Built
Proof, not promises.
A studio is only as good as what it ships. Here is what I have built and run, from products to AI agents. The advisory work draws on all of it.
Product
ShippedGoals App
- Problem
- Personal goals scatter across notes and apps, so progress is hard to see and easy to drop.
- What I built
- A focused goal-tracking app, designed and built end to end, live on its own subdomain.
- Outcome
- Shipped and running in production.
- Twelve goals across four categories, three per category, by deliberate constraint
- Fully client-side: no accounts, no database, no backend to maintain
- Built on a pre-decided Skylark 118 design system for a 3-hour intent-to-live ship
- Export, share, pin, or set as a phone wallpaper to keep goals visible
Agent
Open sourceData Steward Agent
- Problem
- Teams sit on messy data and lack a safe, repeatable way to let an agent clean and govern it.
- What I built
- An open-source agent that profiles, cleans, and documents datasets with a human in the loop.
- Outcome
- Released as open source for other builders to run and adapt.
- Three blocking gates run inside the delivery pipeline, not a retrospective review
- Data integrity gate: quality, consistency, documentation, and business context
- Privacy and security gate: PII, GDPR and CCPA, and deletion protocols
- Change management gate: schema governance with validated rollback, public on GitHub with diagrams and templates
System
In productionClarity Engine
- Problem
- Executive decisions stall when the signal is buried under noisy inputs and competing context.
- What I built
- A decision-support system that turns scattered inputs into a clear, ranked picture to act on.
- Outcome
- Running in production as part of the advisory practice.
- Pulls scattered inputs into one structured place instead of many
- Scores and ranks items so the next action is obvious, not buried
- Produces a single act-on view rather than a static list
- Runs as part of the advisory practice for live decision-support
Agent
In productionSignal Stream
- Problem
- Marketing teams miss buyer signals because monitoring is manual and easy to let slip.
- What I built
- A market-intelligence agent that monitors public conversation, scores signal, and delivers digests.
- Outcome
- Runs a live intelligence feed into Slack on a weekly cadence; the architecture is the reference for Ronin.
- Always-on GitHub Actions pipeline, running unattended since March 2026
- Collects roughly 147 community posts per run through a residential proxy
- Scores relevance with Claude Haiku layered on keyword scoring
- Delivers daily and weekly signal digests straight into Slack
Product
BetaMarket Signal AI
- Problem
- Following a company means stitching earnings, news, and social chatter together by hand.
- What I built
- A trading-insights dashboard that assembles earnings, news, and social signal per company.
- Outcome
- In beta as a focused research surface.
- Assembles earnings, news, and social signal into one profile per company
- Scores buying signals: consecutive-quarter growth, hiring patterns, fiscal timing
- Flags expansion versus budget-freeze moments for account prioritization
- Built as a focused research surface for ABM and sales planning
Product
ShippedSkylark Client IQ
- Problem
- Sales leaders lack a single view of rep performance and which client relationships are quietly going at risk.
- What I built
- A Salesforce-integrated sales performance and client-risk platform, with custom business logic and a risk-scoring model, delivered as three role-based dashboards.
- Outcome
- Designed and shipped end to end for a client.
- Salesforce (SFDC) integration as the system of record
- Three dashboards by persona: sales rep, manager, and executive team
- Custom business logic modeled to the client's sales motion
- Client risk-scoring model that surfaces at-risk accounts early
The data-integrity and risk logic runs on the same governance backbone I open-sourced as the Data Steward Agent ↗.
About the work
- Does Linda actually build, or just advise?
- Both. Everything on this page was designed and built hands-on, from a live goals app to open-source agents and production market-intelligence systems. The advisory work is grounded in the same building, not borrowed from someone else's case studies.
- Can I use any of these?
- Some, yes. The Goals App is live and the Data Steward Agent is open source. Others are products and client systems at various stages. If one is relevant to your situation, mention it on a discovery call.
Want something like this built?
Whether it is an agent, a dashboard, or an advisory engagement to put agents to work across your team, the next step is the same: a short conversation about what would move the needle.
Book a discovery call