StackLift AI
Delivery playbooks

Practical checklists for scoping and shipping software.

Use these pages to prepare AI projects, estimates, modernization work, SaaS MVPs, workflow automation, agent workflows, and production launches.

Founders, CTOs, operators, and product leaders preparing an AI build

AI Project Discovery Checklist

A practical checklist for scoping an AI project before estimation: goals, data, users, risk, integrations, and launch readiness.

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Teams comparing software build options and budget ranges

Software Estimation Playbook

How to turn an idea, PRD, backlog, or reference product into a defensible software estimate with scope, risk, cost, and timeline.

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Enterprise teams planning AI copilots, RAG, automation, or agent systems

Enterprise AI Readiness Checklist

A readiness checklist for enterprise AI software: data access, governance, security, evaluation, human review, and operations.

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Leaders responsible for aging internal systems, portals, or platforms

Legacy Modernization Roadmap

A practical roadmap for modernizing legacy software without a risky big-bang rewrite: audit, slice, replace, migrate, and stabilize.

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Founders and product teams preparing a SaaS MVP

SaaS MVP Launch Plan

A SaaS MVP launch plan covering scope, roles, payments, onboarding, analytics, support, security, and release readiness.

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Operations teams replacing manual work with software automation

Workflow Automation Discovery

A discovery checklist for workflow automation: process steps, systems, exceptions, approvals, audit, and ROI.

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Teams planning multi-agent software or operational AI workflows

Agentic Workflow Design Playbook

How to design AI agent workflows with task boundaries, permissions, review gates, telemetry, and escalation paths.

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Founders, CTOs, and delivery teams preparing a launch

Production Readiness Checklist

A practical production readiness checklist for CI/CD, environments, monitoring, QA, rollback, security, and support.

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Turn a playbook into a scoped plan.

Use the free estimate flow to convert discovery notes into an AI-assisted, architect-reviewed scope, cost range, and timeline.