Stop Paying More for "Smarter" LLMs @arizeai

Uploaded July 2026 | Updated September 2026, 2 weeks ago

Stop blindly upgrading your application's base LLM to the latest frontier models, hoping it will magically fix your accuracy issues. If your retrieval pipelines, context construction, and memory layers are throwing insufficient data into the prompt window, even a human couldn't provide the right output. All you're doing is scaling up your enterprise token costs for what we call "confident irrelevance", where an expensive model confidently answers a question you didn't even ask. Focus on your data infrastructure, not just your model weights.

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$When AI Can Write Code, What Are Software Engineers Worth? | Citadel When AI can generate code in seconds, what still makes a software engineer valuable? In this Arize:Observe session, Craig Owenby of Citadel explores how agentic coding tools are changing software engineering, and why the profession still requires far more than producing code. Craig compares large language models to the printing press. The printing press replaced the manual work of copying books, but it did not replace authors. In the same way, AI coding agents can automate the mechanics of writing code without replacing the judgment, vision, empathy, and experience required to build useful software. The session covers: • Why “coder” and “software engineer” are increasingly different roles • How tools like Claude Code, Codex, Copilot, and Cursor remove traditional barriers to building software • What the printing press teaches us about AI-assisted development • Why engineers should avoid competing with AI on raw code generation • How Sears lost its advantage by competing with e-commerce on the wrong terms • Why human experience, intuition, and empathy remain essential • How constraints can improve product and engineering decisions • Why shipping more features can increase volatility and reduce user trust • How AI acts as leverage for strong and weak engineering decisions • Why product direction and problem selection matter more as implementation gets easier The central lesson: software engineering is not primarily about writing code. It is about deciding what should be built, understanding why it matters, and applying technology with judgment. When everyone can code, engineers differentiate themselves through their standards, instincts, product sense, and ability to understand the people using what they build. :contentReference[oaicite:0]{index=0} Chapters: 00:00 When everyone can code, what are engineers worth? 00:46 LLMs and the printing press 01:30 The limits that shaped software engineering 02:42 We finally live in a world where everyone can code 03:45 The existential question for experienced engineers 04:45 Coders versus software engineers 06:05 Don’t make the same mistake as Sears 07:38 Human judgment, experience, and empathy 09:02 Why constraints can produce better software 10:25 Product volatility and the Sharpe ratio 11:49 Software engineering is about solving problems 12:38 LLMs as leverage for engineers 13:45 What sets engineers apart 14:25 Your humanity is the key 🔗 Learn more about Arize: https://arize.com 🔗 Explore Arize:Observe: https://arize.com/observe 🔔 Subscribe for more talks on AI engineering, coding agents, evaluation, observability, and the future of software development: https://www.youtube.com/@arizeai?sub_confirmation=1 #SoftwareEngineering #CodingAgents #AIEngineering$

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