AI and the Andes Retreat
What comes next for your work and your life?
You can be capable, experienced, and doing well, and still have an unanswered question about what comes next. These guides help you examine how AI may change your work, choose what to learn, and make a decision you can test.
Start with the question you actually have. A prediction about the economy may matter. So may the decision you've been putting off at your own desk.
Start where your question begins
How does AI change experienced work?
Will AI Replace Consultants? What Changes for Experienced Advisors
Will AI replace consultants? Examine the research, client value, pricing choices, and practical tests for experienced advisors deciding what to change next.
Will AI Replace CFOs? How Finance Leadership Changes
Will AI replace CFOs? Examine accounting evidence, decision authority, data controls, and a practical finance pilot before changing your team or career.
Will AI Replace Lawyers? A Practical Guide for Experienced Attorneys
Will AI replace lawyers? Examine legal research, drafting, client trust, ethics, and a practical way to test AI while keeping professional responsibility clear.
Will AI Replace Senior Software Engineers? What Changes, and What to Test
Examine AI and senior engineering with current research, real developer questions, practical workflow tests, and a decision worksheet for your next step.
Will AI Take My Job? How to Assess What Could Change
Will AI take your job? Separate task exposure from job loss, assess your responsibilities, and choose a practical next step without relying on a prediction.
What Should You Learn When AI Keeps Changing?
Choose what to learn by the work you want to do. Understand AI literacy, coding choices, technical depth, and how to practice without outsourcing understanding.
Can AI Agents Run Your Business? What You Still Need to Decide
See what separates an AI demo from a business process. Assess tasks, confidentiality, reliability, and human responsibility before delegating important work.
Should You Change Careers Because of AI? Questions to Answer Before You Move
Compare staying, reshaping your role, and changing careers because of AI. Assess your tasks, transferable skills, constraints, and a trial before a major move.
Prepare, learn, and evaluate what comes next
How Do You Prepare for an AI Future You Cannot Predict?
Prepare for AI by examining your actual work, separating evidence from predictions, and choosing one useful experiment with a clear decision and review date.
What Might AI Change by 2030? Three Scenarios and Decisions You Can Make Now
Compare three plausible AI futures using dated evidence and clear assumptions. See which signals matter and which work and life decisions you can make now.
How Much AI News Do You Need Before It Stops Helping?
Find a practical boundary for AI news: keep updates tied to your responsibilities, test relevant tools, and stop researching when your next action is clear.
Can You Trust AI to Help You Make a Life Decision?
Use AI to examine career and life decisions, check factual claims, question assumptions, and compare options while keeping the final choice and responsibility.
What do you want to do with the answer?
Worried About AI and Your Future? Start With the Question You Can Act On
Separate predictions from decisions, reduce an unhelpful news loop, and find one action you can test. A practical discussion of everyday uncertainty about AI.
What Gives Your Work Meaning When AI Can Do More of It?
Explore what AI changes about contribution, creativity, and identity. Use practical reflection to choose work and commitments that matter in your own life.
How Do You Make a Life Decision When the Future Is Uncertain?
Work through an uncertain decision by separating facts, assumptions, values, and reversible tests. Includes a practical worksheet for choosing what to do next.
Could a Retreat Help You Work Through a Question About Your Future?
Understand what a retreat can offer when you need to examine a decision, what to ask before attending, and how the work connects to action back home.
Finance: forecasts, reporting, and decisions you can defend
How to Evaluate AI FP&A Tools: Questions, Tests, and Cost
Evaluate an AI FP&A vendor with a source packet, missing-field test, data-permission review, and cost assumptions you can inspect.
AI Variance Analysis: Check the Numbers and the Explanation
Build a checked variance bridge before using AI commentary. Separate arithmetic, business causes, evidence, assumptions, and actions in FP&A reporting.
AI Financial Forecasting: How to Test Drivers, Budgets, and Business Scenarios
Review AI-assisted forecasts with explicit drivers, assumptions, calculation tests, coherent scenarios, and a worked profit-versus-cash example.
AI Cash Flow Forecasting: How to Test Receipts, Timing, and Liquidity Decisions
Test AI cash forecasts against a baseline. Review invoice timing, Excel joins, exceptions, cash accuracy, vendor claims, and the decisions treasury must own.
How to Verify AI Financial Models Before an Investor Deck
Check formulas, source definitions, cohort assumptions, and a doubled-churn scenario before using an AI-assisted financial model in an investor deck.
Finance AI Governance: Data, Approvals, Evidence, and Agent Permissions
Map finance AI data and action boundaries. Review approvals, source evidence, exceptions, vendor claims, changes, training, and a hypothetical invoice-agent case.
How Should a CFO Budget for an AI Pilot and Measure Its ROI?
Build an honest AI pilot budget. Compare full workflow costs, capacity gains, quality, usage, review effort, and three hypothetical ROI outcomes.
AI Prompts for CFO Board Reports: Drafts You Can Verify
Use a source-check workbook, board-report prompts, and a worked margin example to review AI drafts before a CFO report reaches the board.
Consulting: client questions, useful offers, and delivery
AI Market Research for Consultants: Build a Checked Evidence File
Use AI to organize market research while checking definitions, source quality, competitor claims, sizing assumptions, interviews, and recommendations.
Scope an AI Consulting Pilot: Baseline, Boundaries, and Handoff
Write an AI pilot scope with a defined workflow, approved data, a baseline, acceptance tests, review capacity, exclusions, stop rules, and client handoff.
