Specialised Track · Sales Function

Put AI to work across the sales cycle.

A three-day, hands-on programme for sales leaders, account executives and revenue operations teams. Redesign prospecting, lead scoring, personalised outreach, proposal drafting, pipeline forecasting and competitive intelligence with applied AI and agentic automation. Every delegate leaves with a working lead triage agent built in their own Codespaces lab, an AI sales playbook and a ninety-day plan for their team.

3 days 16 modules 60%+ hands-on Codespaces lab included STOA certified
Daniel Sto
Why this programme exists
"Scoring a lead, drafting the outreach, calling the forecast. Each is an agent waiting to be built. The relationship still belongs to the salesperson."
Daniel Sto · Director of Faculty, STOA Institute
Duration
3 days
Format
Live online or on site
Next open date
Private cohorts
Fee
On request
per delegate
For teams
Private cohort from 8 delegates
Schedule a TNA call
Programme overview

Built around the sales cycle, from prospecting to forecast.

This three-day programme is built for sales leaders, account executives and revenue operations teams who have to decide where AI belongs in their sales cycle. It is analytics-led and pipeline-first: participants work on their own accounts and their own pipeline data, finding and scoring prospects, building research-driven outreach, drafting proposals, forecasting with more than one method, and running the deal reviews and post-mortems that keep a forecast honest. Generative AI does that research, drafting and summarising well, and an AI agent goes one step further: given a goal, it reads the inbound lead, applies the scoring rules, drafts the follow-up and hands the result to a salesperson for approval. The decisions that follow sit with the sales leader: which work is handed over, under which rules, and on what evidence the result can be trusted in front of a prospect.

Day one establishes how generative AI works, takes every participant through structured prompting on their own accounts, and maps AI across the sales cycle before going deep on prospecting: the ideal customer profile, trigger events and buying signals, weighted lead scoring, list building with deep research modes, and account and competitor research. Day two covers the middle of the funnel: research-driven outreach and multi-touch cadences, proposal and business review drafting, pipeline forecasting with trend, weighted pipeline and regression methods, signal-based deal reviews and forecast post-mortems, and conversation intelligence for coaching. Day three moves from assistants to agents. Participants design and build an inbound lead triage and follow-up agent on a lead list carrying realistic ambiguity and planted edge cases, instrument it and read its traces, metrics and costs, then settle the CRM automation and governance rules under which an agent may work in front of prospects.

Every lab runs in a pre-configured cloud environment opened from a browser, with no software to install. Participants choose a visual build track or a coding-agent track, and each lab is verified against fixed acceptance criteria. Participants leave with a working lead triage agent, a sales prompt library, a weighted scoring model, an outreach cadence, an evidence pack of traces and metrics, an AI sales playbook for their team and a ninety-day rollout plan. The programme finishes on where the field is heading: agentic AI, where a sales agent is given a goal and researches, scores, drafts and updates the CRM under human supervision, with context engineering, loop and graph engineering, agentic retrieval-augmented generation, the Model Context Protocol and voice agents.

Who should attend

This programme is designed for sales and revenue teams in B2B and enterprise sales across all industries:

  • Chief Revenue Officers, Sales Directors and Heads of Sales
  • Sales Managers, Regional Sales Managers and Sales Team Leads
  • Account Executives and Key Account Managers
  • Business Development Managers and Business Development Representatives
  • Inside Sales Representatives and Sales Development Representatives
  • Sales Operations and Revenue Operations Analysts and Managers
  • Sales Enablement Managers and Sales Trainers
  • Presales and Solution Consultants
  • Commercial Directors and Bid Managers

Learning outcomes

By the end of this programme, participants will be able to:

  • Explain how generative AI works and where its output needs verification
  • Apply the C.L.E.A.R. framework and K-shot prompting to sales work
  • Map AI opportunities across their own sales cycle and CRM data
  • Define an ideal customer profile, spot buying signals and score leads with a weighted model
  • Research accounts and competitors and build a battlecard with AI
  • Build research-driven, personalised outreach cadences with AI drafting and human polish
  • Draft proposals, bid responses and business review packs with AI
  • Forecast with three methods and explain why they disagree
  • Run signal-based deal reviews and forecast post-mortems (MAPE, bias and slippage)
  • Turn call transcripts into coaching insight and CRM updates
  • Build a working lead triage and follow-up agent
  • Evaluate an agent's traces, metrics, costs and failure modes
  • Apply governance controls to AI in front of prospects and customers
  • Leave with an AI sales playbook and a ninety-day plan for their team
Programme outline

Sixteen modules. Three days. One working sales agent.

