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No Off Ramp Decisions as Forcing Functions for Driving Change

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Sometimes we need to have a forcing function to make change inevitable.  Implement a no-off-ramp change that aligns teams and partners with the vision.  This assumes you have enough clout or leverage to make that happen.  Drivers can include asset sales, contract changes, and regulatory issues. Holding the line can be challenging when people raise issues and either actively or passively resist.  Make a type of change that cannot be reasonably undone, and then create gatekeepers for the new desired behavior when people are onboarded A Mind Map Thinking through the aspects related to making changes. See the video down below for a better explanation of the diagram than I do here in writing. Click to expand Maybe I can get an AI to convert the transcript into the body of this article. Problem You have a problem that can't be resolved as a normal part of the business. The Organization refuses to respond to the need.  There is some current behavior that is driving up ...
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The short/medium forecast for LLM based coding agents and aids July 2025 edition

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Here are three short videos I did after reading a bunch “AI is blah blah to programming” posts on LinkedIn. Maybe not yet to binary Never another general purpos programming language The future is domain specific languages (DSLs) Revision History Created 2025 07
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Creating order out of chaos in a world of AI Everywhere

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The hot ticket right now is "Put AI Everywhere". This usually results in a race to come up with ideas about how AI can be used in new products or existing systems.  I suggest creating a system to analyze existing processes, software, and programs with a structured approach, identifying opportunities and assessing risks and rewards. LLM agents, chat bots and instructors models that turn human speech and writing patterns into content or actions is in scope here.  TTS, STT, translators and other non integrated LLM uses are out of scope. The talk below iteratively breaks down our process until we reach the point where we identify AI opportunities. We start with PDCA (Plan-Do-Check-Adjust) as a notion for the lifecycle of products, software, and processes. We can map that into the following in the software space. Item 4 could be anything specific to your domain.  Design Time: All of the processes that happen before actual code execution. This is before transactions, customer ...
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Quit hiding the scrollbars on a Mac! Make Mac scrollbars always visible

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macOS on Mac and MacBook machines automatically hides the scrollbars when you aren't scrolling. It is a great space saver, but it can make things difficult. This behavior violates the "what you see is what you can do" implicit contract between users and the system. It makes it impossible to scroll applications or browser windows that contain a scrolling drawing area.  An example is the DASH  plotting and dashboard system. The graph view grabs all scale and drag operations to the full width of the screen. The trackpad just affects the content area and not the page-level scrolling. We have a fix for that! Make scrollbars on macOS always visible You can do this via the macOS Settings application Settings --> Appearance --> Show scrollbars Created 2025/07
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2025 OWASP Top 10 for LLM Applications - Creating a common understanding of security risks

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LLM-supported AI is being stuffed into every computer-based and computer-assisted process. A lot is being said about the benefits of LLM, with some secondary discussions about security and behavioral risks. Many of the risk discussions have been unstructured bullet points or anecdotal stories of hacked systems. The OWASP Top 10 for LLM Applications 2025 provides a framework for understanding the top risks of an LLM-integrated system. The OWASP Top 10 for LLM Applications deserves the same attention the OWASP Top 10 for Web applications has held for over a decade. The Developer's Playbook for Large Language Model Security  by Steve Wilson provides a solid foundation for understanding risks existing in an LLM ecosystem. It also led me to the  OWASP Top 10 for LLM Applications 2025 .  This is a great resource for anyone looking to integrate LLMS into business processes or existing systems. I got this book as part of a set of O'Reilly books in a Humble Bundle. OWASP Top 10 fo...
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Joy and headaches building a well structured multi-platform Flutter app with CoPilot

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You only understand something when you are forced to do it yourself. I've been looking for a way to force myself to build and test a multi-platform application.  A lousy game night scoring experience demanded an NIH solution. So, I built a multi-platform Flutter application using only CoPilot agent prompts. It was a learning experience where I had to cheat, relying on my knowledge to drive CoPilot where I wanted it to go. The end result is a multi-platform Flutter app,  fs_game_score that can be found on GitHub .  This is a generic game scoring app created almost  entirely using VSCode's Copilot  agent mode  with virtually no  hand coding. There were lots  of AI agent prompts with many undo/redo attempts. The application has been tested on Android, IOS, Chrome, macOS, and Windows 11.  At least a dozen lessons learned Coding It helps if you know what libraries you want to use. That lets you direct the copilot to the most up-to-date or best pra...
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Lets try Mad Libs Style

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We used to "play" buzzword bingo in meetings and company events.  For everyday craziness, I've been using an internal MadLibs-style approach. I'll try and collect samples over time. Sample problems One (2025) Life is too short to ___________ in _____________ Two (2025) Real programmers can write ______________ in any __________ Sample Solutions One 2025 Life is too short to spend 5  hours per day in meetings Life is too short to spend more than 1/3  in work Life is too short to spend the whole day in doors   Two 2025 Real programmers can write Fortran  in any language Real programmers can  write Testable Code  in any schedule Revision History 2025 05 Created
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Using OpenVoice as an all local voice operated agent.

General Impressions OpenVoice OS is an interesting project that runs on relatively lightweight hardware and lets you retain local voice processing. The most obvious use cases are Home Automation or local voice bot. AI has everyone's attention and all the voice agent work is now happening around AI integration for smarter responses. OpenVoice feels small as it currently exists.  It is mostly a curiosity on its own. OpenVoice LLM integration requires you to know something. IMO the best thing would be to have a zero-config Ollama or LocalLLM that is part of the default extended skill set.  The Raspberry Pi was great but it felt constrained. The most cost-effective and full-featured hardware setup for completely local voice recognition and processing is probably a Mac desktop.  It would be capable of running OpenVoice and local MLX-based LLMs. Revision History Created 2024 04
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Selecting the OpenVoice O/S installation path for your Raspberry Pi based voice agent.

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I had a pile of Raspberry Pi 3b and Raspberry Pi 400 hardware so I used that.  If I had been building a magic-mirror type unit then I would have had a GUI.  In my case, I wanted a headless agent.  The Rasberry Pi 3 was frustratingly slow.  The P400 was pretty usable with and without the GUI. In my case, I ended up running the Pi headless to create more headroom for any processing on the unit. The RaspOVOS image was dead simple to write to an SD card on my Windows machine using the Raspberry Pi OS installer program. The decision tree looks pretty much like Related Links https://community.openconversational.ai/latest https://github.com/OpenVoiceOS/ovos-releases https://github.com/OpenVoiceOS/raspOVOS Revision History Created 2024 04
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I tried to plant something in a garden....

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I tried to plant something in an enterprise garden.  The garden was actually be a graveyard of bad decisions. First Version. I tried to plant something in an enterprise garden. It turned out that it was actually a graveyard of bad decisions. Revision History This page is subject to revision based on future input. Created 2025/04 Updated 2025/07  
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