AI Code Correct
Jeff LangrDiscover how AI can help build and verify software through AADV, a practical approach to delivering generated code that does exactly what it's supposed to.
| Platform |  | Pricing | Freemium | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 17 | Subscribers | Read | jjlangr.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Adding Small New Requirements, Revisited
If you’re wondering where you can find the article “Adding Small New Requirements” (i.e. not with the word “Revisited”), it doesn’t exist. No wait, that’s not true. It does exist, except that it’s not complete, polished, or published. I mig...
Changing behavior with AADV
### Capturing examples and interfaces
Examples: The lingua franca of AADV?
In my last post, I demonstrated that ChatGPT generated code semantic drift: Its solution deviated from the CAX examples provide. In this case, it generated some code to support sales of shares from the stock portfolio app, something it was ...
Semantic drift in AADV
1In my prior post, I exposed an example of how LLMs at times generate more code than you request. When I provided examples that demonstrated how to track stock purchases in my portfolio, the LLM generated this domain module:
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Authors
The writers behind this newsletter.
40+ year software dev veteran. AI, design, TDD, collaborative dev techniques. Author of 5 books; co-author: Clean Code. Pragmatic Bookshelf Technical Advisory Board. Owner, Langr Software Solutions (https://langrsoft.com)
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