Engineer with nearly a decade of experience says AI can now design systems, considers switching to farming
Reddit user u/JumpAppropriate714 posted in r/ClaudeCode around October 24, 2026, saying that he is a software engineer with nearly a decade of experience and feels exhausted by the speed of AI development. He said that he used to think AI could write code but could not design systems and still needed supervision from senior engineers; he no longer says that now, because AI can design systems in many cases and performs better.
The engineer wrote that everything is changing faster than the human brain can process, that he is seriously considering farming or growing food himself for the first time, and that he believes the number of jobs that can really provide a stable income over the next 5 to 10 years may keep decreasing. He also pointed out that the significance of building websites, making games, or launching SaaS products is diminishing, and felt that people are actively building things that will make themselves obsolete.
Salesforce CEO Marc Benioff said on The Logan Bartlett Show podcast in September 2025 that the company’s customer support team has been cut from about 9,000 people to about 5,000 because “it needs fewer people.” He said that AI agents (Agentforce) now handle about half of customer conversations, with humans handling the other half. A company spokesperson confirmed that support cases decreased after deploying help.agentforce.com, that the company is no longer actively filling support engineer roles, and that some employees have been redeployed to departments such as professional services, sales, and customer success.
Updated on August 12, 2026, the Stanford Digital Economy Lab paper Canaries in the Coal Mine? showed, using ADP payroll data through June 2026, that employment for young workers aged 22 to 25 in high-AI-exposure occupations was about 19% lower than the level it would have been if it had tracked the growth of low-exposure occupations among the same age group. The gap has continued to widen since it was first recorded in August 2025, when it was about 15%. Researchers pointed out that the overall economy has not seen broad-based job displacement; the adjustment has mainly come through reduced hiring of young people rather than increased departures. Experienced workers showed no similar gap. The decline is concentrated in occupations where AI is used more for automation than for complementary tasks.
Original sources:
Title: I'm tired, boss. Publisher: u/JumpAppropriate714 (Reddit r/ClaudeCode) Publication date: 2026-10-24 URL: https://www.reddit.com/r/ClaudeCode/comments/1xebls8/im_tired_boss/ Nature of source: original post Verification status: multiple media citations and user-provided screenshots were actually read for this report, verification date 2026-10-26 Supporting content: engineer’s nearly decade of experience, shift in view on AI’s ability to design systems, consideration of farming and 5- to 10-year job outlook
Title: Salesforce CEO Marc Benioff says AI cut 4,000 customer service jobs: ‘I need less heads’ Publisher: Fortune Publication date: 2025-09-02 URL: https://fortune.com/2025/09/02/salesforce-ceo-billionaire-marc-benioff-ai-agents-jobs-layoffs-customer-service-sales/ Nature of source: media report (quoting the podcast) Verification status: relevant passages were actually read for this report, verification date 2026-10-26 Supporting content: Benioff’s statement that the support team was cut from about 9,000 to about 5,000 and that AI handles half of conversations
Title: No Widespread Displacement, but the AI Employment Gap for Young Workers Has Widened to 19% Publisher: Stanford Digital Economy Lab Publication date: 2026-08-12 URL: https://digitaleconomy.stanford.edu/news/canariesaug26/ Nature of source: research institution update Verification status: full key points were actually read for this report, verification date 2026-10-26 Supporting content: 19% lower employment in high-AI-exposure occupations for ages 22-25, mainly through reduced hiring, no broad-based overall displacement
ABAB AI Insight
This Reddit post reflects the direct impression some senior engineers have of the leap in generative AI capability: a cognitive shift from believing that system design still requires human supervision to believing that AI can now do system design better in many scenarios. That shift is consistent with Salesforce’s public disclosure of support-team reductions, with the company handing about half of support conversations to AI through Agentforce and correspondingly reducing headcount additions. The Stanford study, meanwhile, shows at the payroll-data level that the employment path of 22- to 25-year-olds in high-AI-exposure occupations has fallen behind that of lower-exposure peers by about 19%, with the main mechanism being reduced hiring rather than mass layoffs.
The study authors (Erik Brynjolfsson and others) explicitly noted that the data are currently descriptive patterns and do not by themselves prove causation; the gap remains after excluding tech companies and computer occupations and controlling for factors such as interest rates and remote work, and it is concentrated in occupations where AI is used more for automation. Experienced workers have not shown a similar gap, which contrasts with the poster’s case as someone with nearly a decade of experience who still feels pressure, suggesting that the impact may first appear as a contraction in entry-level and early-career paths rather than immediately affecting senior roles.
At the capital and business level, Salesforce, as the provider of the AI agent product Agentforce, has itself become a public case of lower support costs and workforce restructuring tied to product capability. Stanford’s data, based on a large set of U.S. payroll records covered by ADP, show that the adjustment is happening first on the hiring side, meaning the window for new entrants to gain practical experience is narrowing. If this pattern continues, the future supply of senior talent may be constrained by reduced early-stage experience accumulation, rather than being determined solely by the replacement of existing senior workers.
The poster’s view of farming as a personal coping option is an individual survival-strategy statement; the research and company cases show that AI’s visible employment impact is currently concentrated in specific age and occupational exposure dimensions and is transmitted through hiring mechanisms. The key indicators to watch in future changes are hiring counts for young workers in high-exposure occupations and whether firms continue to increase the share of tasks automated, rather than overall unemployment or the layoff numbers of a single company.
ABAB News · Cognitive Law
When AI capability jumps, system design shifts from “must be supervised by humans” to “can be handled by models in many scenarios,” and the path of experience accumulation shrinks accordingly.
When employment adjustments happen first on the hiring side rather than the departure side, reduced entry opportunities show up earlier than cuts to existing positions.
When young workers in high-exposure occupations lag behind relatively in employment paths while experienced groups show no similar gap, it indicates an age and task-automation gradient in the impact.