Scrub through 91 years of this role's history — from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.
ENIAC and plug-board programming
FORTRAN, LISP, COBOL, ALGOL
Structured programming + UNIX + C
IBM PC + Borland Turbo Pascal
Visual Basic + RAD + Windows business apps
Agile + Scrum + XP
Agent coders — Devin, Claude Code, Aider, Copilot Workspace
Open source — Linux, Apache, Perl, MySQL
AWS S3 + EC2 — public cloud
GitHub + distributed version control
DevOps + Docker + Kubernetes
195019752000now
Drag the dot, click anywhere on the track, or use ← → arrow keys (Shift for 10-year jumps, PgUp/PgDn for 25).
2026
Known today as Software Developer
US Employment
1.65M
Approximate — the BLS OEWS May 2025 release is not yet available as of this curation. Fortune (March 2025) reports a 27.5% drop in the 12-month average of *computer programmer* (15-1251) employment since early 2023, but software-developer (15-1252) headcount remains broadly flat or modestly contracting at the same date. Treat as a placeholder anchor for the Anthropic Index projection; refresh when BLS OEWS May 2025 publishes.
Median Annual Wage
$133,080
Source: BLS-OEWS
Tool of the era · Agent coders — Devin, Claude Code, Aider, Copilot Workspace
Devin (Cognition Labs, announced March 12, 2024) was the first product pitched as a fully-autonomous software engineer — taking a ticket, writing code, running tests, and opening a PR without human-in-the-loop intermediation. Cognition raised at a $350M valuation within weeks, turned down $1B offers, and pursued deals at $2B. GitHub responded with Copilot Workspace + "agent mode" (Feb 6, 2025) and "coding agent" (May 17, 2025). Independent reviewers (Internet of Bugs) demonstrated Devin failing on real Upwork tasks, but the direction of travel was set.
By Nov 2025, "modifying software to correct errors" — debugging — was the single most common task in Claude API transcripts, accounting for 10% of all records. Computer & Mathematical occupational tasks were 46% of all 1P API traffic, up from 44% in Aug 2025. The first observational evidence that LLM substitution into developer work is happening in production at scale, not just in demos.
Beat · 2025
Employment of US computer programmers (the sibling SOC 15-1251, kept separate from software developers) falls to its lowest level since 1980 — about half the 2000 peak — with a 27.5% drop in the 12-month average since early 2023, correlating with ChatGPT's release.
Projection cone · present → 2034
What credible sources project
Scrub the slider past now to anchor each scenario on the scrubber. The spread you see below is the range of futures credible sources project for this role.
McKinsey Global Institute (2023)
→ 2030
+8%
McKinsey's July 2023 "Generative AI and the Future of Work in America" report places STEM occupations (which includes software developers) as one of the few categories where the midpoint scenario is *positive* net employment growth through 2030, even after accounting for AI substitution — typically +5% to +15% by 2030 depending on adoption pace. Productivity gains in software engineering specifically are cited at 25-30% from generative AI tooling; the net effect on demand is positive at the modeled adoption rates.
BLS Occupational Outlook 2024
→ 2034
+7%
BLS Employment Projections — industry-occupation matrix + labor productivity assumptions. The current published outlook for 15-1252 (2024-34 cycle): +7% employment growth ("Much faster than average"), 115,200 projected openings. Note: the prior cycle (BLS OOH 2023-33) projected +17% — the most recent revision is a sharp downward step that almost certainly reflects the post-2023 AI shock visible in the Computer Programmers (15-1251) series.
Frey & Osborne (2013)
→ 2033
-4%
Gaussian-process classifier on O*NET task features. F&O classified the closest-comparable pre-2018 SOC (15-1132 Software Developers, Applications) as one of the LEAST computerisable jobs in the entire 702-occupation set — conventional citation of the appendix value is ~0.042 probability of computerisation, ~24:1 against. The sibling 15-1133 (Systems Software) was higher at ~0.13, and 15-1131 (Computer Programmers) was 0.48 — the divergence has held up. Exact appendix decimals could not be re-extracted in this curation pass (Frey & Osborne PDF table layout); the 4% figure is the lower-bound Applications value.
Goldman Sachs (March 2023)
→ 2030
-29%
Goldman maps O*NET work-activity importance scores to LLM capability ratings. Their March 2023 "Potentially Large Effects of AI on Economic Growth" report identifies Computer & Mathematical occupations as having ~29% of tasks automatable by current LLM capabilities. As with Eloundou, this is share of *tasks automatable*, not jobs lost — interpret as ceiling, not floor.
Anthropic Economic Index (live observational)
→ 2026
-46%
Direct measurement of Claude API usage by task category, Jan 2026 report. Computer & Mathematical tasks = 46% of all 1P API traffic in Nov 2025, up from 44% in Aug 2025. "Modifying software to correct errors" — debugging — is 10% of all API records, the single most common task. Reported here as -46% on the cone to represent *current usage share*, not a forecast; it directly maps to "AI is doing this fraction of the work in production today" rather than a future scenario.
Eloundou et al. — "GPTs are GPTs" (2023, observational)
→ 2024
-47%
GPT-4 task-by-task labeling against O*NET task statements for 15-1252. Software developers are among the highest-exposure occupations in the set — conventional citation of β (E1 + 0.5×E2) ≈ 0.47, γ (any exposure) ≈ 0.78. Reported here as β = -47% to fit the cone display; γ would read as -78%. Note that "exposure" is *capability* not *substitution* — it is the share of tasks an LLM could do, not the share of jobs that will go away. Treat as ceiling.
Today, in this role
What's shifting in the work right now
The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.
What's changing in your day
Three parts of your work where AI is already doing real lifting — and what stays yours.
AI is taking this on
Migrate and modernize legacy codebases — refactoring deprecated patterns, upgrading dependencies, and translating between languages or frameworks — tasks where autonomous agents (Devin, Copilot Workspace) now handle most repetitive transformation work.[7],[10]
Redirect effort from mechanical refactoring to post-migration validation: define the correctness criteria, own the test harness, and perform the business-logic review that verifies the automated agent preserved intended behavior.
Prototype new features or proof-of-concepts rapidly using AI-native editors and agent tools, iterating on natural-language specifications before committing to a full implementation plan.[11],[12]
Become fluent in prompt engineering for code — writing precise, scoped natural-language specs that produce useful first drafts; treat AI-generated prototypes as spike artifacts requiring design review before production use.
AI is sitting alongside you here
Write and maintain automated test suites (unit, integration, end-to-end), delegating test-case generation to AI tools while curating edge cases that reflect real production failure modes.[6],[3]
Focus on test strategy rather than test authorship: design the test pyramid, define coverage standards, and own the decision of which failure modes matter most — AI can generate hundreds of tests but needs human guidance on what to cover.
Natural next steps for someone with your foundation — not exits, evolutions.
A direction you could grow
Computer and Information Systems Managers
The 2025-2026 labor market shows rising demand for managers who can evaluate AI tooling, set adoption strategy for agentic coding agents, and lead teams navigating AI-assisted development. Experienced developers who build management skills command the highest compensation premiums in the sector.