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 · 2026-10
The factory floor and the data center are moving at two different speeds. Industrial production and manufacturing output both ticked up in September, but barely. Meanwhile Microsoft, Oracle, Meta, Amazon and Alphabet are pouring tens of billions more into AI infrastructure than a year ago. If you run a mid-sized operation, the gap between those two speeds is where your next decision should live.
The industrial production index hit 104.0 in September, up from 103.3 in August and up 2.2% from a year ago. Manufacturing output moved similarly, 99.4 versus 99.2, up 1.4% year over year. Capacity utilization held flat at 75.9%, barely above August's 75.8%. The number that stands out is manufacturing construction spending: 171 $B a year, down 19.1% from a year ago. Plants are running, but nobody is breaking ground on new capacity. Manufacturing jobs are flat too, at 12,652 thousand, up only 0.3% from last year.
Business investment in software rose to 831 $B a year, up from 809 $B and up 9.0% from a year ago. The big vendors are growing fast: Microsoft's fiscal-year revenue hit 331.8 $B, up 17.8%, and Oracle's hit 67.4 $B, up 17.4%. But custom programming services jobs fell to 2,355 thousand, down 1.4% from a year ago. Companies are spending more on software and employing fewer custom programmers to build it. Open source ERP is still gaining slow, steady attention, with Odoo at 55,455 GitHub stars, up 2.4% from a year ago.
Capital spending at the biggest tech companies is not slowing down. Oracle's capex hit 55.7 $B for its fiscal year, up 162.4% from a year ago. Meta's hit 69.7 $B, up 87.1%. Microsoft's hit 115.9 $B, up 79.6%. Alphabet and Amazon are up 74.1% and 58.8% respectively. Epoch AI counted 109 notable AI models released, up from 99, a 10.1% increase. But the agent frameworks that are supposed to put that spending to work, LangChain, CrewAI, AutoGen and the OpenAI Agents SDK, are only growing adoption 1.4% to 4.2% on GitHub. The money is way ahead of the tooling.
Electric power generation fell to 114.9 from 125.8 in August but is still up 9.2% from a year ago. Utilities output is up 8.7% from a year ago, at 117.3. Demand tied to data centers is showing up in the energy numbers.
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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