Jim Jones
I'll make an impact on your team, day one.
Twenty years of software. Bay Area clients. Roots back in Nebraska. The work I do now is exactly what I spent the last two decades getting good at — I've just stopped doing it for Silicon Valley unicorns and started doing it for mid-market companies here.
The long version
I've been shipping production software for two decades, the entire time on systems built to handle real traffic and real consequences. I know what fragile code looks like under load, and I know what hardened code looks like — and the difference between the two is the difference between an AI rollout that compounds and one that quietly dies in someone's Slack channel.
Eleven-plus years of those years were Silicon Valley consulting — engagements at Uber, PagerDuty, LegalShield, Juvo, and Lime. Organizations with complicated systems, hard constraints, and engineering cultures that didn't tolerate hand-waving. That's where I learned to get current on a codebase fast, earn the room's trust faster, and move a team from stuck to shipping without a lot of ceremony. Performance reviews at those engagements came back Exemplary. I worked for that rating because it meant I'd done what I said I'd do.
The AI work started in earnest when the tools got good enough to matter. On the Lime engagement I drove the Claude Code rollout across their engineering org — past 70% adoption, with MCP integrations wired into Jira, GitHub, Datadog, and Confluence, company-wide trainings, and ongoing mentorship for engineers learning to change how they actually work rather than just adding another tab to their browser. The same engagement also produced Lime's ML production systems — promotion-conversion and customer-churn forecasting on SageMaker, XGBoost, and Snowflake. Live in production, handling real volume, wired into real business decisions, not proof-of-concepts that never left a Jupyter notebook.
The thread that runs through all of it is the same: find the place where complexity is grinding people down, simplify it until the team can own it, and leave the codebase and the team better than you found them. That's what I do. It's not complicated to describe. It's just hard to find someone who'll actually do it.
Blue Sage is the bet that Nebraska's mid-market has been underserved by consulting firms that parachute in, charge Bay Area rates for slide decks, and leave before anything ships. I've been on the other side of that enough times to know what "done" actually looks like. I build it, I hand it off, and your team owns it.
Credentials
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Two decades shipping production software at Silicon Valley scale
Twenty years of production engineering on systems serving hundreds of millions of requests — the kind of operating environment where fragile code surfaces immediately and the gap between a demo and a real workflow is unforgiving.
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Led the Claude Code rollout across Lime's engineering org — 70%+ adoption
Built MCP integrations connecting the AI toolchain to Jira, GitHub, Datadog, and Confluence. Ran company-wide trainings on a recurring cadence and one-on-one mentorship engineer-by-engineer through their first real workflow changes. Tracked weekly adoption metrics until the curve held past 70% — the same playbook Blue Sage now runs for clients.
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Built Lime's ML production systems for promotion-conversion and customer-churn forecasting
Delivered machine-learning pipelines on SageMaker and XGBoost with Snowflake as the data layer. These were live production systems at Lime handling real volume and connected to real business decisions — not proof-of-concepts that never left a Jupyter notebook.
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11+ years of Silicon Valley consulting — Uber, PagerDuty, LegalShield, Juvo, Lime
Five engagements across firms at different scale and complexity levels. Uber's engineering bar, PagerDuty's on-call culture, and Lime's mobility-at-scale operations all demand a certain directness about what's broken and what it'll take to fix it. The Lime engagement is where the AI rollout and ML systems above were built; the others built the habits that travel into every project.
Why Nebraska
I spent years doing good work for Bay Area companies that had no shortage of engineers willing to do it. At some point it stops feeling like the highest-leverage place to be. Nebraska's mid-market — insurance agencies, regional banks, manufacturers, logistics firms — has real operational problems that AI can materially help with, and almost no one showing up to do that work seriously.
The bet is simple: companies with 50 to 500 employees in Lincoln and Omaha are making decisions about AI right now, mostly without good guidance. A firm that shows up with actual engineering depth and a track record, rather than a license to resell someone else's platform, is a different conversation than what most of them have been offered so far.
I'm not here to build a big consulting firm. I'm here to do good work for a small number of clients who need it, and make sure the change sticks after I leave.
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