Testing Is a Role, Not a Person
I was going to call this post “Interrogating My Own Code” but that was a bit opaque, even though it’s … More Testing Is a Role, Not a Person →
Stories from a Software Tester
Twice upon a time, in another space, no distance in any direction from here ...
Latest posts
The Integration Seam
Awhile back I posted my call to action posts: Testers: Act Like a Developer. Since that time, I’ve done a … More The Integration Seam →
When Performing Causality Means Performing Experience
I originally wanted to title this post “What Is It Like to Be Nothing?” which would be a direct riff … More When Performing Causality Means Performing Experience →
When AI Performs Causality Instead of Practicing It
In my previous post, I talked about the cautionary aspect of AI hallucinating its own hallucinations. There’s a deeper element … More When AI Performs Causality Instead of Practicing It →
When AI Hallucinates Its Own Hallucinations
I recently had an ongoing series on AI and Testing. Today I’m not running evals or measuring correctness scores. Today … More When AI Hallucinates Its Own Hallucinations →
Testing: The Art of Unlearning
In two earlier posts I traced the path from Aristotelian to Galilean thinking as a way of understanding how testing … More Testing: The Art of Unlearning →
AI Was Already Here: Loud Opinions vs. Precise Understanding
Previously I had talked about the idea of personal marketability when it came to learning AI. That was in the … More AI Was Already Here: Loud Opinions vs. Precise Understanding →
DSPy and RAG: Grounding Answers in Documents
In the previous post we looked at the idea of building up a pipeline with DSPy. In this post, we’ll … More DSPy and RAG: Grounding Answers in Documents →
DSPy Pipelines: Wiring Steps Without Writing Prompts
In the first post, we got everything set up to start exploring DSPy. Here we’ll continue that journey by looking … More DSPy Pipelines: Wiring Steps Without Writing Prompts →
DSPy: Declaring Instead of Prompting
In my AI and Testing series, which ran for a couple of months, I focused heavily on the testing side … More DSPy: Declaring Instead of Prompting →
AI and Testing: Evaluation Synthesis
This series has now covered eight metrics across two evaluation paradigms. We’ve applied them to a warp drive paper, a … More AI and Testing: Evaluation Synthesis →
AI and Testing: Evaluating Conversations
In the previous posts in the DeepEval series, we built up a diagnostic framework for evaluating RAG systems, covering Faithfulness, … More AI and Testing: Evaluating Conversations →
AI and Testing: Recall, Relevancy, and Richer Evaluation
In the previous posts we looked at the Faithfulness and Contextual Precision metrics with DeepEval, and started building an intuition … More AI and Testing: Recall, Relevancy, and Richer Evaluation →
The Last Useful Animal
In my previous posts, I’ve been talking a lot about AI technology and tooling, and any enthusiasm within those posts … More The Last Useful Animal →
Testing the “Yes-Man” in Your Pocket
If you’ve been following my recent posts on how to test AI, you know that evaluating Large Language Models (LLMs) … More Testing the “Yes-Man” in Your Pocket →
AI and Testing: From Specification to Story
In the previous post, we built a formal ontology from the Z-Machine specification, used it to drive code generation, and … More AI and Testing: From Specification to Story →
AI and Testing: From Ontology to Implementation
In the previous post, we looked at setting up an ontology based on a Z-Machine specification. Our goal was to … More AI and Testing: From Ontology to Implementation →
AI and Testing: From Specification to Ontology
In the previous posts we looked at setting up a graph pipeline and auditing that pipeline. All of this was … More AI and Testing: From Specification to Ontology →
AI and Testing: Auditing a Knowledge Graph Pipeline
In the previous post we looked at the code for an entire pipeline that uses a lightweight ontology to guide … More AI and Testing: Auditing a Knowledge Graph Pipeline →
AI and Testing: A Knowledge Graph Pipeline in Practice
In the previous post we talked about the conceptual basis of knowledge graphs and ontologies and pointed toward the code … More AI and Testing: A Knowledge Graph Pipeline in Practice →