Industrial production index
Total US industrial output, 2017 = 100. The broadest read on whether plants are busier.
vs. a year ago
ARMKU Pulse
Manufacturing output, software spend, the AI build-out and the grid behind it. Pulled automatically from public, primary sources and refreshed daily. Once a month we write up what it means for a mid-sized operator.
Monthly brief · 2026-09
Factories took in strong new orders this month, but they're running plants a little less hard than before. Meanwhile the money pouring into AI infrastructure is still accelerating, not leveling off. If you run a mid-sized operation, the gap between demand looking fine and capex looking insane is the thing to watch this month.
Manufacturers' new orders hit $664B in July, up 9.9% from a year ago and up from $658B the month before. That's a real demand signal. But capacity utilization slipped to 75.7% from 76.0%, and the manufacturing output index eased to 99.1 from 99.4. Plants have work on the books but aren't pushing output harder yet. The sharpest flag is manufacturing construction spending, down 21.2% from a year ago to $170B/yr. New plant and expansion spending is cooling even as orders climb.
Business investment in software climbed to $809B/yr, up 8.7% from a year ago. The big platform vendors are showing it too: Microsoft revenue up 17.8% for the fiscal year, ServiceNow up 20.9%, Oracle up 17.4%, Workday up 13.1%, Salesforce up 9.6%. But custom programming services jobs actually dipped, 2,363k against 2,364k the month before, down 1.3% from a year ago. Companies are spending more on software and getting it built with fewer custom-dev heads. Open-source ERP activity, the GitHub stars for Odoo, ERPNext, and Dolibarr, stayed essentially flat month over month.
Notable AI model releases hit 107 for the year, up from 98, a 9.2% increase. The number that matters more is capital spending: Oracle's capex is up 162.4% from a year ago, Meta up 87.1%, Microsoft up 79.6%, Alphabet up 74.1%, Amazon up 58.8%. Five of the biggest companies in the world are pouring unprecedented money into AI infrastructure. On the tooling side, agent framework GitHub stars, LangChain, CrewAI, AutoGen, OpenAI Agents SDK, grew only slightly month to month. The infrastructure build is way ahead of visible developer adoption of agent frameworks.
Electric power generation rose to 125.5, up 6.9% from a year ago. Utilities output climbed to 113.0, up 6.2%. Both are accelerating, which tracks with the AI capex numbers above.
Is the factory floor actually busier? Output, utilization, orders, jobs and the money going into new plants.
Total US industrial output, 2017 = 100. The broadest read on whether plants are busier.
vs. a year ago
Manufacturing only, 2017 = 100. Strips out mining and utilities.
vs. a year ago
Share of manufacturing capacity in use. Above 80% plants are stretched; below 75% they have slack.
vs. a year ago
People employed in US manufacturing, thousands, seasonally adjusted.
vs. a year ago
Value of new orders received by US manufacturers each month, billions of dollars.
vs. a year ago
Money going into new factories, billions of dollars at an annual rate. The reshoring boom in one line.
vs. a year ago
Where the software dollars go: business investment in software, programming jobs, the revenue of the SaaS bellwethers, and the pull of open-source ERP.
US private fixed investment in software, billions of dollars at an annual rate. Quarterly.
vs. a year ago
Employment in US custom computer programming services, thousands. A proxy for implementation and integration work.
vs. a year ago
Annual revenue from 10-K filings, billions of dollars.
vs. a year ago
Annual revenue from 10-K filings, billions of dollars.
vs. a year ago
Annual revenue from 10-K filings, billions of dollars.
vs. a year ago
Annual revenue from 10-K filings, billions of dollars.
vs. a year ago
Annual revenue from 10-K filings, billions of dollars.
vs. a year ago
Stars on the odoo/odoo repository. Developer attention to open-source ERP, not market share.
since we started tracking
Stars on the frappe/erpnext repository. Developer attention to open-source ERP, not market share.
since we started tracking
Stars on the Dolibarr/dolibarr repository. Developer attention to open-source ERP, not market share.
since we started tracking
How fast the AI wave is really moving: notable models per year, the capital the hyperscalers are spending, and developer adoption of agent frameworks.
Models in Epoch AI's notable models database, by publication year, through the last complete year.
vs. a year ago
Payments for property, plant and equipment from 10-K filings, billions of dollars. Mostly data centers now, but not only.
vs. a year ago
Payments for property, plant and equipment from 10-K filings, billions of dollars. Mostly data centers now, but not only.
vs. a year ago
Payments for property, plant and equipment from 10-K filings, billions of dollars. Includes warehouses as well as data centers.
vs. a year ago
Payments for property, plant and equipment from 10-K filings, billions of dollars. Mostly data centers now, but not only.
vs. a year ago
Payments for property, plant and equipment from 10-K filings, billions of dollars. Mostly data centers now, but not only.
vs. a year ago
Stars on langchain-ai/langchain. Developer adoption proxy for agent frameworks.
since we started tracking
Stars on crewAIInc/crewAI. Developer adoption proxy for multi-agent frameworks.
since we started tracking
Stars on microsoft/autogen. Developer adoption proxy for multi-agent frameworks.
since we started tracking
Stars on openai/openai-agents-python. Developer adoption proxy for agent tooling.
since we started tracking
Whether the grid is keeping up with the compute being built.
US electric power generation, 2017 = 100, monthly. Not seasonally adjusted, so the summer peaks are real.
vs. a year ago
US electric and gas utilities output, 2017 = 100, seasonally adjusted. The underlying trend without the weather.
vs. a year ago
Every series comes straight from a primary, public source: the Federal Reserve Bank of St. Louis (FRED) for production, orders, jobs, construction and electricity; SEC EDGAR filings for company revenue and capital spending; GitHub for open-source adoption; Epoch AI for the count of notable models. Nothing is estimated by hand.
A few honest caveats. GitHub stars measure developer attention, not market share. Hyperscaler capital spending is total, not data centers alone. Company figures are fiscal years, which do not all end in December. The AI model count runs through the last complete year. When a source goes quiet, the series simply stops at its last real point.
The monthly brief is drafted by an AI assistant from this exact data, then reviewed and published by Rodolfo Kong. Raw feed: /pulse/data.json.
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