Platform teams crack under AI load 🏗️, Microsoft burns its Claude Code budget 🔥, Curbside Consults 🗣️
Your Integration Team Is the New Bottleneck — And Healthcare Has the Worst One
An AI agent took down a production Kafka cluster at a major company last week.
Not a hypothetical. A real autonomous agent, a real message queue, a real outage.
The agent had credentials. It had been delegated infrastructure tasks. It did what agents do — it acted. Nobody on the platform team had reviewed the scope.
This is the story of every health system’s next 24 months, compressed into a single incident.
An interview with Emma, OpenAI’s data infrastructure lead, puts it bluntly: the platform team is where AI-accelerated development goes to wait.
😤 “This is just a staffing problem. Hire more platform engineers.” Good luck. The same AI tools creating the app-side acceleration are eating the talent pipeline for infra roles. And health systems compete for platform engineers against every FAANG company in the country.
😤 “Agents shouldn’t have infrastructure access.” You’re right. And yet.
Microsoft Burns Its Entire AI Budget on Claude Code — Then Kills It
Microsoft gave thousands of engineers Claude Code licenses in December. By May, the token-based billing had consumed the Experiences & Devices division’s entire annual AI budget.
Licenses revoked by June 30 — the last day of Microsoft’s fiscal year.
This is the Doximity AI-COGS story from the enterprise side. Free-tier clinical AI absorbs inference cost now, hopes to monetize later. Microsoft’s own engineers proved the model breaks at scale — when thousands of power users hit an uncapped token API, budgets evaporate.
😤 “They’re just pushing Copilot CLI. It’s politics, not economics.” Sure, but the budget number is real. The token bill was real. Every health system CIO evaluating ambient scribe contracts should ask: “What happens to my pricing when my docs use this 10x more than your pilot projected?”
💡 80/20: Before signing any AI vendor contract, ask for a per-provider token-usage cap model. If they can’t show you what the bill looks like at 3x projected utilization, you’re buying Doximity’s margin problem.
Claude Mythos Finds Thousands of Zero-Days — Healthcare Should Care
Anthropic’s Claude Mythos Preview autonomously discovered and exploited thousands of zero-day vulnerabilities across every major OS and browser. One was a 17-year-old RCE in FreeBSD.
83% first-attempt exploit success rate. Project Glasswing put it in the hands of AWS, Apple, Microsoft, CrowdStrike, and 7 other partners. In one month, they found 10,000+ high/critical vulnerabilities.
Healthcare is the #1 target for ransomware. An AI that finds vulnerabilities at this speed is either the best defense tool a health system CISO has ever seen — or the scariest offensive capability an attacker has ever held.
MCP Goes Stateless — The Biggest Protocol Revision Since Launch
Anthropic’s Model Context Protocol is getting its largest revision since launch: a stateless core that runs on ordinary HTTP infrastructure.
Current MCP servers maintain session state, which kills horizontal scaling behind load balancers. The 2026-07-28 release candidate fixes this with standardized session creation, resumption, and migration — plus MCP Apps (server-rendered UIs) and a Tasks extension for long-running work.
For healthcare builders, this matters. MCP is how AI models discover and use external tools — including FHIR servers, EHR APIs, and clinical decision support services. Stateless MCP means you can deploy MCP servers the same way you deploy any microservice. No sticky sessions. No single-instance bottleneck.
$24 Billion in Curbside Consults Go Unbilled Every Year
CPT codes 99446-99452 have existed since 2014. They pay $36-144 per interprofessional telephone/EHR consultation. Actual billed volume per CMS Part B claims: ~$35-50M annually.
That’s ~99.8% under-utilization. About $24B left on the table.
The money isn’t lost to cultural devaluation. It’s lost to CPT-code ignorance. The first vendor to build an EHR-integrated curbside-to-99447 billing workflow — detect the consultation event, generate CMS-required documentation, capture verbal consent, surface the appropriate CPT code, route to revenue cycle — captures a TAM no current competitor is positioned for.
💡 80/20: If you’re a clinician-builder looking for a real problem with real money: the curbside consult billing workflow. ~10 curbsides per physician per week, ~$50 average, ~1M US physicians. Do the math.
DeepSeek Targets $10B Valuation with Open-Source AGI Bet
Founder Liang Wenfeng is raising ~70B yuan ($10B) in DeepSeek’s first outside funding round — a record for a Chinese startup’s debut financing. State-backed funds, Tencent, and IDG Capital in the mix.
The commitment to open-source matters for healthcare. DeepSeek’s models are already widely used in clinical AI research. Continued investment means more capable, free foundation models for health IT — and continued pressure on closed-model pricing from OpenAI and Anthropic.
Health Samurai Ships Termbox — A Free FHIR Terminology Server
Termbox ranked #1 in the FHIR TX Benchmark, up to 30x faster than competitors on complex operations. Preloaded with SNOMED CT, LOINC, RxNorm, ICD-10, CPT, and UCUM. Free developer version runs locally.
🎙️ Lenny’s Podcast — “The AI Paradox” (Dan Shipper)
Dan Shipper runs Every, a ~30-person company where every employee uses Claude Code and Cowork daily. His prediction: companies will converge on one super-agent per organization because unattended agents degrade. The successful deployments have a named human responsible for the agent’s output quality. Name names.
What are you building this week? Reply and tell me — I read every one.
— Kevin