EXPOSED
Writing functions, unit tests, boilerplate CRUD endpoints, and translating a ticket into a pull request are exactly what coding models do well now, and that is a large share of the median developer's week. What persists is deciding what to build under vague requirements, owning a production system at 3am, negotiating tradeoffs across teams, and being the person accountable when a design choice costs money or leaks data. The occupation splits: the junior implementation tier compresses hard, the systems-and-accountability tier holds, and no license protects either side.
Headcount grew steadily across the period.
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.
BLS projection, 2024–2034
+15.8% 1,693,800 → 1,961,400 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +15.8% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~115,200 openings a year on average, including replacing people who leave.
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Holding it up: judgment & accountability . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier An 11 reflects the split week: ticket-to-PR work, test scaffolding, API glue, and framework migrations are now draftable in minutes, but the parts that eat the other half of your time — reproducing an intermittent race condition in a distributed system, reading a decade of undocumented business logic to figure out why the invoice total is off by a cent, and deciding which of four broken proposals to ship before quarter-end — still need someone holding the whole system in their head.
Fully desk- and screen-based A 3 rather than 0 because on-prem deploys, hardware-in-the-loop debugging, and embedded or firmware work put some developers next to physical devices, but the median job is a laptop, an IDE, and a Slack window from anywhere with WiFi.
No licence, no signature requirement A 3 is where no-licence sits: there is no PE stamp for most software in the US, no bar admission, no statutory sign-off, and CI/CD means a broken commit gets reverted rather than litigated — the employer's EULA disclaims warranty and the company, not you, absorbs the outage.
Exists to be accountable for ambiguous calls A 15 is earned by the calls with no runbook — approving a schema migration on a live table, choosing to log or not log a field that turns out to be PII, deciding at 3am whether to roll back or forward, and setting an architecture that either scales or gets rewritten in two years — decisions where you are named in the postmortem and the cost is measured in revenue or breached records.
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 (11/20 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 (3/20) is whether the law requires a licensed human to sign. Trust premium (9/20) is whether buyers specifically pay for a person. Judgment and accountability (15/20) 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 27 of this occupation's 41 points (66%).
Embodiment (3/20) 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.
No occupation passed every test: close enough to software developers on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
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 55/100, still EXPOSED.
Task-mix shift is real here: as ticket-to-PR work is automated, the residual job becomes architecture, incident forensics, cross-service migration under legacy constraints, and reviewing/verifying machine-written diffs at scale. If the median role effectively becomes review-and-integrate of AI output plus system design, measured resistance of the remaining day rises even with no new capability limit — visible already in the collapse of junior openings versus stable senior/staff demand.
Formalized on-call and postmortem accountability tied to regulatory incident reporting — SEC Item 1.05 cybersecurity material-incident disclosure within four business days, and EU NIS2 24-hour reporting — makes the engineer who owns the system the person whose call is documented in a filing. If firms respond by naming system owners of record for critical services, the ambiguity-ownership component hardens.
Sector-specific attestation regimes that name an individual engineer: the EU Cyber Resilience Act (obligations phasing to 2027) plus CISA's Secure Software Development Attestation Form, which requires a named company officer to attest to SSDF practices for software sold to the US federal government. If attestation devolves to a named responsible engineer with personal exposure — or if a licensure scheme like the (currently withdrawn in most states) PE Software Engineering exam is revived for safety-critical systems such as medical device firmware, avionics, or voting systems — a signature requirement appears where none exists.
FDA Software as a Medical Device and DO-178C/FAA airworthiness pathways already require named individuals to sign verification records for a narrow slice of developers. If FDA guidance on AI-enabled device software function requires human-identified authorship and sign-off on model-generated code changes in premarket submissions, that slice widens.
Narrow route only: procurement and insurance language demanding provenance. Cyber insurers and enterprise vendor questionnaires increasingly ask whether AI-generated code entered the codebase, and some contracts (and license-contamination fears after the GitHub Copilot litigation) require warranty that code is human-authored or human-reviewed with named reviewers. That is willingness to pay for human authorship, but it is contractual rather than consumer taste, and it caps low.
The limit. No realistic route to a broad consumer trust premium — buyers of software want the artifact, not a human's hand in it, and no client asks who typed the function. Embodiment has no route. Even with attestation regimes, licensure would cover a small safety-critical minority; the bulk of the occupation remains unshielded, and the compressing junior tier gains nothing from any of these levers.
| New York-Newark-Jersey City, NY-NJ | 121,000 | $166,830 +23% |
| Seattle-Tacoma-Bellevue, WA | 92,770 | $167,280 +23% |
| San Jose-Sunnyvale-Santa Clara, CA | 87,350 | $213,110 +57% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 69,060 | $154,930 +14% |
| San Francisco-Oakland-Fremont, CA | 69,030 | $186,640 +37% |
| Dallas-Fort Worth-Arlington, TX | 67,030 | $133,290 -2% |
| Los Angeles-Long Beach-Anaheim, CA | 55,540 | $160,920 +18% |
| Boston-Cambridge-Newton, MA-NH | 42,310 | $166,090 +22% |
| San Jose-Sunnyvale-Santa Clara, CA | 87,350 | $213,110 +57% |
| San Francisco-Oakland-Fremont, CA | 69,030 | $186,640 +37% |
| Seattle-Tacoma-Bellevue, WA | 92,770 | $167,280 +23% |
Meta · Oracle · Amazon · Block · Monday.com · DeepL · Salesforce · National University of Singapore · Rapid7 · Microsoft · Visa · Electronic Arts · Life360 · Mews · City of Charlotte, North Carolina · Take-Two Interactive · UBS · Magnific · Maya · Globant · Coinbase · PwC · Cisco; Block · Meta, Microsoft · Snap · IBM France · HP
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