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Done Is a Function You Write: Eval-Driven Development for LLMs You Can Actually Trust - Brossura
Libro 4 di 7: Build Agents You Can Trust
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The new unit test, for AI that thinks.
Your large language model crushed the benchmark. Then it shipped, and the support tickets started. Sound familiar? You stopped trusting public leaderboards the day a contamination-resistant test dropped your "verified" score by thirty-five points overnight. And you realized the number you'd been steering by was noise. So now you're flying blind: a nondeterministic system that's brilliant on the demo, wrong 30% of the time at scale, and impossible to regression-test the way you test real code.
This is the field manual for LLM evaluation: the discipline that quietly became the center of AI engineering, where you write the tests that decide what a thinking machine is allowed to do. Its core move is a reframe: "done" is not a vibe or a leaderboard rank but a function you write, and once you can write that check, you can delegate to the machine everything that passes it. Treating evals as test-driven development for generative AI, it starts where the real failures are, your own traces, and ends with a suite that blocks silent regressions on every deploy. Along the way you'll align an LLM-as-judge to human labels, debug judge bias, defeat benchmark contamination, and separate capability from reliability.
The payoff is the scarce skill no model upgrade erases: not writing code, but writing the checks that let you delegate with confidence. And finally ship AI you can stand behind.
This is hands-on AI engineering, not theory. If you build with large language models and need to know they work before users do, this is the discipline that gets you there.
Read chapter one free with Look Inside.
Part of the Build Agents You Can Trust series, in The Verifier's Library.
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Done Is a Function You Write: Eval-Driven Development for LLMs You Can Actually Trust (Build Agents You Can Trust)
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Done Is a Function You Write (Paperback)
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Paperback. Condizione: new. Paperback. The new unit test, for AI that thinks.Your large language model crushed the benchmark. Then it shipped, and the support tickets started. Sound familiar? A nondeterministic system can be brilliant in the demo and wrong at scale, and you cannot regression-test it the way you test real code. The number you were steering by was measuring someone else's problem.Done Is a Function You Write is the field manual for LLM evaluation, the discipline that quietly became the center of AI engineering. Its core move is a reframe: "done" is not a vibe or a leaderboard rank, it is a function you write. Once you can write that check, you can delegate to the machine everything that passes it.Eval-driven development, from your first failing check to a suite that guards every deploy: Done as a function replaces the vibe check and the leaderboard rank with an executable definition of correct, treating evals as test-driven development for generative AI.Trace-first AI testing starts where the real failures live, your own production traces, so the suite measures your problem instead of a public benchmark's.LLM-as-judge alignment calibrates a machine grader against human labels and teaches you to spot and debug judge bias before it decides a release.Contamination defense shows why a verified score can drop thirty-five points overnight, and how to keep AI model evaluation honest when benchmarks leak into training data.Capability versus reliability separates what a model can do once from what it does every time, the distinction that decides what is safe to ship.The regression gate assembles a suite that blocks silent regressions on every deploy, the new unit test wired into your pipeline.This is hands-on AI engineering, not theory. Read it and you will write the checks that decide what a thinking machine is allowed to do, delegate exactly as much as those checks prove safe, and ship AI you can stand behind. That is the scarce skill no model upgrade erases.For engineers, data scientists, and applied-AI teams building with large language models and agentic AI, past "can the model do it" and stuck on "can I trust it enough to ship." Part of the Build Agents You Can Trust series, in The Verifier's Library. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798183828559
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Done Is a Function You Write (Paperback)
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Paperback. Condizione: new. Paperback. The new unit test, for AI that thinks.Your large language model crushed the benchmark. Then it shipped, and the support tickets started. Sound familiar? A nondeterministic system can be brilliant in the demo and wrong at scale, and you cannot regression-test it the way you test real code. The number you were steering by was measuring someone else's problem.Done Is a Function You Write is the field manual for LLM evaluation, the discipline that quietly became the center of AI engineering. Its core move is a reframe: "done" is not a vibe or a leaderboard rank, it is a function you write. Once you can write that check, you can delegate to the machine everything that passes it.Eval-driven development, from your first failing check to a suite that guards every deploy: Done as a function replaces the vibe check and the leaderboard rank with an executable definition of correct, treating evals as test-driven development for generative AI.Trace-first AI testing starts where the real failures live, your own production traces, so the suite measures your problem instead of a public benchmark's.LLM-as-judge alignment calibrates a machine grader against human labels and teaches you to spot and debug judge bias before it decides a release.Contamination defense shows why a verified score can drop thirty-five points overnight, and how to keep AI model evaluation honest when benchmarks leak into training data.Capability versus reliability separates what a model can do once from what it does every time, the distinction that decides what is safe to ship.The regression gate assembles a suite that blocks silent regressions on every deploy, the new unit test wired into your pipeline.This is hands-on AI engineering, not theory. Read it and you will write the checks that decide what a thinking machine is allowed to do, delegate exactly as much as those checks prove safe, and ship AI you can stand behind. That is the scarce skill no model upgrade erases.For engineers, data scientists, and applied-AI teams building with large language models and agentic AI, past "can the model do it" and stuck on "can I trust it enough to ship." Part of the Build Agents You Can Trust series, in The Verifier's Library. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798183828559
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Done Is a Function You Write : Eval-Driven Development for LLMs You Can Actually Trust
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Taschenbuch. Condizione: Neu. Neuware - The new unit test, for AI that thinks.Your large language model crushed the benchmark. Then it shipped, and the support tickets started. Sound familiar You stopped trusting public leaderboards the day a contamination-resistant test dropped your 'verified' score by thirty-five points overnight. And you realized the number you'd been steering by was noise. So now you're flying blind: a nondeterministic system that's brilliant on the demo, wrong 30% of the time at scale, and impossible to regression-test the way you test real code.This is the field manual for LLM evaluation: the discipline that quietly became the center of AI engineering, where you write the tests that decide what a thinking machine is allowed to do. Its core move is a reframe: 'done' is not a vibe or a leaderboard rank but a function you write, and once you can write that check, you can delegate to the machine everything that passes it. Treating evals as test-driven development for generative AI, it starts where the real failures are, your own traces, and ends with a suite that blocks silent regressions on every deploy. Along the way you'll align an LLM-as-judge to human labels, debug judge bias, defeat benchmark contamination, and separate capability from reliability.The payoff is the scarce skill no model upgrade erases: not writing code, but writing the checks that let you delegate with confidence. And finally ship AI you can stand behind.This is hands-on AI engineering, not theory. If you build with large language models and need to know they work before users do, this is the discipline that gets you there.Read chapter one free with Look Inside.Part of the Build Agents You Can Trust series, in The Verifier's Library. Codice articolo 9798183828559
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