Jonathan SalmonJonathan Salmon
Data · AI · Governance

Your enterprise doesn't have an AI problem. It has a foundations problem.

The pilots stall. The dashboards multiply. Governance says no, so the business routes around it. I've spent my career fixing exactly this — building the data, AI, and governance foundations that let enterprises move fast with confidence, and killing everything that doesn't earn its place.

I'm Jonathan Salmon — Director of Enterprise Intelligence at Centene, leading a 15-person team in one of healthcare's most demanding data environments.

The problem

The pattern I keep seeing

Different companies, same three failures. If any of these sound familiar, we should talk.

Track record

Proof, not job descriptions

What I've actually owned and delivered — the kind of scope a VP remit is built on.

How I lead

Operating principles

The beliefs I actually manage by — not poster slogans.

  1. Empower strong engineers; don't micromanage.

    Hire well, set direction, clear obstacles, get out of the way. Control is the enemy of scale.

  2. Clarity is kindness.

    Say the thing — to your team, your peers, and up. Ambiguity is where careers and projects quietly die.

  3. Every artifact must earn its existence.

    Reports, dashboards, meetings, metrics: prove value or kill them. Waste compounds; so does focus.

  4. Develop people relentlessly.

    Your team's growth is your output. Mentoring isn't charity work — it's how you build an organization that outlasts you.

  5. Boldness is a practice.

    Ask earlier. Advocate louder. Manage up on purpose. Power dynamics are real; pretending they aren't is not a strategy.

  6. 80/20 everything.

    Most value concentrates at the edges; most effort bleeds into the middle. Find the vital few inputs, starve the trivial many, and treat waste as the enemy — because it is.

How this works

Three steps. No pitch deck.

A straight path from reading to conversation.

  1. See how I think.

    Read the AI Signal — five stories every morning, each with my take. You'll know within a week whether I think the way you need.

  2. Start a conversation.

    Email me directly. I read everything myself, and I make time for good conversations.

  3. Explore the fit.

    Fractional, advisory, or board conversations. A straight conversation about your problem.

The AI Signal

What I'm reading in AI

Five stories a day from a short list of sources I actually read — each with my one-line take. This is how I stay in the conversation.

Updated Friday, November 13, 2026

MIT Technology Review

Nvidia privately confirmed it could track chips to fight smuggling, even as industry publicly questioned feasibility

My take: Nvidia told Rep. Bill Foster privately that geotracking advanced AI chips to fight smuggling to China is technically possible, even as its industry group called the Chip Security Act mandates potentially infeasible in public. That gap between private capability and public position is exactly why governance cannot run on vendor assurances alone: require the mechanism, verify the location, and put it in writing.

OpenAI

Gilbert + Tobin rethinks the business of law with AI

My take: Gilbert + Tobin reached 87% active use of ChatGPT Enterprise, more than twice its normal tool adoption, by moving from safe experimentation to personal productivity to defined agentic workflows where people still approve the work. CEO Sam Nickless modeled use himself and set no usage mandate: leaders go first, governance enables rather than blocks, and the payoff is time returned to judgment, not fewer people.

Google DeepMind

Introducing Gemini 4 Hydrogen

My take: DeepMind positioned Gemini 4 Hydrogen as the fast execution engine alongside Carbon and Argon for judgment, priced at $1.50 per million input tokens, with a new Orchestrator that switches models mid task for near Carbon success at 24% less quota and 19% faster completion. That is the right enterprise pattern: do not spend frontier money on every step, route work to the cheapest model that can do it well.

Simon Willison

aws-emulator

My take: AWS shipped an official local emulator for its services, written in Rust by a swarm of agents that made 29,684 commits in three weeks, so teams can test without provisioning paid API keys. The emulator matters, but the build story matters more: agent volume is now real, and the leadership job shifts to review, verification, and knowing what should never have been built.

The Pragmatic Engineer

The Pulse: Details of incident.io’s AI spend

My take: incident.io shared rare real numbers: about $1.6 million in AI spend this year, now roughly $1,600 per engineer per month after Opus 5.5 cut costs from about $4,500, with nearly 80% of production PRs including agent generated code. The median engineer shipped only about 10% more PRs while tenured engineers shipped about 70% more, which is the 80/20 lesson in plain sight: AI amplifies people who already know the codebase, it does not replace that knowledge.

Sources I read daily: MIT Technology Review (AI), OpenAI, Google DeepMind, Simon Willison’s blog, and Ethan Mollick’s One Useful Thing. No aggregators, no hype feeds — five picks, every morning. Browse the archive →
The Signal, weekly

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Building

Independent ventures

Founder work I run outside my day job — where I stay close to the craft of shipping.

Founder · Live in production

Geodynix

U.S. market-intelligence product unifying demographic, economic, housing, and business data — sold as a Snowflake data product and a self-serve insights app.

Founder · In development

Profit Sentinel

B2B SaaS: continuous profit-leak intelligence for mid-market trade contractors, auditing the seams between their operational and financial systems.

Writing

Essays

I'm writing on AI in the enterprise, data leadership, and organizational power — publishing on Medium as part of a deliberate content practice. The AI Signal above is the daily version; the essays are the deep version.

Latest: AI Made Building Free. It Didn't Make Deciding Free. — why review, not output, is the scarce skill now.

I also keep a public reading list — the books that shaped how I think.

Contact

Let's talk.

I make time for good conversations — with data and AI leaders, founders who want an advisor, or peers working on the same hard problems. I read everything myself.

jonathan.salmon@gmail.com

Connect on LinkedIn

Résumé available on request.