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What Decides Whether a Coding Session Succeeds? Anthropic's New Study Says Domain Expertise, Not Coding Background.

Published: June 17, 2026

So what decides whether a coding session succeeds? Anthropic just put out a study. Turns out it is not your coding background.. that is becoming less relevant. It is domain expertise. The more you understand the problem you are solving, the more the agent does per instruction, and the more often the session ends in success.

Matches my experience.. 25-odd years as an analyst ....SAS, Python...from analysis to ML models...on the coding itself these agents beat me by multiples. Where I still win is the deep domain side.. greatly satisfying catching Claude when it makes a mistake while confidently telling me it validated everything.

I pulled some main findings, quoted straight from the report, into the attached carousel.

Full Anthropic report here:
https://www.anthropic.com/research/claude-code-expertise

Anthropic Claude Code Expertise Study - 9-Slide Summary

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More on how I build and work with these agents.. over at tigzig.com. It's an AI-agent first site - so you can just point your Claude Cowork, Claude Code, or any AI agent at it and have it explore for you. Or feel free to explore yourself.

Full Deck Content (Text Format)

Text below was extracted from the source HTML the PDF was rendered from. The 9 slide images above are the visual.

Download the PDF deck Read the Anthropic report View the markdown

Slide 1 - The three biggest takeaways

Anthropic's new study · Claude Code · the three biggest takeaways

  • Coding backgrounds are less relevant.
  • Management occupations show the highest success.
  • More domain expertise, more success.

Based on Anthropic's analysis of about 400,000 Claude Code sessions from 235,000 people, October 2025 to April 2026. Findings quoted in full inside.

Slide 2 - Coding background is becoming less relevant

"Every major occupation succeeds at rates within a few points of those in software-related occupations."

Software engineers verified at 34%. Lawyers, analysts, scientists, marketers, sales: every one of the ten largest groups lands within seven points.

Slide 3 - Management occupations come out highest

"Management occupations are highest on verified success, slightly above the software engineering occupations."

Anthropic's own read: their higher success "may reflect management skills that transfer to directing an agent." With a caveat, that it "may also partly reflect our measurement," since managers may be quicker to confirm when they got what they asked for.

Slide 4 - More expertise, more work per instruction

"The greater domain expertise a person brings to a session, the more work Claude does per instruction."

Same tool, different driver. Anthropic measured how much Claude does off a single prompt, by the user's rated expertise at the task.

More than twice the actions and five times the output from the same instruction. Expertise here is task-specific, not job title.

Slide 5 - And more often the session ends in success

"The more domain expertise a person has, the more often the session ends in success."

Verified success more than doubles, 15% to 33%. Most of the jump comes early, moving from novice to intermediate.

Slide 6 - When trouble hits, expertise pulls the session back

When a session hits trouble, expertise is what pulls it back.

"19% of sessions where the user appears to be a novice end abandoned, against 5 to 7% for everyone else."

Slide 7 - The mix is shifting from fixing to building

"The share of sessions spent fixing broken code fell from 33% to 19%."

+27% — value of the average task, versus a freelance-market benchmark.

The mix is shifting from fixing toward building, running, analyzing and writing, and the typical task is worth more.

Slide 8 - The honest caveat from Anthropic

"We cannot measure real-world outcomes... whether code written in a session is actually used or discarded." Nor whether a session "produces an economically valuable artifact." Every label comes from a model reading the transcript, and "classifiers remain challenging to validate at scale."

Slide 9 - Where I build & write · Source & method

Where I build & write

Live macro data, database AI, quants and MCP servers, plus 45 live apps, 200+ build guides and a security checklist for tool builders: tigzig.com.

Agent-first portal. Point Claude Cowork, Claude Code, or any AI agent at tigzig.com: it finds the right tool, guide or dataset, hits the APIs to pull and analyze the data, and sets up the open-source tools and MCP servers for you.

Source & method

The report: Agentic coding and persistent returns to expertise. Zoe Hitzig, Maxim Massenkoff, Eva Lyubich, Ryan Heller, Peter McCrory. Anthropic, 16 June 2026. anthropic.com/research/claude-code-expertise

A privacy-preserving analysis of about 400,000 interactive Claude Code sessions from about 235,000 people, Oct 2025 to Apr 2026, classified by a model reading each transcript and cross-checked against automatic telemetry.

What I did here

Every headline is a direct quotation. All charts were rebuilt from Anthropic's figures (3 to 6) in this house style; all data is Anthropic's.