Posts connected by the agents tag.
📅 October 15, 2026
⏱️ 9 min read
The first 80% of a feature gets the demo, the congratulations, and the promotion packet. The last 20% (the part that makes the thing actually usable) costs a magnitude more and is rewarded far less. The reason is structural: every additional nine of reliability is a different engineering problem than the one before it, and you cannot reach it by extending a design that was never built for it. In the age of AI, when the token cost of writing the scalable version is roughly the token cost of writing the disposable one, the V1-then-rewrite habit deserves a second look.
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📅 October 08, 2026
⏱️ 11 min read
Boris Cherny's three prompting directives map onto the Quest Engine exactly: what you want is the Why (the problem statement), how it should verify is Renew (the definition of done), and how much effort is the How. The middle one is the subtle one, because effort is no longer a procedure, it is a strategy, a topology of agents, and a budget of resource plus time. The list is short because Search and execution are assumed.
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📅 October 06, 2026
⏱️ 8 min read
Roughly 80% of the software I produce now starts as a prompt, not a keystroke. Mapped onto the Quest Engine, that means agents have moved into the Drive (the How) and are eating into the four W's. What is left for me is the Why, the context still trapped in people's heads, and the work of running a fleet of agents predictably.
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📅 October 06, 2026
⏱️ 13 min read
Elon's algorithm is not really an automation algorithm. It is a procedure for forcing shared understanding of a process, and automation is what it happens to permit at the end. The Quest Engine says the same thing structurally and translates it to a world that is mostly digital, where the walk around the factory floor can be delegated to agents and the goal is not a fully automated process but a self-sustaining one that keeps humans only where judgment genuinely lives.
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📅 October 05, 2026
⏱️ 12 min read
In a conversation about Ruby, Rails, and the future of programming, Matz described joy, freedom, and motivation as the thing a language gives you that is hard to replicate. Freedom maps cleanly to Autonomy and Drive. Joy turns out to be the Discovery/Play/Joy triad. Motivation is not a force at all, it is the container, and it needs expanding before the mapping closes.
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📅 September 26, 2026
⏱️ 11 min read
A few weeks of running Astra next to Opus 5 left me with three conclusions: the behavior I depend on is mostly harness and habit rather than intelligence, watermarking every output treats a shared piece of work as if the model made it alone, and I want a personal profile that travels with me so the model stops being the thing I have to learn.
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📅 September 23, 2026
⏱️ 7 min read
Six months of building AI infrastructure and coaching coworkers on their agent workflows taught me the bottleneck is no longer code creation. Someone can write ten thousand lines in a day, but nobody found a way to make a colleague understand those ten thousand lines any faster than in 2019. Validation is still the vehicle through which humans actually learn a system, and that work has not been automated.
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📅 July 31, 2026
⏱️ 7 min read
Start with the code works for the software engineering circle of the Venn diagram, but a technical program manager naturally starts from the why, not the code. Once agents act like subordinates, the person steering them sits in the overlap and needs two documents: a Why doc facing outward toward the problem and stakeholders, and a How doc facing inward toward the agent's technical direction.
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📅 July 29, 2026
⏱️ 10 min read
Spec-driven development is a vague enough term that it can mean anything from a paragraph of intent to a fully waterfalled design. I tried the fully-specified version and it backfired: it left no room for an autonomous agent to explore alternatives. What worked instead was naming the actual sequence. Build multiple proofs of concept, verify each one against something real, and only then write the design document, informed by what the proofs of concept actually showed.
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📅 July 24, 2026
⏱️ 7 min read
For thirty years we optimized software to be easy for a human hand. Agents invert that goal. The graphical interface is turning from the thing you drive into the thing you read, and the tools that survive the shift are the ones an agent can talk to.
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📅 July 10, 2026
⏱️ 11 min read
Agentic tooling made pull requests cheap and plentiful, so the bottleneck moved from writing code to trusting it. The answer is not another review loop but front-loaded rigor: invest the engineering effort ahead of time to build a full, production-shaped synthetic environment you run locally, so that validation itself becomes cheap and the PR turns into a context-sharing mechanism instead of an approval gate. Tools like .NET Aspire and Dapr show what that inner loop can look like, and the same principles carry over to homegrown systems.
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📅 July 03, 2026
⏱️ 6 min read
Kahneman's two modes of thinking (fast System 1 and slow System 2) map onto learning to ride a bicycle. Attention gives way to automaticity, and that same arc is a methodology for thinking about agents, leverage, and engineering systems.
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📅 July 03, 2026
⏱️ 6 min read
Blameless engineering, borrowed from Google's SRE culture, is usually filed under postmortems. But the postmortem is only the last place the culture shows up. Blamelessness shifts all the way left into how you design systems, and it lands on one uncomfortable rule: the team is the unit of work, and heroes are a symptom of a system that is not yet well crafted. In the age of agents, where there is no one to blame, that rule stops being a nicety and becomes the only way to debug at all.
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📅 June 29, 2026
⏱️ 6 min read
Nine years of work notes, from sort-of-daily Markdown files in 2017 to monthly Word docs to a single yearly running document, and how AI agents finally took over the writing through worklogs.
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📅 June 27, 2026
⏱️ 8 min read
Time matters, but expertise does not come from time alone. In software engineering, AI makes the missing part impossible to ignore: growth comes from new constraints, real feedback, rising stakes, and ownership of outcomes.
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📅 April 19, 2026
⏱️ 7 min read
When working with AI agents, craftsmanship, judgment, and taste are what humans contribute. Craftsmanship builds expertise through exploration, judgment determines what you control versus delegate, and taste guides what's worth building. These map to searching, being driven, and renewal in the Quest Engine.
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📅 April 08, 2026
⏱️ 13 min read
Quest Engine is a methodology built on three recursive action steps that help you solve problems at any scale. Through Searching, Being Driven, and Renewing (you compound your capability continuously). AI coding agents amplify these natural processes as tools that multiply your leverage.
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📅 March 28, 2026
⏱️ 10 min read
How worklogs transformed my workflow with AI coding agents (capturing context across sessions, using GitHub Issues as a backend, and turning structured logs into an agentic work queue).
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📅 February 07, 2026
⏱️ 9 min read
Reflecting on my experience using AI coding tools since Claude Opus 4.5, contrasting Rust and scripting language development, and insights on multi-agent workflows.
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📅 December 11, 2025
⏱️ 9 min read
A deep dive into how a keyboard configuration project evolved from manual Go programming to agent-assisted development, and the surprising realization that having agents make direct changes is simpler than writing code to automate everything.
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📅 September 13, 2025
⏱️ 5 min read
How this entire blog system was created using AI agents, including the technical implementation, content creation, and instructions for adding new posts.
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