COOKED
The judgment core of this job — reading grain and defects, deciding cut patterns to maximize yield, setting blade height and feed rate — is exactly what optical scanning plus optimizing saw software already does better than a human eye in modern mills. What holds is the physical side: loading and off-bearing heavy stock, clearing jams, changing and tensioning blades, and catching a machine that is drifting out of tolerance before it wrecks a run. The threat here is less 'chatbot' than capital investment: every mill that upgrades to an optimized line cuts headcount per board foot, and small custom shops are where the remaining jobs live.
Part 2020 shock, part continued decline in the years since.
Median pay $30,410 → $42,770 +12.5% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-0.6% 45,000 → 44,700 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -0.6% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~4,800 openings a year on average, including replacing people who leave.
EdgerHewerBolterCrozerLatherMillerPlanerRipperSawyerSlasherTrimmerEdgermanResawyerSplitterEqualizerJigsawyerLathmakerBolt MakerCob SawyerLog SawyerPony EdgerRip SawyerSaw RunnerTail Edger
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier An 8 reflects that the yield decisions — where to break a cant, which defect to drop out, how to nest cuts in a rough board — are already solved by scanner-plus-optimizer packages on modern gang rips and crosscut lines, while blade changes, jam clearing, and infeed handling still need someone at the machine, so it sits above the 0-6 floor without approaching mixed-work territory.
Hands-on in uncontrolled environments At 14 you are on a mill floor with airborne dust, 90+ dB, green lumber that weighs what it weighs, and stock that arrives warped and unpredictable — off-bearing, decking, and reaching into a guarded but live machine to clear a bind are the parts no arm-and-vision rig has cheaply replaced.
No licence, no signature requirement A 1 is right because nothing about running a resaw or a chop saw requires a state licence or credential — OSHA 1910.213 governs the guarding on the machine, not a certificate in your name, and the mill carries the exposure when someone is hurt.
Executes defined procedures on defined inputs A 5 fits work run off a cut list and grade rules with tolerances specified in advance — the real calls, like scrapping a run or stopping the line when the blade is wandering, are escalated to a lead or millwright rather than owned by the tender.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (8/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (1/20) is whether the law requires a licensed human to sign. Trust premium (2/20) is whether buyers specifically pay for a person. Judgment and accountability (5/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 8 of this occupation's 30 points (27%).
Embodiment (14/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 45/100 — EXPOSED.
Task-mix shift within the same job: once optimizing scanners own cut-pattern decisions, what is left is jam clearing, blade change and tensioning, saw-guide alignment, and detecting tolerance drift by sound and feel. This tier genuinely exists and is the part mills already keep staffed on optimized lines. Rises only as the routine tier is removed, and rises against a shrinking headcount base.
Narrow but real in the custom/architectural slab and instrument-tonewood segment, where buyers pay for a named sawyer's decisions about how a log is opened (quartersawn vs. flatsawn figure, bookmatching). This is a few thousand jobs at most, not the 40,850, and does not transfer to dimensional-lumber or pallet-stock mills.
Grade-stamping authority: lumber grading under ALSC-accredited agencies (WWPA, SPIB, NELMA) requires a certified grader whose stamp carries the mill's liability for building-code-compliant structural lumber. If a sawing operator in a small mill holds the grading certification — and if ALSC does not accredit camera-based automated grading for structural stamps — the operator personally owns a call that a building inspector can trace back.
Sawmill work remaining in the small/custom-shop tier is irregular-stock handling: reclaimed timber with embedded nails and unknown moisture, live-edge slabs, urban salvage logs. If reclaimed-lumber and urban-wood-salvage volume keeps growing (Urban Wood Network, growing municipal ash-removal streams), the residual work is exactly the stock an optimized automated line rejects — metal detection failures, irregular geometry, hand-fed slabbing — which is unpickable and unfeedable by current gantry automation.
OSHA machine-guarding and lockout/tagout (29 CFR 1910.147) already requires an authorized employee to perform energy isolation before blade changes and jam clearing; if an OSHA rulemaking or state plan extends this to require a named, trained authorized person to sign the LOTO permit on automated optimizing lines — as some sawmill insurers' loss-control programs already require — a designated human becomes procedurally required for every stoppage.
The limit. Every lever here is small and most apply to the shrinking custom-shop tail rather than the industrial mills where the volume of employment sits. The dominant force is capital substitution: an optimized line cuts headcount per board foot regardless of what happens to liability or grading rules. Even with all levers landing, this stays a contracting occupation — the score describes the job's character, not the number of them.
| Los Angeles-Long Beach-Anaheim, CA | 600 | $46,380 +8% |
| Portland-Vancouver-Hillsboro, OR-WA | 560 | $49,740 +16% |
| Atlanta-Sandy Springs-Roswell, GA | 550 | $39,610 -7% |
| Riverside-San Bernardino-Ontario, CA | 430 | $43,800 +2% |
| Dallas-Fort Worth-Arlington, TX | 420 | $37,620 -12% |
| Sacramento-Roseville-Folsom, CA | 420 | $47,460 +11% |
| Seattle-Tacoma-Bellevue, WA | 380 | $55,280 +29% |
| Cleveland, OH | 330 | $49,610 +16% |
| Longview-Kelso, WA | 180 | $60,100 +41% |
| Seattle-Tacoma-Bellevue, WA | 380 | $55,280 +29% |
| Santa Cruz-Watsonville, CA | 30 | $54,340 +27% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 30. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.