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Yes, getting a first software developer job may be harder than it was for many of today’s senior developers—but the evidence does not show that software development is disappearing. Recent U.S. studies find pressure on early-career hiring and a relative decline in junior developer vacancies, while the Bureau of Labor Statistics still projects growth in software developer employment overall. For a CS student, the practical response is to build strong engineering fundamentals, demonstrate work you can explain and maintain, and seek roles that provide real experience and feedback. No study cited here establishes what autonomous coding agents will do to entry-level hiring specifically.
What has changed about the first step into software work?
The clearest recent evidence points to a more difficult entry-level market, not to the end of the profession. The measures matter: one study tracks early-career workers across industries, another tracks software vacancies by seniority, and occupational projections count all experience levels together. They answer different questions.
Early-career employment has come under pressure in highly AI-exposed industries
A U.S. Census Bureau working paper using matched employer-employee data reports a 12% regression-adjusted decline in employment among workers aged 22–24 in the most AI-exposed quintile of industry-state cells over the ten quarters following ChatGPT’s introduction. The paper says hiring rates largely recovered by early 2025, but from a smaller employment base. This result is not an estimate for every CS graduate, every software job, or AI exposure alone: the study covers workers across industries and discusses other labor-market trends and shocks as well. The Census Bureau’s April 2026 working paper, revised May 7, is the source for that finding.
Junior developer openings have declined relative to senior openings
Near-universe U.S. online vacancy data analyzed by Samuel Westby, Alicia Sasser Modestino, and Peiran Cheng show a 14–15% relative decline in junior versus senior software developer vacancies following ChatGPT’s release. Their June 2026 IZA discussion paper attributes rising experience requirements mainly to employers asking for more experience within the same job titles. In the junior listings that remained, wording increasingly emphasized problem solving, communication, and attention to detail rather than AI-specific skills. These findings describe vacancy patterns; they do not prove that employers never value AI fluency. Read the IZA paper.
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Long-term occupation growth does not tell you how many entry-level jobs are available
The U.S. Bureau of Labor Statistics projects 10% employment growth for software developers from 2025 to 2035. It also projects about 106,100 average annual openings across software developers, quality assurance analysts, and testers combined; many openings are expected to come from replacing workers who leave an occupation. Neither figure is a projection of junior vacancies. They describe a broader occupation group and a longer time horizon than the studies of recent hiring. The BLS Occupational Outlook Handbook was last modified August 27, 2026.
A separate Federal Reserve discussion paper finds that coder employment growth slowed sharply after ChatGPT’s introduction, while remaining positive and slower than before 2022. The authors characterize the paper as preliminary research circulated to stimulate discussion, not an official forecast or proof that AI alone caused the change. Its results are useful context for a changing labor market, not a prediction of the number of jobs available to a particular graduating class. See the March 2026 paper.
What should a CS student learn to be ready?
Start with the ability to build and reason about software, not with the assumption that a particular AI tool or agent framework is an automatic hiring advantage. The BLS says developers need a strong programming background and must keep up with tools and languages. It also identifies analytical, communication, creative, detail-oriented, and interpersonal qualities. The IZA vacancy findings point to problem solving, communication, and attention to detail in remaining junior listings.
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- Write and read code in at least one language well enough to explain control flow, data structures, errors, and design choices.
- Practice breaking an ambiguous task into requirements, smaller components, and testable outcomes.
- Learn debugging, version control, automated testing, and the basics of deployment and maintenance. These are sound ways to show end-to-end engineering ability; the cited studies do not establish them as a guaranteed hiring checklist.
- Strengthen communication by explaining trade-offs, documenting decisions, and asking precise questions when requirements are unclear.
Use AI assistance without outsourcing your judgment
It is prudent to learn how to inspect and verify AI-generated code: check assumptions, test edge cases, look for security or reliability problems, and be able to explain what you accept or change. That is practical preparation for work in which AI tools may be present, not a skill the vacancy study identified as a universal junior-job requirement. The available studies examine outcomes around ChatGPT or generative-AI exposure; they do not isolate autonomous coding agents or show that one agent product, model, or framework is required for a first job.
How can you show employers what you can do?
Make one project legible from problem to maintenance
A polished, understandable project can give you a concrete way to discuss engineering decisions. Choose a problem with a real user or clear use case. In a repository and short project description, show how you gathered requirements, made trade-offs, wrote and tested the code, debugged failures, deployed it if appropriate, and handled a change or bug afterward. If you used AI tools, explain where they helped and how you verified their output. This is practical advice inferred from the skills employers and vacancy descriptions emphasize; it is not evidence that a portfolio guarantees an interview or offer.
Look for experience that includes feedback and delivery
Internships, team projects, apprenticeships where available, and adjacent technical roles can each be worth investigating. The sources do not rank these routes or establish that any one is universally necessary. When comparing an opportunity, ask how much coding and debugging it involves, whether you will receive code review or mentorship, whether you will see testing, deployment, and maintenance, and whether the work gives you credible experience to discuss in later applications.
| Route to investigate | Questions to ask before choosing |
|---|---|
| Junior software developer role | Will you work on production code, receive review, and learn how a team tests and maintains software? |
| QA or testing role | Will you gain experience with test design, automation, debugging, or collaboration with developers? The BLS groups QA analysts and testers with developers for its openings projection, but that projection does not describe the programming content of a particular job. |
| Internship, apprenticeship, or team project | Will you contribute to a real deliverable, get feedback, and be able to explain your individual work? Availability and program structure vary by employer and location. |
| Adjacent technical role | Does the work build relevant software-delivery experience, such as troubleshooting, scripting, testing, or working with development teams? |
Also check the conditions that can determine whether an option is viable: location, work authorization, eligibility rules, pay, schedule, and whether the role’s actual duties match its title. A job label alone does not establish how much coding, mentorship, or software delivery experience it offers.
How should you read the outlook where you live?
The strongest quantitative evidence above is U.S.-specific. If you are considering the UK, a separate 2026 Department for Science, Innovation and Technology survey reports that 97% of surveyed UK AI-sector respondents identified at least one skills gap, 35% of organizations had difficulty filling AI roles, and 31% cited candidates lacking work experience as a recruitment barrier. The same executive summary says 88% of organizations use on-the-job training rather than structured education or training programmes, 13% of graduate schemes include AI training, and 57% of respondents plan to adopt agentic AI within three years. These are survey findings about the UK AI sector, not all UK software jobs or U.S. hiring; planned adoption is not evidence that adoption has happened. Read the UK government survey executive summary, published January 28, 2026.
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For any location, treat projections, vacancy data, and a specific employer’s requirements as different kinds of evidence. Check current postings in the places where you can work, note recurring requirements, and compare those requirements with your coursework and experience. Neither broad occupational growth nor one study’s hiring decline can tell you exactly how many entry-level openings will be available to you.
What this means for your first-job plan
Prepare for a first role that may ask you to demonstrate more readiness than a traditional “learn everything on the job” junior position: sound programming, careful problem solving, clear communication, and the ability to work with others. Build evidence of those abilities, seek meaningful feedback and delivery experience, and learn to use AI output critically. That plan addresses the hiring signals the studies actually measure without assuming that AI agents have already settled the future of entry-level software work.
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