Knowledge Architecture · AI Operations · Documentation Engineering
Mansa Gills
I build trusted knowledge systems that help people, products, and AI work better.
For more than 10 years, I've helped fintech, SaaS, AI, and developer-platform organizations turn fragmented information into structured systems that improve self-service, product adoption, internal alignment, and decision-making. My work combines information architecture, documentation strategy, governance, program leadership, and AI-enabled workflows so knowledge can be reused reliably by both people and intelligent systems.
How I Create Value
Documentation is a system, not just a collection of pages.
Effective knowledge work requires strategic planning, clear ownership, thoughtful structure, and continuous improvement. I design the systems behind the content so internal teams, customers, developers, and AI tools can find trusted information and use it efficiently.
Information architecture, taxonomies, content models, navigation, and source-of-truth systems designed around real user workflows.
Roadmaps, review workflows, standards, ownership models, and reporting practices that keep knowledge accurate as products and organizations change.
Source grounding, retrieval analysis, prompt and validation workflows, chatbot evaluation, and reusable context that make AI outputs more dependable.
Program planning and coordination across Product, Engineering, Support, Customer Success, Implementation, Design, and leadership teams.
10+
Years building technical knowledge systems
50%+
Reduction in developer support tickets at Peach
100
REST endpoints supported through structured documentation
6+
Enterprise client programs managed at ReadMe
Portfolio Overview
Five core specialties spanning AI chatbot architecture, content strategy, and technical leadership, each backed by a real case study.
Embedded in API design processes across multiple companies -- shaping naming conventions, parameter structure, and endpoint behavior alongside engineering, and co-authoring product design docs.
Worked hands-on with MCP integrations across platforms including Claude, Stripe, Supabase, and Webflow. Contributed to the development and testing of a production MCP feature.
Developed multi-audience content frameworks for 6+ major tech clients at ReadMe spanning FinTech, AI/Hardware, and Enterprise SaaS. Built docs that drove adoption and reduced support load.
Wrote full OpenAPI specifications from scratch that went directly into production. Led API reference overhauls, Postman collections, and SDK docs at Affirm, Veeva, Delhivery, and ReadMe.
Designed end-to-end AI workflows for Levias Lending including Voice AI cold-calling agents, social media automation, and internal knowledge management systems.
Featured Work & Documentation
Explore our comprehensive guides, API documentation, and integration resources designed to help you implement robust financial and identity verification solutions.
Tech Blog Articles
Long-form technical and help-center content written for developer- and IT-focused audiences — spanning observability, cybersecurity, endpoint management, and consumer gaming support.
Philosophy
The principles that guide how I think about documentation, AI systems, and human-centered design.
Documentation Philosophy
"Great AI experiences begin with great explanations."
My approach to documentation transforms technical complexity into empowering user experiences. Technology should be accessible and genuinely helpful, not intimidating. I turn dry technical content into human-centered guides that help users solve real problems and feel capable, not lost in jargon.
01AI Philosophy
"Partnership over replacement."
I use AI as both a tool and a collaborator: to enhance writing quality, streamline client workflows, and create efficiency that lets teams focus on meaningful work. The goal isn't to automate everything; it's to amplify human creativity and problem-solving. I build AI systems with guardrails, quality review, and genuine user empathy baked in.
02Communication Philosophy
"Strategy is the bridge between capability and adoption."
The future of AI isn't defined solely by technical capabilities, but by how well we communicate its value and guide users through meaningful interactions. Strategic content leadership, synthesizing diverse stakeholder needs into cohesive, clear solutions, is what drives adoption, reduces friction, and empowers people to excel.
03Let's Connect
Ready to build better AI experiences together? Reach out directly or ask my AI assistant anything about my background.