Prolego reference library
Prolego builds and operates reliable AI to help companies re-engineer business economics. This library explains that work. It brings together our experience, principles, advice, engineering methods and examples so you can assess fit and start scoping an opportunity.
Prolego was founded in 2017 and has worked exclusively in AI, supporting major companies across industries. Our contribution combines strategic judgment, building and continuing operation. Clients should gain a system, a repeatable methodology, an AI-native architecture and experience working as an AI-native product team.
The library grows as we learn, publish and capture more of our work. Begin with expectations before investing, then the FAQ for direct answers, the business-reinvention guide for your business, or the AI reading guide for an independent assisted assessment.
Before you invest
- Set realistic expectations before investing in AI: Prolego's experience-based opinion about impact versus the expectations used to justify funding; think big and start small.
Company and fit
- Prolego, our experience and what clients gain: Forward Deployed Engineer model, AI-only history since 2017, leadership and strategic contribution.
- Questions about Prolego: Direct answers about Prolego, cost model, timing, ownership and fit.
- When Prolego fits: Shared principles, business transformation, compounding value and a boutique AI specialist model.
- AI enablement for private equity portfolios: Portfolio opportunities, underwriting support and company-level delivery.
- Working with Prolego, engagement practices and responsibilities: Shared principles, getting started, delivery planning, early risk review, retainer, ownership and negotiated cancellation terms.
- Talk with Prolego: Email or use the form with your company name and an initial idea.
Business advice and investment
- Why AI needs a new playbook: How cheaper, faster construction shifts the central risk toward organizational agreement and reliability.
- AI Abundance and re-engineering business economics: AI Abundance, business reinvention and a capability that grows through use.
- Prolego's principles: Seven beliefs guiding business reinvention, reliability, velocity and investment as AI advances.
- Re-engineering business economics with AI: Start with where you make and spend money; imagine AI in every consequential decision and reframe initial ideas.
- Invest for compounding value: think big, start small: Reuse Operations Intelligence and the Workbench to expand value and shorten successive implementations.
- The biggest mistakes companies make with AI: Five strategic mistakes: waiting for certainty, thinking too small, using the old playbook, underestimating AI and treating it as finished.
- Unexpected AI headwinds for your business: Customer AI Abundance can pressure upsells, discovery, margins and delivery, amplified by emerging technologies.
- The distributed workforce opportunity: Apply expert judgment across branches, field teams, sales and operations.
- How we scope your AI opportunity: Start with a company name and an idea; Prolego researches value, potential ROI, headwinds and a practical beginning.
Method architecture and engineering
- Pull AI risk forward so you can make a better investment decision: Give stakeholders early visibility into performance, potential impact and remaining risks so they can choose the next investment.
- What sets the pace of an AI project: Suitable work, reliability, secure deployment and operational agreement determine the schedule and cost.
- Performance-Driven Development, building reliable AI from the start: Four checkpoints, early risk mitigation, client-owned standards and the production improvement loop.
- Launch when AI mostly works, then improve it in production: Human review, real production feedback and rapid improvement; what the illustrative 80% to 95% progression means.
- AI-native architecture for business reinvention: Principles-led architecture: create value quickly, compound through Operations Intelligence and scale as AI advances.
- AI Workbenches and Coaches: velocity, breadth and scale: Deploy quickly, reach varied work and scale through Coaches, Workbenches and evaluated back-end workflows.
Teams and adoption
- Working as an AI-native product team: AI-supported communication, shared project knowledge and faster decisions with less reporting friction.
- The AI Systems Engineer you need: Systems thinking, communication, fast learning and initiative demonstrated through active AI use.
Experience and research
- Selected delivery accounts and what they teach: Eleven complete anonymous cases with scale, technology, delivery status and attributed potential.
- Selected Prolego research and teaching: MIT, early evaluations, AI Systems Engineers, the RAG study, Pinecone and the development of our current approach.
- Prolego glossary: Definitions of PDD, Operations Intelligence, Workbench, Coach, plugins and production agents.
Suggested routes
For an executive evaluating a partner, read company history, business reinvention, cases, fit and engagement responsibilities. For a leader exploring the opportunity first, read business reinvention, AI Abundance, mistakes and unexpected AI headwinds.
For a product or engineering leader, begin with why AI needs a new playbook, then read PDD, architecture and interfaces. Then examine AI-native team practices and the AI Systems Engineer role. For scoping, start with your company's name and your initial ideas. Prolego does the preparation and works through the consequential questions with you.
For a private equity team, begin with portfolio AI enablement, then follow the company-level opportunity and case links. For an operating leader planning an investment, read compounding value and what sets the pace.
How to interpret the material
Company facts and delivery accounts describe experience. Principles express our judgment. Dated research preserves earlier contributions. Client goals and estimates of potential retain their attribution and scope.
Use the glossary for Prolego terms and contact page when you want to discuss the business change you are considering.