jlcases

4 ms·

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by jlcases 1y ago
This is a clever approach to providing LLMs with specific, up-to-date package documentation context. How does it handle versioning if multiple versions of a package exist? Does it pull docs for the specific version used in the project conte
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by jlcases 1y ago
Creator here. This article came from a pattern I observed across dozens of AI-augmented development teams: initial velocity skyrockets with tools like Cursor AI and GitHub Copilot, but productivity crashes months later when teams need to mo
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Show HN: Beyond Vibe Coding:The sustainable approach to AI-assisted development(medium.com)
1 points by jlcases 1y ago|1 comments
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by jlcases 1y ago
Creator here. I'm launching an early MVP of PAELLADOC - a framework I'm developing to help teams make AI-assisted development more sustainable. The idea came from my own struggles with AI tools like Cursor: while they provide amaz
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Show HN: Paelladoc – Making AI-assisted development sustainable(paelladoc.com)
1 points by jlcases 1y ago|1 comments
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by jlcases 1y ago
This touches on a critical issue I've encountered in AI development: the synchronization between documentation and rapidly evolving AI systems. Here are my key learnings: 1. Version Control for Context: I've found that treating co
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by jlcases 1y ago
Based on my experience building AI documentation tools, I've found that evaluating LLM systems requires a three-layer approach: 1. Technical Evaluation: Beyond standard benchmarks, I've observed that context preservation across lo
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by jlcases 1y ago
This compression approach reminds me of similarities with human knowledge transfer. In both cases, we're looking for compact representations that can reconstruct complex information. For technical documentation, I'm experimenting
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by jlcases 1y ago
What impresses me most about technical documentation like this is how it structures knowledge into comprehensible layers. This article manages to explain an extremely complex system by establishing clear relationships between components. I&
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by jlcases 1y ago
That's great to hear! Building that semantic structuring module, especially with a MECE approach, would significantly enhance the pipeline's value for complex downstream tasks like knowledge graph creation or advanced RAG systems.
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by jlcases 1y ago
This is a valuable contribution. The quality of ML models heavily depends on the quality of training data, and extracting structured information from unstructured documents (like PDFs) is a critical bottleneck. A key challenge after OCR is
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by jlcases 1y ago
Interesting approach. The effectiveness of any AI, especially in nuanced scenarios like interviews, hinges on how well its underlying knowledge is structured. For an 'invisible AI interviewer' to ask relevant, probing questions, i
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by jlcases 1y ago
Code readability is directly related to the quality of its contextual documentation. I've been experimenting with documentation following MECE principles, which has greatly improved the maintainability of my projects.
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by jlcases 1y ago
The biggest challenge with ML models isn't the algorithm but the organization of contextual knowledge. In my experience, hierarchical structuring of documentation significantly improves results, especially when working with LLMs.
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by jlcases 1y ago
Documentation quality has been the determining factor in the evolution of my side projects. I've developed a structured documentation system that has completely transformed my workflow with AI assistants.
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by jlcases 1y ago
Knowledge structuring is key for self-taught learning. I've found that organizing resources using MECE principles (Mutually Exclusive, Collectively Exhaustive) significantly improves the learning curve, especially for complex technical
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by jlcases 1y ago
Author here. This article explores how AI tools are inadvertently creating knowledge gaps in agile teams, based on observations from multiple development teams. The key findings include: - How AI-assisted development affects team
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The silent agile crisis: knowledge loss in the AI era(medium.com)
3 points by jlcases 1y ago|1 comments
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by jlcases 1y ago
Fascinating approach with ologs and FSMs I've been working on PAELLADOC ( https://github.com/jlcases/paelladoc ) which applies MECE principles to documentation structure. Similar philosophy but focused on knowledge
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by jlcases 1y ago
Yes, that's Diataxis (formerly Divio). I faced similar challenges and found that combining it with MECE principles in my PAELLADOC framework made documentation much easier, especially with AI tools. Good luck getting your team started
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by jlcases 1y ago
Very interesting video. Many thanks
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by jlcases 1y ago
Great question about MECE vs Divio's system! They actually complement each other rather than conflict. MECE (Mutually Exclusive, Collectively Exhaustive) comes from management consulting and focuses on organizing concepts without ove
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by jlcases 1y ago
The hierarchical system I've developed organizes knowledge in nested MECE categories (Mutually Exclusive, Collectively Exhaustive). Rather than paralleling code exactly, it creates a conceptual tree that represents the mental model beh
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by jlcases 1y ago
Thank you for introducing me to ologs - they're fascinating. I'm intrigued by the distinction you make between formal methods and semi-formal approaches. I'd love to explore how your "likely-correct model for writing&quo
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by jlcases 1y ago
I've been working on a documentation system that improves how AI assistants understand project context. The problem I'm solving is that traditional documentation approaches are too fragmented for AI to effectively process. After s
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by jlcases 1y ago
I've noticed that the formalization of methods described by AWS parallels what we need in technical documentation. Complex systems require not just formal verification but also structured documentation following MECE principles (Mutual
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by jlcases 1y ago
I've found that the quality of LLM output depends enormously on how you structure the context. After experimenting with various documentation approaches, I've had the best results using MECE principles (Mutually Exclusive, Collect