Every module follows the TEA™ framework, twenty percent theory, twenty percent examples, sixty percent hands-on application on your own accounts and pipeline. Day one maps AI across the sales cycle and goes deep on prospecting; day two covers outreach, proposals, forecasting and deal execution; day three builds, evaluates and governs a lead triage agent.

Day 1: The Sales AI Landscape and Prospecting

01
Day 1 · Module

Generative AI Essentials for Sales Professionals

  • What is generative AI?
  • Large language models and chat assistants (ChatGPT, Claude, Microsoft Copilot, Gemini)
  • Tokens, context windows and memory
  • Chat models, reasoning models and deep research modes
  • Hallucination and non-determinism
  • Verification of AI output before it reaches a prospect
  • Prospect and customer data in AI tools
Live walkthrough the calculator test
02
Day 1 · Module

Prompting for Sales Work

  • The C.L.E.A.R. prompt engineering framework
  • K-shot prompting (zero-shot, one-shot, few-shot, multi-shot)
  • Chain-of-thought prompts
  • Persona, tone and house-style instructions
  • Structured outputs (account summaries, call notes, comparison tables)
  • Common prompting errors in sales copy
  • The sales prompt library and reusable agent skills
Hands-on exercise applying C.L.E.A.R. to participants' own accounts and pipeline
03
Day 1 · Module

AI Across the Sales Cycle

  • The sales cycle (prospecting, qualification, outreach, discovery, proposal, negotiation, close, account management)
  • Where AI moves sales numbers
  • CRM data hygiene before intelligence
  • AI features inside CRM and revenue platforms (Salesforce Agentforce, HubSpot Breeze, Microsoft Dynamics 365 Sales, Gong, Clari)
  • Use case mapping across prospecting, deals and forecasting
  • Deterministic and probabilistic work in the sales cycle
  • Where the salesperson stays in each workflow
  • Quick wins on this quarter's pipeline
Hands-on exercise the Sales AI Opportunity Map on participants' own pipeline
04
Day 1 · Module

Prospecting and Lead Scoring

  • The ideal customer profile (ICP):
    • Industry, company size and geography
    • Contact seniority and buying roles
    • Disqualifiers (students, competitors, companies below the size threshold)
  • Trigger events and buying signals (funding, hiring, expansion, leadership change, technology change)
  • Weighted lead scoring (fit, signal, access)
  • Lead tiering and score thresholds
  • List building with deep research modes (ChatGPT, Gemini, Claude, Perplexity)
  • Data sources and enrichment (LinkedIn Sales Navigator, ZoomInfo, Apollo, Clay)
  • Predictive lead scoring inside the CRM
Hands-on exercise find, score and pursue, building a weighted scoring model on participants' own prospects
05
Day 1 · Module

Account Research and Competitive Intelligence

  • Prospect and account research
  • The account research brief (structure, priorities, decision makers, recent events)
  • Deep research reports on target accounts
  • Competitor monitoring and battlecards
  • Market and trend analysis
  • Win and loss analysis from CRM notes
  • Competitive positioning and differentiators
  • Source checking, citation and fabricated facts
Individual and pair work building a research brief and battlecard on a target account

Day 2: Outreach, Forecasting and Deal Execution

06
Day 2 · Module

Outreach and Personalisation

  • Research-driven personalisation
  • Personalisation signals (role, trigger event, shared context, prior contact)
  • Multi-touch cadences (the Dream 100 pattern)
  • Channel mix (email, LinkedIn, phone, video)
  • AI-drafted outreach with human polish
  • Reply handling and follow-up discipline
  • Objection responses from a library
  • Sales engagement platforms (Outreach, Salesloft, HubSpot Sequences)
  • Consent, opt-out and outbound compliance (GDPR, PDPL)
Hands-on exercise building an eight-touch cadence for participants' top ten accounts
07
Day 2 · Module

