• An Anthropic manager says Claude has made traditional coding interviews a poor hiring signal.
• His advice to juniors: target business problems and build a focused prototype over a weekend.
• Google and Amazon are also reshaping engineering work and hiring around AI fluency and impact.

Out with the coding test, in with Claude.

That's the shift Felix Rieseberg, an Anthropic engineering manager, says he has made to his team's hiring process, arguing that AI has rendered traditional coding interviews a poor measure of who will succeed at work.

"The coding interview is dead, at least for my team at Anthropic," Rieseberg wrote in a Tuesday post on X. "I've seen enough to know that it no longer provides signal."

Rieseberg elaborated in a blog post, writing that there's "no point" in giving candidates coding challenges or asking them about programming languages like assembly.

"Claude is now better at both," he said of the company's own AI model.

Coding challenges were once a "weak but useful" predictor of success, Rieseberg said, but the most impactful builders on his teams are not necessarily the people who excel at such tests.

"I'm seeing engineers who are comparatively new fly past people who are probably better coders and have been around much longer," he wrote. "Hunger beats tenure."

AI is writing most of the code at Anthropic, and the shift tracks with changes underway at other Big Tech companies. Business Insider's Hugh Langley reported last week that Google is expanding pilots for software-engineering interviews that allow candidates to use Gemini to assess their AI fluency and prompting skills.

Amazon, meanwhile, told engineers on Tuesday to prioritize customer and business outcomes over raw AI usage. The company calls the moment the era of the "Renaissance Developer," in which human judgment and machine intelligence combine to build products faster.

How junior engineers can stand out

The rise of AI coding tools has fueled fears that junior developer roles will become harder to get, as AI takes on work like debugging and building simple features — tasks that once helped early-career engineers learn the ropes.

In his blog, Rieseberg shared advice for junior engineers — or, more broadly, people without organizational status or power. Rather than just clearing backlog tickets, he said they should identify the business problems their company is trying to solve.

Then, they should come up with a bold idea that could materially advance those goals and build a working prototype over a weekend. The project should communicate one compelling idea, he said, rather than bury several good ones inside an overly ambitious product.

Newer engineers should also lean into their outsider perspective. They may be more likely to spot broken user experiences or question ingrained assumptions about what is possible, Rieseberg said.

He pointed to two relatively new Anthropic engineers who built a graphical interface for Claude Code over a weekend; the first public version shipped around eight days later.

Rieseberg said he has not yet solved the problem of how to assess candidates who build effectively with AI.

For now, he said he is scanning resumes and portfolios for small prototypes that show "taste, empathy, and principled thinking" — qualities that AI researchers and tech leaders are increasingly putting a premium on in the age of AI.

• A startup founder said that leaner teams may not be the right approach for every company in the AI era.
• Chatbase CEO Yasser Elsaid said he plans to double his 40-person team within six months.
• AI models are "extremely smart and capable, but not fully independent," he told Business Insider.

As some companies race to use AI to shrink their teams, one startup founder is going against the grain by planning to hire more people.

Yasser Elsaid, the founder of customer-service AI startup Chatbase, said the company now has 40 employees and plans to double its team over the next six months.

"I might have been wrong about building with a lean team in the age of AI," Elsaid wrote in a post on X this month.

Elsaid previously embraced smaller teams. In a LinkedIn post in January, he said Chatbase, a San Francisco-based startup that lets companies build AI agents for customer service and support, had stayed at 17 full-time employees for much of its first three years, with most hires in engineering.

However, in comments sent to Business Insider, Elsaid said that he now considers his bet on lean teams "pretty wrong."

"I think it's a big mistake for founders to live in a future that doesn't exist yet," he said.

Elsaid said that more capable coding models, including Anthropic's latest Claude model Opus 5.5, initially made him think Chatbase could get by with fewer people.

But Elsaid said that this conclusion only holds if a startup keeps the same roadmap it had before AI. Rather than accept that code had become a commodity, he decided Chatbase should set its sights higher.

"If building is easier, build harder things," he said. "Most moats in software come from someone doing something hard for longer, and being right. That hasn't gone away."

'Not fully independent'

That view runs counter to a broader push toward AI-powered lean teams.

Block cut nearly half its workforce in February, with CEO Jack Dorsey saying AI and "smaller and flatter teams" were changing how companies are built.

Coinbase, meanwhile, cut 14% of staff in May, citing engineers' ability to ship in days what once took teams weeks; it is now testing smaller AI-native pods and "one person teams."

The same logic has powered the "tiny teams" startup trend: OpenAI CEO Sam Altman has predicted a one-person billion-dollar company, while Cursor grew from $1 million to $100 million in annual recurring revenue in under a year with fewer than 50 employees, according to private market research platform Sacra.

But Elsaid said the best models are not yet independent enough to replace people. They still need humans to decide what to build, give them direction, and make sure the result works for customers, he said.

"Code is largely right or wrong: it does what you want or it doesn't," Elsaid said. "But what to build, how it should work and what the experience should feel like is what makes your product different."

He estimated that about 90% of Chatbase engineers' work is now product work: researching, talking to customers, forming an opinion, and turning that into a specification an agent can code.

The rest requires engineers who can understand the code and make sure different AI agents are not working against each other, he said.

Chatbase is also hiring customer-facing staff, particularly in sales and customer success, he said, because enterprise customers still need to be heard and persuaded.

The models are "extremely smart and capable, but not fully independent," he added. "Maybe that changes and one day you won't need humans in the building process at all. But that isn't today."