Tool and Die Makers
In short: today's best AI models could do about 31% 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 39% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 61% of the time, stays with people.
Analyze specifications, lay out metal stock, set up and operate machine tools, and fit and assemble parts to make and repair dies, cutting tools, jigs, fixtures, gauges, and machinists' hand tools.
56,930 people do this job in the US. $64,050 a year.
Reviewed on October 18, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work12 h
- Desk work AI can't do yet3 h
- Stays with people25 h
Tool and Die Makers, now: of a 40-hour week, AI could take on 0 hours, 12 hours become checking its work, 3 hours are desk work it can't do yet, and 25 hours stay with people.
The largest pieces: Design jigs and fixtures (about 4 h, a person checks); Plan the machining sequence (about 4 h, a person checks); Design tools and dies in CAD (about 2 h, 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.
- 35%
- 3%
- 0%
- 0%
- 61%
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 31% 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, 0%. With Claude Mythos Preview (early), measured in April 2026, 10%. Today's estimate: 31%.
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
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 17 tasks showed up. Within each of Anthropic's methods, never across a change: 0.085% to 0.012% (released February and March 2025); 0.0027% to none (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.085% | 191 of 708 | 1 of 17 |
| Released March 2025 | 0.012% | 483 of 703 | 1 of 17 |
| The week of Aug 4, 2025 (released September 2025) | 0.0027% | 602 of 655 | 1 of 17 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 17 |
| The week of Feb 5, 2026 (released March 2026) | none | n/a | 0 of 17 |
| April 2026 (released June 2026) | none | n/a | 0 of 17 |
| May 2026 (released June 2026) | none | n/a | 0 of 17 |
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 81% of this job's working time as physical work. For 59% of the working time, a robot has been shown doing most of the task somewhere: 59% in a purpose-built cell. 0.59 of 3, the 286th highest of the 923 jobs.
- Not physical 19%
- No robot shown 22%
- In a purpose-built cell 59%
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
61% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Build and repair dies and jigs, the hands-on work, 17%
- Set up and run machine tools, the hands-on work, 13%
- Polish parts, the hands-on work, 5%
- Test run tools and dies, the hands-on work, 5%
- Measure finished parts, the hands-on work, 4%
- Fit parts together, the hands-on work, 4%
What becomes checking the machine
39% 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.
- Design tools and dies in CAD, costly if wrong, 11%
- Design jigs and fixtures, costly if wrong, 11%
- Plan the machining sequence, costly if wrong, 9%
- Set up and run machine tools, costly if wrong, 3%
- Work out dimensions and tolerances, costly if wrong, 3%
- Select metals for the job, costly if wrong, 0.6%
What to learn
- The hands-on craft. About 61% 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.
- Briefing a model and checking its drafts. About 35% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
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 . 17 tasks from .
| Task | ||||
|---|---|---|---|---|
| Fit and assemble parts to make, repair, or modify dies, jigs, gauges, and tools, using machine tools, hand tools, or welders.Fitting and assembling the parts by hand and machine.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 17% | 3.3 h50 min to 1.7 work days | Hands-on 100% | Stays with people |
| Set up and operate conventional or computer numerically controlled machine tools such as lathes, milling machines, or grinders to cut, bore, grind, or otherwise shape parts to prescribed dimensions and finishes.Setting up and running the lathe, mill or grinder, with the program loaded at the control.Done several times a day by most who do it. Robots: in a purpose-built cell, Makino a61 horizontal machining center with MMC pallet automation at Precise Tool & Die (deployed). Anthropic's rating. | 16% | 2.5 h38 min to 6.7 h | Hands-on 80%, systems 20% | 18%Desk part half by now |
| Develop and design new tools and dies, using computer-aided design software.Designing the tool in the CAD system.Done more than weekly by most who do it. | 11% | 1 work day2.5 h to 4.2 work days | Documents 100% | 43%Half by Dec 2026 |
| Design jigs, fixtures, and templates for use as work aids in the fabrication of parts or products.Designing the work aids at the desk.Done more than weekly by most who do it. | 11% | 4.2 h1.7 h to 1.3 work days | Documents 100% | 93%Half by now |