AI Consulting Pricing: Model the Project Before Quoting It
Use an editable consulting cost calculator to compare scope, review effort, contingency, and contribution margin before quoting an AI project.
Build an AI Advisory Offer From Work You Already Know
Turn existing consulting expertise into a defined AI advisory offer with a decision, evidence packet, acceptance conditions, and honest cost assumptions.
AI Governance Readiness: Deliver a Gap Report With Owners
Assess AI governance readiness through use cases, data flows, permissions, evaluation evidence, incidents, ownership, and a prioritized client action register.
AI Change Management: Run a Small Rollout You Can Inspect
Plan an AI rollout around affected roles, review workload, observed objections, and acceptance conditions using an editable rollout sheet.
Review AI-Written Consulting Proposals Before You Send Them
Draft consulting proposals with AI while checking client requirements, deliverables, commitments, evidence, price calculations, exclusions, and approval.
Run an AI Use-Case Workshop That Produces a Decision
Facilitate an AI workshop with workflow evidence, participant prompts, eligibility gates, transparent scoring, dissent, owners, and a testable pilot decision.
AI Operating Model Consulting: Define Services and Decision Rights
Build an AI operating model with service boundaries, decision rights, workflow ownership, intake, evaluation, incident routes, funding, and rollout gates.
Legal work: review, confidentiality, and client responsibility
AI Workflows for In-House Counsel: Permission, Review, and Escalation
Use an editable permission and exception log to define an in-house AI legal workflow, its source material, review owner, and escalation conditions.
AI Legal Operations Intake: Routing, Status, and Approval
Build a legal operations AI intake workflow with matter records, routing checks, approval dependencies, service measures, and a 30-day pilot.
AI Law Firm Billing: Actual Work, Fees, and Client Value
Examine AI-assisted legal billing with a worked hourly invoice, review time, tool expenses, client communication, and a future fixed-fee proposal.
AI and Client Confidentiality: Check the Workflow Before Uploading
Check product terms, retention, training use, consent, and review ownership before putting client information into an AI workflow.
AI Legal Brief Review: Verify Citations, Facts, and Reasoning
A proposition-ledger method for AI-assisted briefs, including real-but-unsupported cases, quotations, factual sources, reasoning, and filing review.
AI Contract Review: Keep Redlines, Sources, and Decisions Separate
Inspect a synthetic AI-assisted contract review with original text, proposed changes, an exception log, and unresolved decisions for counsel.
AI eDiscovery and Privilege Review: Test the Actual Decisions
Evaluate AI document review with source manifests, reference sets, missed-material checks, privilege escalation, chronology, redaction, and release records.
AI M&A Legal Diligence: Sources, Missing Evidence, and Decisions
Build an AI-assisted M&A legal diligence issue register with entity checks, missing evidence, provision review, follow-up requests, and client decisions.
Engineering: architecture, code quality, and team decisions
AI for Staff Engineer Architecture Decisions: A Reviewed Design, Not a Confident Diagram
Use AI to prepare an architecture decision record with verified constraints, alternatives, failure tests, permissions, and a practical 30-day review plan.
AI Legacy Code Refactoring: Preserve Behavior Before You Simplify the Code
Plan an AI-assisted legacy migration with characterization tests, compatibility checks, dependency review, rollback criteria, and a worked refactoring worksheet.
AI Code Review for Senior Engineers: Review the Change, the Evidence, and the Remaining Risk
Review AI-generated pull requests with a risk rubric, independent acceptance checks, dependency and permission review, a worked case, and a 30-day team trial.
AI Developer Productivity: Measure Review, Quality, and Cost
Use an editable pilot log and calculator to measure AI-assisted engineering work, including reviewer effort, rework, quality, and complete costs.
AI Software Testing: Verify the Test Before Trusting the Green Result
Evaluate AI-generated tests with independent expectations, negative cases, state and permission checks, mutation examples, and a practical test-adequacy worksheet.
Build or Buy an AI Capability? Include the Simpler Workflow and the Exit Plan
Compare building, buying, and a simpler workflow using task acceptance, data permissions, integration, operating costs, exit criteria, and a worked enterprise AI case.
AI-Generated Code and Technical Debt: Decide What the Team Can Maintain
Assess maintenance obligations from AI-assisted code using an issue inventory, ownership and risk criteria, a worked service case, and a 30-day remediation plan.
Experienced Engineer to AI Work: Test a Move Before Committing
Test an AI career move with a real task, acceptance evidence, review effort, and a decision exercise that separates learning from a job forecast.
AI and Engineering Manager Workload: Where the Work Moves
Trace how AI shifts engineering preparation, review, rework, and coordination using a task log instead of a universal team-size formula.
AI and the Andes Retreat: bring the question you keep returning to
AI and the Andes Retreat begins with the question of what comes next for you. A useful answer often has to be tested in your life. AI and the Andes Retreat is a five-day seminar retreat in Peru's Sacred Valley, for 8-15 participants, with no plant medicine. The work is to examine behavior, identify what is driving it, and choose actions you can carry home.
If you've understood your options and still keep delaying the next step, time and space for that inquiry may be useful. Explore AI and the Andes Retreat.
Put the answer to work
Use the editable source checks, cost models and review logs. Each worked example states its assumptions and limits.
Ask about AI and the Andes Retreat
If you have a decision or recurring pattern you want to investigate, tell Florian a little about the question. He can discuss whether the five-day Sacred Valley seminar may fit.