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Tech Strategy in the AI Era — A Playbook

Architect for agents as first-class users, not bolt-ons

Every SaaS tool you bought in 2019 assumed humans were the users. Every new tool assumes agents are. 27 modules on how to audit your stack, pick what stays, what goes, what becomes API-first, and how to make sure the tools you choose tomorrow don't lock you out of the agents you'll run next quarter. The tech strategy job changed; this is the new version of it.

27 interactive modules69-page PDF9 PDF chaptersInstant PDF + PortalFree strategy call included$27
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How to read this playbook · The AI-Era Lens

Tech stack when agents are the users

The foundation in this playbook (architecture decisions, vendor evaluation, build-vs-buy, observability, security) is timeless. The AI era inverted the buying scorecard and changed which tools become structural to your stack. Hold these six shifts in your head as you work through every module — same disciplines, very different inputs.

Shift 1

The buying scorecard inverted

Old order: features → price → UI → security → support → integrations. New order: API completeness → auth granularity → event coverage → rate limits → observability → security → price. UI moved way down because most of the team isn't in the UI anymore. Read the vendor evaluation modules with an inverted scorecard.

Shift 2

Auth granularity is the bottleneck

Whole-team accounts with everything-or-nothing API tokens are increasingly unusable. Per-agent credentials with minimum-scope permissions become structural. Read the security and access modules with 'can I grant an agent permission to do exactly X' as a load-bearing test.

Shift 3

Webhooks beat polling, by a lot

Polling stacks up across many agents and burns rate limits. Webhook-first tools become first-class citizens. Read the integration modules with 'do they emit events as webhooks or only on polling' as a deciding factor.

Shift 4

The build-vs-buy line moved

Building dropped roughly an order of magnitude because agents handle most of the implementation. Things that were 'obviously buy' in 2019 are 'honestly worth building' in 2026 — bespoke CRM, internal dashboards, ops tooling. Read the build-vs-buy modules with the new math.

Shift 5

Migration cost dropped, switching cost stayed

Data migration is fast now (agents do it). Agent-rule rebuilding isn't — every agent configured against the old vendor has to be redesigned against the new one. Read the vendor selection modules assuming longer-term commitments and deeper diligence up front.

Shift 6

Observability changed shape

Logs/metrics/traces still matter. What's new is agent-watching primitives — replay decision trees, audit hallucinations, capture the customer-saw-Y-when-it-should-have-been-X moment. Read the observability modules as 'design agent introspection,' not just app introspection.

How to read the foundation modules

Read every framework in this playbook through these six shifts. Architecture principles still apply. Security still matters. ROI math still works. What changed is which tools are structurally fit for an agent-augmented operation. When you do a vendor-evaluation exercise, weight API/auth/events at the top and UI near the bottom.

What's Inside

27 interactive modules — first 3 are free to preview.

1Tech Stack Audit & Rationalization
2Integration Architecture Design
3Tool Selection Framework
4Data Flow Mapping
5Migration & Implementation Plan
6Security & Compliance Checklist
7Customer Data Platform & Single Source of Truth
8Analytics & Business Intelligence Setup
9Website & Digital Experience Technology
10Marketing Technology (MarTech) Stack Design
11CRM Strategy & Configuration Playbook
12Sales Technology & Enablement Tools
13Workflow Automation & iPaaS Design
14Customer Communication & Messaging Platforms
15E-Commerce & Payment Technology
16Cloud Infrastructure & Cost Management
17API Strategy & Developer Experience
18Disaster Recovery & Business Continuity
19Cybersecurity Framework & Incident Response
20AI & Machine Learning Use Cases for Growth
21Customer Support Technology & Self-Service
22Product Analytics & Feature Adoption Tracking
23Technology Training & Adoption Programs
24Technology Roadmap & Prioritization Framework
25Build vs. Buy Decision Framework
26Technology Team Structure & Vendor Management
27Annual Technology Review & Investment Plan

Why this workbook?

01

Actionable exercises

Not theory — hands-on activities you complete for your business.

02

Scoring frameworks

Rate where you stand today and track improvement over time.

03

Battle-tested templates

Proven by hundreds of businesses across industries.

04

Walk away with a plan

By the last page, you have a concrete action plan ready to execute.

Who is this for?

Technology leaders who want a proven system, not guesswork
Founders and CEOs building their first growth engine
Teams that need a shared framework to align and execute
Consultants who need ready-to-use client deliverables
TS

Written by Tiago Santana

Growth operator. $100M+ in revenue generated across companies. Founder of Gardenpatch and The Cooling Co.

I've spent the last decade running technologyfor companies at $1M–$100M ARR. When AI agents joined the team, almost everything I knew got rewritten. This playbook is what I'd hand a new technologyleader on day one in the AI era — not what worked in 2019. Every module is something I'd actually use, today, in my own companies. Money-back if it doesn't help.

More about Tiago →

Founding members get a free copy

The honest version: these playbooks launched in May 2026. No reviews here yet — because the first ten people are still reading them.

First 10 reviewers · honest feedback wanted

Free copy of any playbook in exchange for an honest review.

Read it. Use it on a real problem you're working through. Tell us what landed, what didn't, and whether it was worth $27. Your review goes on this page (with your name + role, or anonymous — your call). You also get a free 30-minute strategy call with Tiago to apply it to your specific situation.

Who this is for: operators running a real team (any size, any industry) who would actually use a framework like this and tell the truth about it. Not for resellers, not for AI-generated reviews, not for five-star-as-default. Critical reviews are more useful than glowing ones.

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