AlignTrue
AlignTrue is an open-source reference architecture for supervised AI systems that need durable receipts, replayable state, governed actions, and fenced side effects.
Learn moreReceiptsReplayabilityGovernance
Applied AI product lab.
Main Character is Gabe Mays's lab for building AI products and making existing software more AI-native. The work is the research: what models can do, what users adopt, which product patterns hold up, and where the technology is actually useful.
Operating model
Building is how the lab learns.
01
Build
Make products and prototypes instead of only studying AI from the outside.
02
Learn
Use hands-on work to see what models, tools, and users actually do.
03
Reuse
Carry forward the product patterns and technical pieces that hold up.
Building is the research method.
Working directly with current models, coding tools, users, and operating constraints gives better signal than watching from the outside.
The lab shows where models are useful, where infrastructure bottlenecks matter, what people actually adopt, and which patterns become durable.
That firsthand product signal informs Gabe's AI investing and his conversations with founders, operators, and investors.
Selected projects
Work across consumer AI products, model audit tools, agent architecture, and frontline software. Different surfaces, same lab pattern: build, learn, and keep what proves useful.
These are selected public examples, not an exhaustive project history. Some related systems, client implementations, and reused patterns remain private.
GlassAlpha
GlassAlpha is an open-source toolkit for deterministic audit reports for tabular ML models, with fairness, explainability, calibration, robustness, and reproducibility metadata in one local workflow.
Learn moreML auditFairness testingReproducible reports
Maintenance Control
A private MVP build for approved-publication retrieval, voice query, and source-cited maintenance guidance on phone, web, and wearable surfaces.
Learn moreGrounded retrievalVoice queryControlled manuals
Other projects
Additional work across consumer AI, ecommerce AI, SaaS automation, developer and CMS tools, documentation software, and product leadership. Most of that work is private or narrow by design; the value is repeated exposure to real workflows and constraints.
About GabeConsumer AIEcommerce AISaaS automationDeveloper tools
Reusable AI product patterns
The reusable parts of applied AI work: product surfaces, context, evaluation, workflows, human review, provenance, and handoff.
AI-native product surfaces
Modernization paths
Durable context
Workflow automation
Model evaluation
Human review loops
Provenance and auditability
Operational handoff
How we work
Clear constraints, fast loops, and close contact with real use. Build narrowly, validate the workflow, and leave behind software that can be maintained.
Build the thing
Make real product surfaces, test them with real constraints, and let the work show what matters.
Learn from use
Pay attention to where AI helps, where it fails, and how people change their behavior around it.
Keep what holds up
Turn repeated patterns into clearer product architecture, reusable tools, and better judgment for the next build.
AI projects
Some projects become products. Some become reference architecture. Some become private tools or collaborations. The point is to build close enough to the technology to learn from it.
Good projects have users, workflows, data, feedback, and a reason to improve over time.
Selected collaborations make sense when the work is concrete, the workflow is real, and the learning will matter beyond the first build.
Products built around AI
Existing product modernization
Durable context and memory
Evaluation and model behavior
Internal AI tools
Selected collaborations
About Gabe
Main Character is founder-led by Gabe Mays: a place to build AI products, learn from the work, and collaborate when there is a concrete project worth building.
Before Main Character, Gabe led product teams at GoDaddy and built products across SaaS, automation, developer tools, and AI systems. Before tech, he served as a Marine Corps Captain with deployments to Iraq and Afghanistan.
The lab also informs Gabe's own AI investing and conversations with founders, operators, and investors. The common thread is firsthand product signal from building with the technology.
Talk shop
Have a concrete AI problem worth building around?
Send the product, workflow, or modernization problem with enough context for Gabe to tell whether there is a serious build.
Good fit
AI products, modernization, workflow software, evaluation, durable context, and selected collaborations with clear constraints.
What happens next
Gabe will review and follow up directly when there is a concrete project to discuss.