Proposal and Sales Document Generation

  • Discovery notes to proposal structure
  • Proposal, bid and tender response drafting
  • Question banks and past proposals as source material
  • Pricing and value narratives
  • Executive summaries and cover letters
  • Quarterly business review packs
  • Account plans and renewal cases
  • Human review and sign-off of AI-drafted documents
Individual and pair work drafting and peer-reviewing a proposal section from participants' own discovery notes
08
Day 2 · Module

Pipeline and Forecasting

  • Three forecasting methods (trend, weighted pipeline, regression)
  • Leading and lagging indicators in the funnel
  • Buyer-action signals and CRM stages
  • Forecast categories (commit, best case, pipeline)
  • Coverage models and pipeline sufficiency
  • AI data analysis on pipeline exports (Excel, Google Sheets, ChatGPT, Claude)
  • Forecast narratives for the weekly call
Hands-on exercise one company, three forecasts, then explaining the spread
09
Day 2 · Module

Deal Execution and Forecast Post-Mortems

  • Signal-based deal reviews (the six buyer actions)
  • Mutual action plans
  • Deal risk flags and next-best actions
  • Forecast post-mortems:
    • Mean absolute percentage error (MAPE)
    • Directional bias
    • Slippage by channel, stage and rep
  • Pipeline hygiene automation (stale deals, missing close dates, next-step reminders)
Case study analysis why we missed, a forecast post-mortem on a deal log
10
Day 2 · Module

Conversation Intelligence and Sales Coaching

  • Sales manager workflows (pipeline reviews, one-to-ones, coaching)
  • Call recording and conversation intelligence (Gong, Chorus, Zoom AI Companion, Microsoft Teams)
  • Call notes to coaching insight
  • Talk ratios, objections and next steps from transcripts
  • Meeting follow-up and CRM notes
  • Coaching plans and skill gaps by rep
  • Recording consent and customer data in transcripts
Hands-on exercise turning a call transcript into coaching notes and a CRM update

Day 3: Sales Agents and the AI-Assisted Sales Team

11
Day 3 · Module

AI Agents for Sales

  • What is an AI agent?
  • Agents, assistants and workflow automation
  • The agent loop (goal, observe, reason, act, evaluate, repeat)
  • Levels of autonomy and human-in-the-loop
  • The build spectrum (no-code, low-code, full-code)
  • Visual agent builders and coding agents (n8n, LangFlow, Claude Code)
  • Agents inside CRM platforms (Salesforce Agentforce, HubSpot Breeze Agents, Microsoft Dynamics 365 Sales agents)
  • Sales agent use cases (lead triage, account research, follow-up drafting, CRM updates, forecast commentary)
  • The agent design brief (goal, inputs, tools, outputs, guardrails, success criteria)
Live demonstration an agent completing a multi-step sales task end to end
12
Day 3 · Module

Building the Lead Triage and Follow-Up Agent

  • The lab environment (GitHub Codespaces, browser-based, pre-configured)
  • The inbound lead case (a software company, thirty to fifty inbound leads a week, a shared spreadsheet)
  • The ICP and tiering rules (industry, company size, seniority, budget and timeline signals)
  • Lead tiers (Hot, Warm, Cold, Duplicate) with a reason per lead
  • Follow-up drafts for Hot leads
  • The two build tracks (visual canvas, coding agent)
  • Planted edge cases (students, competitors, duplicates, small companies without a budget signal)
  • Acceptance criteria and automated checking of results
Lab building the inbound lead triage and follow-up agent end to end
13
Day 3 · Module

Monitoring and Evaluating the Sales Agent

  • Observability for AI agents (LangSmith)
  • Traces and their contents (context, prompt, model response, tokens, latency, cost)
  • The metrics baseline
  • Failure-mode probes and abstention on missing information
  • Optimisation levers (instructions, context size, model choice)
  • Measured before-and-after comparison
  • The Agent Health Check measures:
    • Groundedness and source citation
    • Tiering and escalation behaviour
    • Hallucination and omission rates
    • Prospect-data leakage
    • Cost, latency and reliability
Lab instrumenting the lead triage agent, recording the baseline and running a failure-mode probe
14
Day 3 · Module

