JetBrains vs Magic

AI Reduces Entry-Level Hiring in Software Development

A JetBrains survey of over 15,000 developers shows 90% use AI coding agents at least weekly. A Stanford study 'Canaries in the Coal Mine' reports a 20% decline in employment for software developers aged 22-25 in the US since late 2022, while experienced developers see growth. This trend worries the author, Dr. Volker Oshege, chairman of viadee, as it threatens the future talent pipeline. He argues that AI shifts bottlenecks to review capacity and guardrails, requiring human judgment. He advocates for mixed teams, buddy systems, and continuous training to ensure the workforce of 2036. The article is an opinion piece, not a news report, and contains no specific corporate announcements or financial data.

• A JetBrains survey found 90% of developers use AI coding agents at least weekly.
• A Stanford study shows a 20% employment decline for software developers aged 22-25 in the US since late 2022.
• The article is authored by Dr. Volker Oshege, chairman of viadee Unternehmensberatung AG.

A New Agentic Experience: JetBrains Air in IDEs – EAP Now Open

Last week, we shared our point of view on where we think agentic development is headed and introduced JetBrains' answer to it: JetBrains Air, an open system of products for agentic development. To…

How AGI Became a Marketing Department Case

The article discusses how AI, particularly coding agents, is transforming the role of software developers. It highlights that 90% of professional developers use such tools weekly, with 68% daily, and about a third are 'agentic coders' who generate 84% of their code via AI. This shift is changing the developer's role from generalist to specialist, and now to a 'Forward Deployed Engineer' who works closely with clients. The article emphasizes that the real value of developers is shifting from pure coding capacity to understanding business context, identifying problems, and making sound technical decisions. It draws on examples from Google Research and the hiring practices of OpenAI and Anthropic, and suggests that businesses should focus on teams that can quickly build domain context rather than just counting developers.

• 90% of professional developers use coding agents weekly, 68% daily (JetBrains survey).
• One third of developers are 'agentic coders' generating 84% of their code via AI.
• Google Research is investigating whether software agents understand standards and collaborate with developers.

Magic AI Claims Frontier-Level Pretraining for Under $1M

Magic, an AI startup co-founded by Austrians Eric Steinberger and Sebastian De Ro, claims a major breakthrough in pretraining efficiency. Its new recipe reportedly matches DeepSeek V4 Pro's base model quality using 50x less compute, costing about $500,000 on Nvidia GB200 systems, and is over ten times more compute-efficient than leading open-weight models. Scaling to roughly $4 million, Magic says it outperforms all public base models on perplexity evaluations, comparing against DeepSeek V4 Pro, Kimi K2, and Nvidia's Nemotron 3 Ultra, while excluding closed models from Anthropic, Google, and OpenAI. The company has raised over $460 million, with a $320 million round valuing it at $1.5 billion, and partners with Google Cloud for tens of thousands of GB200 chips. Magic has not yet released a model, and all claims are self-reported.

• Magic claims its pretraining recipe matches DeepSeek V4 Pro's quality with 50x less compute, costing ~$0.5M on GB200, and is 10x more efficient than leading open models.
• Scaling the recipe to ~$4M, Magic says it beats all public base models on perplexity evaluations.
• Magic has raised over $460M, with a $320M round valuing it at $1.5B, and partners with Google Cloud for GB200 compute.