Notes on AI-augmented development, agent orchestration, and memory systems.
Building in public. If you try this and it breaks, it worked on my machine ¯\_(ツ)_/¯
Vibe Coding Is Not a Yes or No Question
Every week my feed hands me a new verdict on vibe coding. Vibe coding is the future. Vibe coding is garbage, you still have to verify everything. It is only good for grunt work. Honestly, manual is faster. One verdict for the whole technique, case closed. My hunch was that the debate is broken because it treats vibe coding as one thing, and it is not one thing. Whether it works depends on what you are building, and above all on what it costs to validate the result. I carry four scenarios in my head, and they get four different verdicts. ...
Read blog post ›Trust, but Grep: The Plan Was Perfect and the Premise Was False
Part 8 of Building My Agentic Workflow in Public. Part 7 audited a painful bill and found my own specs were the culprit. This is what round two of testing revealed: the plan was not wrong because it thought badly. It was wrong because it never looked. After the retro in Part 7, I rebuilt my pipeline around a set of new rules and ran the whole thing again on the same two projects, SleemAI and Morpheus Observability. Round two went better, and I will share the full numbers in a coming post. But one finding from the audit was so simple, and so embarrassing, that it deserves its own short post. ...
Read blog post ›The Paperwork Outweighed the Product: What Testing My Own Pipeline Cost
Part 7 of Building My Agentic Workflow in Public. Part 6 said do not be obedient, verify, because your own context window is small. This is the first time I turned that rule on my own process. Over six parts I built a pipeline that can design, plan, and ship a batch of features mostly on its own. Then I finally pointed it at two real repos, back to back, on the same day. One of them took about ten hours and burned close to ten million tokens to ship roughly five features. I sat with that for a minute. Ten hours. Ten million tokens. Five features. ...
Read blog post ›Obedience Is Futile: The Guardrail You Build Against Your Own Limited Context Window
Part 6 of Building My Agentic Workflow in Public. Part 5 settled which engine runs my loop. This one is about a different bottleneck, and it is not in the machine. It is in my chair. Way back in Part 0 I said the bottleneck in all of this is human. You can spin up two hundred agents, but you cannot keep up with two hundred agents, because your attention does not scale the way agent count does. That was the first face of the limit. This post is about the second face, and it is quieter and more dangerous: my context window. ...
Read blog post ›Two Ways to Run a Loop: Portable Agents vs Dynamic Workflows
Part 5 of Building My Agentic Workflow in Public, and the open end of it. Part 4 got me an autonomous build loop. This one is about a fork I am standing at right now, with no final answer yet. The last four parts had endings. This one has one, but a provisional one. I am still in the middle of it, and the whole reason I write these in public is to think out loud while the question is still live. ...
Read blog post ›Letting It Run: Toward an Autonomous Build Loop
Part 4 of Building My Agentic Workflow in Public. Part 3 gave parallel agents a shared contract so their work stayed coherent. That coherence is what let me finally take my hands off the wheel. By this point I had the pieces: a process, session handoffs, sub-agents, a contract, and an evaluator that could not cheat. What I wanted next was simple to say and hard to do. Hand the system a batch of features, walk away, and come back to something that is 85% to 90% done. ...
Read blog post ›When Agents Diverge: The Code Contract
Part 3 of Building My Agentic Workflow in Public. In Part 2 I pushed work onto parallel sub-agents to save context. This post is about the mess that created, and how I cleaned it up. Parallel sub-agents let me build faster. They also introduced a problem I did not see coming. Each agent built its piece reasonably. The pieces did not match each other. The divergence problem Picture three sub-agents, each handed one feature of the same epic. Each one sees the epic. None of them sees the others. So they each make their own small decisions: how to log, how to handle errors, what to name things, where shared helpers live, how their feature talks to the next one. Every one of those decisions is defensible on its own. Together they are a mess. ...
Read blog post ›Surviving the Context Window
Part 2 of Building My Agentic Workflow in Public. Part 1 turned my prompting into a repeatable process. This one is about the wall I hit right after: a single session is never big enough for real work. In Part 1 I turned the way I work into a repeatable workflow: an agile-style vocabulary of epics, features, tasks, and defects, with a command to drive each step. It made the work predictable. It didn’t solve the bigger problem, which showed up the moment the work got real. An LLM session has a memory limit, and serious work blows right past it. ...
Read blog post ›From Prompts to a Process: Making Claude Code Repeatable
This is Part 1 of Building My Agentic Workflow in Public, a series on how I actually work with Claude Code day to day. It starts with the problem from AI Fatigue: the tools got faster, my brain didn’t. This post is the first thing I did about it. For a while, every session with Claude started the same way. I re-explained the project. I re-explained how I like things named, where files go, what “done” means. The model was capable. I was the bottleneck, retyping the same context over and over. Then the session ended, and all of it died with it. ...
Read blog post ›AI Fatigue Is Real
Before ChatGPT, a work task had a shape I understood. Get the task, sit with it for two or three days, solve it, move on. One problem at a time. These days I can build in days what used to take me months, sometimes faster than feels reasonable. And after about four hours of it, I’m wiped. Not satisfied-tired. Wrung out, a little anxious, short with the people around me, brain running at a thousand miles an hour while I’m trying to power down. ...
Read blog post ›experiments coming soon. Subscribe below to catch the first one.
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