarked methodologies. Each pillar names its source so practitioners know what they are learning, where it came from, and which discipline applies when.

    MethodologyWhat it contributes
    Discovery InquiryAristotelian dialectic and Cicero's stasis theory applied to enterprise discovery: question sequences that surface stakes, criteria, and authority without leading the witness. Uses the question-type names from Rackham's trade book SPIN Selling (1988), which is not peer-reviewed.
    Buyer-Readiness FrameEight-condition qualification spine: economic stakes, decision criteria, decision process, paper process, business pain, sponsorship, competing alternatives, and walk-away triggers. Replaces eponymous mnemonics with a defensible diagnostic.
    Persuasion by PositionAristotle's pisteis (ethos, logos, pathos) and Cicero's De Oratore on three duties of an orator. Reframes commercial teaching as a primary-source rhetorical discipline.
    Champion ArchitectureDrucker's management writing and Hanan's 1970 consultative selling book (both books, not peer-reviewed studies): identifying, equipping, and protecting an internal champion through measurable outcomes the champion owns.
    Negotiation PostureMary Parker Follett (1924) on integrative bargaining, Walton and McKersie (1965) Behavioral Theory of Labor Negotiations, Raiffa (1982) Art and Science of Negotiation, Carl Rogers (1957) on empathic understanding from Journal of Consulting Psychology, and Aristotle's Nicomachean Ethics on phronesis (practical wisdom).
    Influence Without ManipulationCialdini, Vincent, Lewis, Catalan, Wheeler, and Darby (1975) reciprocal-concessions research from JPSP; Asch (1956) on conformity from Psychological Monographs; Festinger (1957) cognitive dissonance; and Stoic ethics on the line between persuasion and coercion.
    Practitioner IdentityBandura self-efficacy (1977), Mezirow transformative learning (1990), and Dreyfus skill acquisition: the daily disciplines, weekly self-review, and account planning that move sellers from competent to expert.
    The Long GameCarse finite and infinite games, Drucker on the duty to results, and Levitt on the marketing imagination: the operations layer that compounds across quarters and decades.

    Who the cybersecurity AI sales course is for

    Cybersecurity AE moving into AI sales

    You sell cybersecurity tooling today and your company added an AI product (or you joined an AI-native security company). The course teaches the AI-specific layer on top of the discipline you already have.

    AI-native company seller hiring the playbook

    You sell AI products and want top 10% rigor. The course gives you the DecipherU Method, qualification scorecards, and the AI-specific objection playbook your team does not yet have.

    Sales engineer or solutions architect moving to AE

    You have the technical credibility. You need the AE craft. The course teaches the discovery, qualification, multi-threading, and executive engagement that turn pre-sales depth into closed revenue.

    Prerequisites

    Required

    • Two or more years of B2B sales, sales engineering, or customer success experience
    • Working familiarity with discovery and procurement workflows
    • Basic LLM literacy as a user (you have prompted ChatGPT, Claude, or similar)
    • Willingness to commit roughly 90 to 110 hours of focused study and capstone work

    Recommended

    • Experience selling into Fortune 5000 buyers
    • Familiarity with one CRM (Salesforce or HubSpot) at a working depth
    • Exposure to a cybersecurity or AI product (selling, building, or buying)
    • A live or recent enterprise deal you can use as your capstone subject

    Reviews

    Reviews from the first cohort arrive Q2 2026. Capstones in the top 10% may be anonymized into case studies with explicit permission from the practitioner.

    Frequently asked questions

    Who is the cybersecurity AI Sales Mastery course for?

    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.

    How long does the cybersecurity AI sales course take?

    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.

    What's included while the course is free?

    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.

    What credential does the cybersecurity AI sales course issue?

    None today. Cybersecurity Sales Mastery is the only DecipherU course that issues a certificate of completion. Your capstone is a work product you keep and can show in interviews. DecipherU certificates are not accredited and carry no CEU, CPE or continuing-education credit with CompTIA, ISC2, the BACB, NMLS or any state.

    Is technical AI experience required?

    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.

    What methodology does the cybersecurity AI sales course teach?

    The course teaches eight sales approaches drawn from original sources (journal articles and books, each labeled by type) 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.

    Does the cybersecurity AI sales course cover security review?

    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.

    Can I get a refund?

    Nothing to refund: enrollment is free right now. Once a price returns, the same 7-day refund policy applies as before.

    Are reviews available?

    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.

    How is the cybersecurity AI sales course delivered?

    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.

    Free · No accountRead a full sample lesson before you enrollOpen the sample →

    This course is part of a packaged path

    Or see the packaged paths that use this course

    Each path bundles the curriculum sequence, the pay change it leads to, and the recommended courses (this one is on the list). If you are not sure which path matches your starting point, the 2-minute AI Risk Score routes you to the right one.

    Sales rep → cybersecurity sales pro

    Sell cybersecurity to enterprise buyers.

    The enterprise cybersecurity sales track for working AEs and SEs entering the security-vendor market.

    $135K OTE → $250K-$450K OTE · open path →

    Sales rep → AI sales engineer

    Sell AI to enterprise buyers.

    The AI sales mastery track for working AEs and SEs entering the AI-vendor market.

    $135K OTE → $290K-$485K OTE · open path →

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    Last verified: April 2026?Report an inaccuracy

    Course content is for educational purposes only and does not constitute professional advice. Where a lesson states a fact, it names its source, and not every source is a peer-reviewed study. Verify the sources independently.

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