CRM Automation, Governance and the AI-Assisted Sales Team

  • CRM automation patterns and rep adoption
  • Agent hand-offs into the CRM (lead creation, task creation, sequence enrolment, stage updates)
  • Human approval points before customer contact
  • Governance for AI in front of prospects and customers:
    • Prospect and customer data, privacy and consent (GDPR, PDPL)
    • Disclosure of AI use in outreach
    • Brand, claims and what an agent may promise
    • Acceptable-use policy and the agent register
  • The regulatory and standards direction (EU AI Act, ISO/IEC 42001, NIST AI Risk Management Framework)
  • Role redesign across SDR, account executive and manager workflows
Controlled group discussion which sales motions an agent may run without a person in the loop
15
Day 3 · Module

Emerging Methods

  • Context engineering
  • Loop engineering and graph engineering
  • Agentic retrieval-augmented generation (RAG)
  • Model Context Protocol (MCP) and CRM connectors
  • Computer use and browser agents for account research
  • Voice agents for inbound qualification
  • Multi-agent patterns (research, draft, review)
Live demonstration an agent using external tools through the Model Context Protocol
16
Day 3 · Module

Capstone: Personal Action Plans

  • The sales AI use-case portfolio
  • Value, feasibility and risk assessment
  • The pilot definition for the lead triage agent (scope, owner, success criteria, review points)
  • The team's AI sales playbook (prompts, cadences, scoring model, review rules)
  • The ninety-day rollout for the team (next steps, priority use case, timeline, owners)
Personal action planning each participant's AI sales playbook and ninety-day plan
Day 3 · Course closing

Course closing

  • Course debrief and key takeaways
  • Final Q&A
  • Official closing ceremony and award of certificates
  • Group photo
Our training methodology

Three frameworks behind every programme.

Whatever programme you choose, it follows three proven instructional frameworks, from design to delivery to evaluation.

Delivery

TEA™ Delivery Framework

  • T Theory, core concepts & frameworks
  • E Examples, live demos & case studies
  • A Application, hands-on exercises & practice

Our signature approach structures every module into three phases for maximum retention and practical application.

Design

ADDIE Instructional Design

  • A Analyse, assess learner needs
  • D Design, structure the learning path
  • D Develop, build materials & activities
  • I Implement, deliver the programme
  • E Evaluate, measure outcomes & refine

The industry-standard model for course design and learning alignment.

Evaluation

Kirkpatrick Model

  • L1 Reaction, participant satisfaction
  • L2 Learning, knowledge & skills gained
  • L3 Behaviour, on-the-job application
  • L4 Results, business impact & ROI

The globally recognised four-level framework for measuring training effectiveness, from initial reaction to long-lasting post-training effects.

Upcoming sessions

Choose your date.

Private cohorts for sales and revenue teams, live online or on site. Schedule a TNA call and receive a custom proposal within 48 hours.

Date
Format
Duration
Price
Private cohorts run on request.
Live virtual or On-site
1/2 to 5 days
Custom
What every participant gets

You keep everything.

No vendor lock-in, no paywalled materials. Every delegate leaves with the working files, the templates, and the post-programme support to actually use them.

Personal prompt library

8 – 12 tested prompts built during the session on your actual work scenarios.

Templates & dashboards

Dashboards, workflow templates, and evaluation frameworks ready to use.

Learning materials

Full soft copy of all session materials, handouts, and reference guides.

STOA certificate

Certificate of Completion plus a guided pathway to the Google AI certificate.

30-day support

Post-programme Q&A availability and implementation guidance.

Lifetime updates

Access to updated prompt libraries and resources as AI tools evolve.

Delivery options

Choose how your team learns.

In-Person

Instructor-led on-site

Delivered at your offices or venue. Maximum engagement for teams of 8 – 25 participants. All exercises use your team's actual work scenarios.

Live Online

Virtual instructor-led

Real-time delivery via Zoom, Meet, or Teams. Interactive breakout rooms, same content depth as in-person. Ideal for distributed teams.

Hybrid

Blended approach

Combine in-person and virtual sessions. Flexible scheduling across time zones. Pre-work materials and follow-up resources included.

Training catalogue

104 courses in nine families, overview level, methodology up front.

Download the catalogue
Ready to build

Give your sales team a working agent and a forecast they can stand behind.

Book a private programme for your sales team. Custom proposal within 48 hours. Delivery live online or on site.