Workflow on Thede Technologies

The Thread That Never Ends

Fri, 09 Oct 2026 09:00:00 -0500

For years the rule with AI chat was: keep threads small and single-focused. One chat per task. Finish, close, open a fresh one. Long threads rot. I learned that one the hard way in April, when I mined a month of my own sessions and found that past a hundred turns the answers stopped being right.

With Fable, I stopped.

One thread has been open for days now. I asked it what it was best at, and it said taking in a tremendous amount of information and not losing track of any of it. So I opened a single terminal window and we worked on five projects at the same time. It didn’t lose the thread once. It knew which piece belonged to which project and what we needed to do next.

Whispering to the Machine: Take Three

Wed, 22 Jul 2026 00:00:00 +0000

In February I ended the second installment of this series with a prediction. I said I’d write another update when the landscape shifted again, and that based on the pace, “that might be next month.”

It’s July. Five months - the longest gap since I started writing these snapshots. The first piece, in June 2025, was about learning to collaborate with a model inside an IDE. The second, in February, was about orchestrating a team of agents from a terminal. I assumed the third would be about whatever tool came next.

The move was upstream

Tue, 28 Apr 2026 00:00:00 +0000

I spent most of a day pointing at broken cases. Each time I pointed at one, the model patched it. The next regeneration would surface a different broken case in a different file. We’d patch that. Then a third. By late afternoon I was the one suggesting we slow down and return to first principles. The model wasn’t pulling me up a level on its own.

The bug itself was small. I’ve been wiring up a pipeline that turns transcripts of my conversations with AI tools into clean Markdown for an Obsidian vault. The reasoning part was working: extracting topics, summarizing, tagging. The rendering kept breaking. Stray characters, broken callouts, content that ended up harder to read than the original conversation had been. I was working it inside Gemini CLI, mostly on their fast tier with occasional escalation to their reasoning model. Twelve back-and-forth turns across roughly six hours of intermittent work, and we still hadn’t landed it.

From Tools to Framework

Fri, 03 Apr 2026 00:00:00 +0000

Frameworks are inevitable.

Kevin Kelly wrote about this in What Technology Wants. Certain inventions appear independently, in multiple places, at roughly the same time. The telephone, the lightbulb, calculus. Not because of genius, but because the conditions were right. The ground was ready and the solution was waiting to be found.

Ruby got Rails. Python got Django. PHP got Laravel. In each case, the same pattern: developers working with raw tools hit a ceiling, and someone assembled an opinionated structure that encoded what worked into something repeatable. The framework didn’t invent new capabilities. It organized the ones that already existed into a form that could be taught, shared, and built upon.

Context Architecture

Sat, 28 Mar 2026 00:00:00 +0000

Your AI agent isn’t stupid. It’s lost.

The most common failure I see in agentic systems isn’t a reasoning failure or a coding error. It’s a context failure. The agent didn’t have the right information at the right time, so it guessed. And the guess looked plausible enough that nobody caught it until production.

Context architecture is the skill of building structured data environments so that AI agents can reliably search, find, and retrieve exactly the information they need, without getting confused by dirty data, missing context, or irrelevant noise. Anthropic’s engineering team put it plainly: “Claude is already smart enough. Intelligence is not the bottleneck. Context is.”

Specification Precision

Sat, 28 Mar 2026 00:00:00 +0000

The most valuable skill in the AI economy isn’t coding. It’s writing.

Not blog posts or marketing copy. I mean writing instructions so precise that a literal-minded machine with no ability to read between the lines will execute exactly what you intended. Every time. Without you watching.

I’ve spent the last year building an AI-augmented engineering operation across 13 projects. The single biggest determinant of whether an agent produces good work isn’t the model, the temperature, or the prompt template. It’s the specificity of the instruction I gave it.

The System That Built Itself

Sat, 07 Mar 2026 00:00:00 +0000

I didn’t set out to build a system. I set out to survive.

For the better part of a year, I’ve been operating as a one-person engineering team, across my day job and the products I’m building on my own. I wrote about what that looks like in The One-Person Engineering Team, and about the engineering practices that emerged in Eliminating Waste in the SDLC. But something else happened that I didn’t fully recognize until I stopped and looked at what I’d built.

Eliminating Waste in the SDLC

Thu, 05 Mar 2026 00:00:00 +0000

I wrote a follow-up exploring what happens after you eliminate the waste: The Processing Layer Is Not a Moat.

I don’t write much code anymore.

About six months ago, Dario Amodei predicted that within a year, 90% of code would be AI-generated. More recently, Boris Cherny, the creator of Claude Code at Anthropic, said that 100% of his code was already written by AI. I thought those numbers sounded aggressive. Now I’m living them.

Whispering to the Machine: Take Two

Fri, 27 Feb 2026 00:00:00 +0000

Eight months ago, I wrote a snapshot of what it felt like to collaborate with AI in software development. I talked about using Cursor, chatting with models, migrating a codebase from Bootstrap to Tailwind. I laid out five principles: plan meticulously, work iteratively, use the right tool, embrace collaboration, don’t be afraid to start fresh.

Those principles still hold. Every one of them. But the way I execute on them has changed so much that the original piece reads like a dispatch from a different era. Eight months in this field might as well be a decade.

The One-Person Engineering Team

Tue, 17 Feb 2026 00:00:00 +0000

Boris Cherny, the creator of Claude Code at Anthropic, recently wrote that “pretty much 100% of our code is written by Claude Code.” For him personally, it had been 100% for over two months. He doesn’t even make small edits by hand. He shipped 22 PRs in one day and 27 the day before, each one entirely written by Claude.

I think he’s right. And I think most engineering teams aren’t ready for what that means.

Whispering to the Machine

Mon, 16 Jun 2025 00:00:00 +0000

I had a conversation with another developer recently that left me feeling energized. We were kicking off a new project, and as we started talking about process, it became clear we were both arriving at similar conclusions about how to actually work with AI in software development. It was one of those moments that validates the path you’ve been on.

The ground moves daily. This year alone I’ve worked with two major new series of models from Anthropic, and the difference between them is obvious in the work. What works today might be obsolete tomorrow. That’s why I write these down. Consider this a snapshot, a journal entry of what my process for collaborating with agentic AI looked like in the summer of 2025.