| Study blueprints, sketches, models, or specifications to plan sequences of operations for fabricating tools, dies, or assemblies.Reading the drawings and planning the order of operations.Done daily by most who do it. | 9% | 1.7 h25 min to 4.2 h | Documents 100% | 97%Half by now |
| Smooth and polish flat and contoured surfaces of parts or tools, using scrapers, abrasive stones, files, emery cloths, or power grinders.Stoning and polishing the surfaces by hand and at the grinder.Done daily by most who do it. Robots: in a purpose-built cell, OB7 automated deburring and polishing cell (Productive Robotics) (sold). Anthropic's rating. | 5% | 1.7 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Conduct test runs with completed tools or dies to ensure that parts meet specifications, making adjustments as necessary.Running the die in the press and adjusting it until the parts come out right.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 2.1 h50 min to 5 h | Hands-on 100% | Stays with people |
| Verify dimensions, alignments, and clearances of finished parts for conformance to specifications, using measuring instruments such as calipers, gauge blocks, micrometers, or dial indicators.Checking the part with gauges and micrometers.Done hourly or more by most who do it. Robots: in a purpose-built cell, Mitutoyo MiSTAR robotic measurement cell (with Engineering Data automation) at Méca-Précis (deployed). Anthropic's rating. | 4% | 25 min8 min to 1.3 h | Hands-on 100% | Stays with people |
| File, grind, shim, and adjust different parts to properly fit them together.Filing, grinding and shimming until the parts fit.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 1.3 h25 min to 4.2 h | Hands-on 100% | Stays with people |
| Visualize and compute dimensions, sizes, shapes, and tolerances of assemblies, based on specifications.Computing the sizes and tolerances from the specification.Done daily by most who do it. | 3% | 38 min13 min to 1.7 h | Documents 100% | 100%Half by now |
| Set up and operate drill presses to drill and tap holes in parts for assembly.Drilling and tapping at the press.Done more than monthly by most who do it. Robots: in a purpose-built cell, ARC Specialties Robotic Drill & Tap System with Automatic Part Registration (FANUC robot, Renishaw probe, FARO CMM, Vermont Gage thread gage) (sold). Anthropic's rating. | 3% | 1.1 h25 min to 2.1 h | Hands-on 100% | Stays with people |
| Measure, mark, and scribe metal or plastic stock to lay out machining, using instruments such as protractors, micrometers, scribes, or rulers.Marking the stock with scribes and rules.Done several times a day by most who do it. Robots: in a purpose-built cell, Peddinghaus HSFDB-B CNC plate processor with SignoScript carbide scribing (sold). Anthropic's rating. | 3% | 38 min13 min to 1.7 h | 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.
- Tool Grinders, Filers, and Sharpeners6% now, 6% by 2028
- Model Makers, Metal and Plastic22% now, 22% by 2028
- Grinding and Polishing Workers, Hand11% now, 11% by 2028
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic18% now, 18% by 2028
- Forging Machine Setters, Operators, and Tenders, Metal and Plastic6% now, 6% by 2028
- Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic6% now, 6% 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 Tool and Die Makers is within reach of AI now?
- An estimated 31% of the working time is within reach of AI models now and 39% by the end of 2028, on METR's long-run pace at four in five (38% to 39% across the three paces the site shows). 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 Tool and Die Makers 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: Design jigs and fixtures (93% of the task's time now, 100% by the end of 2028); Plan the machining sequence (97% of the task's time now); and Design tools and dies in CAD (43% of the task's time now, 100% by the end of 2028).
- Which tasks of Tool and Die Makers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Build and repair dies and jigs; Polish parts; and Test run tools and dies. Together such tasks are about 48% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Tool and Die Makers 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 briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 61% of the working time stays with people, 39% becomes checking a model's work and 0% 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 Tool and Die Makers?
- 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 Tool and Die Makers?
- Anthropic's robot exposure rating (September 2026) finds 81% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 59% of the working time. Its index is 0.59 of 3. One example: Makino a61 horizontal machining center with MMC pallet automation at Precise Tool & Die for "set up and run machine tools". 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 17 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 18, 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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