Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders
In short: today's best AI models could do about 13% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 87% of the time, stays with people.
Set up, operate, or tend machines, such as glass-forming machines, plodder machines, and tuber machines, to shape and form products such as glassware, food, rubber, soap, brick, tile, clay, wax, tobacco, or cosmetics.
58,770 people do this job in the US. $45,760 a year.
Reviewed on October 3, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on4 h
- A person checks AI's work1 h
- Desk work AI can't do yet0 h
- Stays with people35 h
Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders, now: of a 40-hour week, AI could take on 4 hours, 1 hours become checking its work, 0 hours are desk work it can't do yet, and 35 hours stay with people.
The largest pieces: Record production data (about 3 h); Review work orders (under an hour, a person checks); Select and install components (under an hour, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 4%
- 9%
- 0%
- 3%
- 83%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 13% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 3%. With Claude Mythos Preview (early), measured in April 2026, 13%. Today's estimate: 13%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
None of this job's 26 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 91% of this job's working time as physical work. For 89% of the working time, a robot has been shown doing most of the task somewhere: 43% in a purpose-built cell, 46% in a structured facility. 1.35 of 3, the 37th highest of the 923 jobs.
- Not physical 9%
- No robot shown 2%
- In a purpose-built cell 43%
- In a structured facility 46%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
87% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Adjust speeds and pressures, the hands-on work, 8%
- Check materials and products, the hands-on work, 8%
- Monitor machine operations, the hands-on work, 8%
- Select and install components, the hands-on work, 6%
- Disassemble equipment for repair, the hands-on work, 6%
- Clean dies and molds, the hands-on work, 5%
What becomes checking the machine
4% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 9% is desk work that is small if wrong, which can be handed over with lighter checks.
- Review work orders, costly if wrong, 2%
- Select and install components, costly if wrong, 2%
What to learn
- The hands-on craft. About 83% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 26 tasks from .
| Task | ||||
|---|---|---|---|---|
| Adjust machine components to regulate speeds, pressures, and temperatures, and amounts, dimensions, and flow of materials or ingredients.Components adjusted for speed, pressure, temperature and flow.Done daily by most who do it. Robots: in a structured facility, Sikora Centerwave 6000 / ECOCONTROL with SET POINT module (sold). Anthropic's rating. | 8% | 17 min8 min to 33 min | Hands-on 100% | Stays with people |
| Select and install machine components, such as dies, molds, and cutters, according to specifications, using hand tools and measuring devices.Dies, molds and cutters chosen to the spec and fitted with hand tools.Done daily by most who do it.Robots: in a purpose-built cell, Krones MouldXpress Robot (sold). Anthropic's rating. | 8% | 33 min13 min to 1.3 h | Hands-on 80%, documents 20% | 20%Desk part half by now |
| Record and maintain production data, such as meter readings, and quantities, types, and dimensions of materials produced.Readings, quantities and dimensions entered.Done hourly or more by most who do it. | 8% | 13 min4 min to 25 min | Systems 100% | 100%Half by now |
| Examine, measure, and weigh materials or products to verify conformance to standards, using measuring devices such as templates, micrometers, or scales.Items examined, measured and weighed with templates, micrometers and scales.Done hourly or more by most who do it. Robots: in a purpose-built cell, Mitutoyo / Engineering Data robotic measurement cell at Méca-Précis (deployed). Anthropic's rating. | 8% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Monitor machine operations and observe lights and gauges to detect malfunctions.Lights and gauges watched at the machine for malfunctions.Done hourly or more by most who do it. Robots: in a structured facility, ANYmal (D) inspection robot (ANYbotics / Vigier Ciment) (deployed). Anthropic's rating. | 8% | 13 min4 min to 38 min | Hands-on 100% | Stays with people |
| Disassemble equipment to repair it or to replace parts, such as nozzles, punches, and filters.Equipment taken apart to repair it or replace nozzles, punches and filters.Done daily by most who do it.Robots: no robot shown. Anthropic's rating. | 6% | 50 min25 min to 1.7 h | Hands-on 100% | Stays with people |
| Clean dies, arbors, compression chambers, and molds, using swabs, sponges, or air hoses.Dies, arbors, chambers and molds cleaned with swabs, sponges and air.Done daily by most who do it. Robots: in a purpose-built cell, LTF die-plate washing machine (Cristiano Torre Engineering) (sold). Anthropic's rating. | 5% | 21 min8 min to 50 min | Hands-on 100% | Stays with people |
| Clear jams, and remove defective or substandard materials or products.Jams cleared and defective product removed from the machine.Done daily by most who do it. Robots: in a purpose-built cell, ibea / AT Sensors inline brick and concrete block inspection with downstream reject robot (Kortmann Beton, Schuettorf) (deployed). Anthropic's rating. | 5% | 13 min4 min to 33 min | Hands-on 100% | Stays with people |
| Review work orders, specifications, or instructions to determine materials, ingredients, procedures, components, settings, and adjustments for extruding, forming, pressing, or compacting machines.Orders and specifications read to know the materials, settings and adjustments.Done daily by most who do it. | 5% | 13 min4 min to 21 min | Documents 50%, in person 50% | 50%Desk part half by now |
| Synchronize speeds of sections of machines when producing products involving several steps or processes.Section speeds matched through a multistep process.Done daily by most who do it. Robots: in a structured facility, Conair PipeMaster downstream extrusion line (puller/haul-off, servo cutter, tilt tables) (sold). Anthropic's rating. | 4% | 17 min8 min to 33 min | Hands-on 100% | Stays with people |
| Measure, mix, cut, shape, soften, and join materials and ingredients, such as powder, cornmeal, or rubber to prepare them for machine processing.Powder, cornmeal or rubber measured, mixed, cut, softened and joined.Done daily by most who do it.Robots: in a purpose-built cell, DosingMatic® Shuttle automatic dosing unit (Palamatic Process) (sold). Anthropic's rating. | 4% | 25 min13 min to 50 min | Hands-on 100% | Stays with people |
| Turn controls to adjust machine functions, such as regulating air pressure, creating vacuums, and adjusting coolant flow.Air pressure, vacuum and coolant flow adjusted at the controls.Done hourly or more by most who do it. Robots: in a structured facility, Bucher Emhart Glass FlexIS Cooling Control (Blank Cooling Control BCC / Plunger Cooling Control) (sold). Anthropic's rating. | 4% | 8 min3 min to 21 min | Hands-on 100% | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers5% now, 5% by 2028
- Machine Feeders and Offbearers5% now, 5% by 2028
- Cutting and Slicing Machine Setters, Operators, and Tenders7% now, 7% by 2028
- Paper Goods Machine Setters, Operators, and Tenders0% now, 0% by 2028
- Adhesive Bonding Machine Operators and Tenders9% now, 9% by 2028
- Rolling Machine Setters, Operators, and Tenders, Metal and Plastic14% now, 14% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders is within reach of AI now?
- An estimated 13% of the working time is within reach of AI models now and 13% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Record production data (100% of the task's time now); Review work orders (50% of the task's time now); and Select and install components (20% of the task's time now).
- Which tasks of Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Adjust speeds and pressures; Check materials and products; and Monitor machine operations. Together such tasks are about 76% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; reviewing work you did not do yourself; and judgment where errors are severe. By the end of 2028 on the long-run pace at four in five, about 87% of the working time stays with people, 4% becomes checking a model's work and 9% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 91% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 89% of the working time, 46% in a structured facility. Its index is 1.35 of 3. One example: Sikora Centerwave 6000 / ECOCONTROL with SET POINT module for "adjust speeds and pressures". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 26 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 3, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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