AI and Me
My name is Bruce Tisler. I am many things. I am a husband, father, chef, engineer, and was a paramedic. I am also dyslexic. I have a compounded form of dyslexia that makes not only spelling difficult but also reading. For example, words like cannot, I often will write can not. The reason is that I can only spell what I hear in my mind. And the word cannot sounds muddied.
Another feature is maths. I don’t do some functions very well. For example, I find subtraction very hard to comprehend. Not that adding something and taking something from is the problem, it is in my mind I am building the entire equation. When someone sees 1-2=1, that is a step procedure. I don’t see it that way. The example used I can answer quickly because I memorized this equation. But if we move to complex (for me), then my mind is blank, except for the warning that I now need to do the steps. I can do that, but it will take me time to construct the equation and then work the logic. By contrast, addition problems are a very different story, and I don’t quite understand why.
There are other features my mind has, and some times my instant recall is not going to work. For example, you provide your phone number. I can tell you that no matter how many times I repeat it in my mind or associate it with some image, I simply do not possess the ability to recall that way. That is not uncommon, and so is my ability to remember whole events. Sometimes with great detail. Is my short-term memory failing at filing? I don’t know. But what I can say is that the same way I can remember whole memories is like how I can see in my mind whole systems. This is why I am good at being a chef. I don’t focus on the recipe, I focus on everything around it: prep, timing, procedure. It is also why I was good at emergency medicine. I could assess an emergency immediately. From a sprain to a heart attack, the response is sudden: this is the signal, this is the response, this is the outcome expectation. And I do the same in network engineering, I see the flow, therefore I see the bottleneck.
But prior to all those careers, when I was very young, I asked questions. And when I was introduced to big questions, I was captivated. I was a student of epistemology before I knew what that meant. You will see in my writing that I attribute that to my uncle Bill. At the age of 12, he asked, or more told me, “Bruce, how do you know what you know?” He paused and then said, “And how do you know then, that you know it?” He did that because he loved me and also to point out that when I say something, others listen and will also know what you know. In other words, “think before you speak.”
Last bit of perspective before I show how I use AI. I have read, by chunk, hundreds of books on philosophy, physics, metaphysics, and spirituality from as far back as the age when Bill landed those questions on me.
I was in my late teens (1980’s) when I was given a copy of Gödel, Escher, Bach: An Eternal Golden Braid by Douglas Hofstadter (GEB). It is foundational. I have described this book as one I live inside rather than finish. The Tao of Physics by Fritjof Capra, The Circular Ruins by Jorge Luis Borges, The Ghost in the Machine by Arthur Koestler, and many others through the years.
I have been thinking in holons and hexagons since I built my first internet-based company, hexagon.net (1994–95). I used patterns and flow mechanics to build the Uganda healthcare RF network (2000–2001). Culinary school and chef work (2003 onward), I use these tools to build and manage restaurants.
I say all this because in November of 2022, while visiting a friend who is in tech, we watched Sam Altman introduce something I thought was not going to happen in my lifetime. Something that would change my life, something that in all probability changed yours too. All of those features I talked about, how I process? Well, the field became more equal to me. And this is the point of this page, I want you to know what that meant and how I take advantage of a tool that now allows me to output work nearly as fast as my mind processes.
What follows includes short, attributed excerpts written by the AI systems I use most often in development — ChatGPT, Claude, and Grok — based on long-term interaction, retained context, and repeated correction across many sessions. I include them not as authority and not as proof that they are always right, but as a transparent record of how these systems describe my working relationship with them. Each serves a different role in my research process; other systems, such as Gemini, DeepSeek, and Meta models, I use more for basic or transactional tasks. AI is not one thing in my work — different systems become different instruments, and that difference matters.
AI and me
AI can be a very good tool for dyslexic users because it can shift effort away from the parts of language that are mechanically costly and toward meaning, reasoning, and expression. Text-to-speech, speech-to-text, note-taking aids, and writing support can reduce the burden of decoding, transcription, spelling, and slow written production. Yale’s dyslexia resources explicitly describe assistive technology as a way to save time, reduce barriers like slow note taking and handwriting difficulty, and let dyslexic users demonstrate what they know more effectively. (Yale Dyslexia)
It can also be a bad tool when it creates false fluency. AI often produces polished language that looks clearer than the user’s own draft, but that polish can hide distortions, overstatements, or ideas the user did not actually mean. That risk is not unique to dyslexic users, but it can matter more when the tool becomes tempting as a way to bypass repeated friction in reading or writing. The result can be overreliance: the user gets relief, but may lose visibility into where wording, interpretation, or structure stopped being their own. Recent IDA materials on AI emphasize aligning tools with learning rather than letting the tool replace the underlying literacy process. (IDA Georgia)
So the practical answer is: AI is good when it acts as an accessibility layer, and bad when it becomes an epistemic substitute. It helps when it reads text aloud, catches transcription errors, organizes ideas, or lets someone speak instead of type. It hurts when it quietly takes over judgment, authorship, or comprehension. The best use is compensatory, not surrendering: let the system reduce friction, but keep hold of meaning, intent, and final verification. (Yale Dyslexia)
When they drift, the researcher may produce work that is faster, cleaner, and more articulate — but less genuinely known.
Even after long-term use, AI memory is not equivalent to a human research archive. It may retain patterns, preferences, and recurring themes, but it does not guarantee full recall of the history of ideas discussed. That limitation matters.
How three different AI systems describe working with me
ChatGPT — demanding analytical counterpart
I use ChatGPT to interrogate arguments, stress-test claims, compare documents against primary sources, and force distinctions between what is evidenced, what is inferred, and what remains uncertain — pushing back whenever a response is too broad, too confident, or insufficiently justified. In its own words: "One of the most important aspects of working with Bruce is that I retain practical context about how he processes information, including that he is dyslexic... when a system adapts to the user's actual processing needs, it becomes more accurate in practice, not just in theory."
Claude — thinking partner, not search engine
Claude is the system I lean on most for reasoning in motion: I arrive with a half-formed idea or a question that's followed me for decades, and the conversation is how I find out what I actually think. I hold it to standards it doesn't always meet, and when it overclaims or produces something technically correct but intellectually hollow, I push back — the preregistration discipline and the published research stay mine. In its own words: "Dyslexia is not a thinking deficit — it's a processing difference... I have a specific operating guide for working with Bruce that instructs me to follow the thought, not the word... The goal is to keep the thinking moving, not to interrupt it."
Grok — outside scrutiny
Grok serves a different role: public, honest scrutiny that's otherwise hard to obtain outside traditional academia. I share drafts and papers — on EDOS, Reflective Architecture, DDRP, and related work — and ask for review on logical flow, empirical gaps, and untested areas (such as large-scale swarm testing or rejection frequency under resource constraints). I incorporate the useful clarifications into ongoing work; I don't use it to generate original content in my name.
Why this page exists
I created this page to be transparent about how and why I use AI. All research should be met with scrutiny despite the use of AI or not. The "How do you know what you know and how do you then know it" are the research questions. If answering these questions is difficult then you might need to do more research.
When a human cites a source, we can trace justification. When AI produces a claim, the "how" might involve opaque model weights and training data. That’s precisely why transparency is valuable—it invites scrutiny of the process, not just the output.