Blog

Stories, insights, and lessons learned from building and using ctx.

Context Engineering¶

Agent Memory Is Infrastructure ¶

March 4, 2026 — Every AI coding agent starts fresh. The obvious fix is "memory." But there's a different problem memory doesn't touch: the project itself accumulates knowledge that has nothing to do with any single session. This post argues that agent memory is L2 (runtime cache); what's missing is L3 (project infrastructure).

Topics: context engineering, agent memory, infrastructure, persistence, team knowledge

Context as Infrastructure ¶

February 17, 2026 — Where does your AI's knowledge live between sessions? If the answer is "in a prompt I paste at the start," you are treating context as a consumable. This post argues for treating it as infrastructure instead: persistent files, separation of concerns, two-tier storage, progressive disclosure, and the filesystem as the most mature interface available.

Topics: context engineering, infrastructure, progressive disclosure, persistence, design philosophy

The Attention Budget: Why Your AI Forgets What You Just Told It ¶

February 3, 2026 — Every token you send to an AI consumes a finite resource: the attention budget. Understanding this constraint shaped every design decision in ctx: hierarchical file structure, explicit budgets, progressive disclosure, and filesystem-as-index.

Topics: attention mechanics, context engineering, progressive disclosure, ctx primitives, token budgets

Before Context Windows, We Had Bouncers ¶

February 14, 2026 — IRC is stateless. You disconnect, you vanish. Modern systems are not much different. This post traces the line from IRC bouncers to context engineering: stateless protocols require stateful wrappers, volatile interfaces require durable memory.

Topics: context engineering, infrastructure, IRC, persistence, state continuity

The Last Question ¶

February 28, 2026 — In 1956, Asimov wrote a story about a question that spans the entire future of the universe. A reading of "The Last Question" through the lens of persistence, substrate migration, and what it means to build systems where sessions don't reset.

Topics: context continuity, long-lived systems, persistence, intelligence over time, field notes

Agent Behavior and Design¶

The Dog Ate My Homework: Teaching AI Agents to Read Before They Write ¶

February 25, 2026 — You wrote the playbook. The agent skipped all of it. Five sessions, five failure modes, and the discovery that observable compliance beats perfect compliance.

Topics: hooks, agent behavior, context engineering, behavioral design, testing methodology, compliance monitoring

Skills That Fight the Platform ¶

February 4, 2026 — When custom skills conflict with system prompt defaults, the AI has to reconcile contradictory instructions. Five conflict patterns discovered while building ctx.

Topics: context engineering, skill design, system prompts, antipatterns, AI safety primitives

The Anatomy of a Skill That Works ¶

February 7, 2026 — I had 20 skills. Most were well-intentioned stubs. Then I rewrote all of them. Seven lessons emerged: quality gates prevent premature execution, negative triggers are load-bearing, examples set boundaries better than rules.

Topics: skill design, context engineering, quality gates, E/A/R framework, practical patterns

You Can't Import Expertise ¶

February 5, 2026 — I found a well-crafted consolidation skill. Applied my own E/A/R framework: 70% was noise. This post is about why good skills can't be copy-pasted, and how to grow them from your project's own drift history.

Topics: skill adaptation, E/A/R framework, convention drift, consolidation, project-specific expertise

Not Everything Is a Skill ¶

February 8, 2026 — I ran an 8-agent codebase audit and got actionable results. The natural instinct was to wrap the prompt as a skill. Then I applied my own criteria: it failed all three tests.

Topics: skill design, context engineering, automation discipline, recipes, agent teams

Defense in Depth: Securing AI Agents ¶

February 9, 2026 — The security advice was "use CONSTITUTION.md for guardrails." That is wishful thinking. Five defense layers for unattended AI agents, each with a bypass, and why the strength is in the combination.

Topics: agent security, defense in depth, prompt injection, autonomous loops, container isolation

Development Practice¶

Code Is Cheap. Judgment Is Not.¶

February 17, 2026 — AI does not replace workers. It replaces unstructured effort. Three weeks of building ctx with an AI agent proved it: YOLO mode showed production is cheap, the 3:1 ratio showed judgment has a cadence.

Topics: AI and expertise, context engineering, judgment vs production, human-AI collaboration, automation discipline

The 3:1 Ratio ¶

February 17, 2026 — AI makes technical debt worse — not because it writes bad code, but because it writes code so fast that drift accumulates before you notice. Three feature sessions, one consolidation session.

Topics: consolidation, technical debt, development workflow, convention drift, code quality

Refactoring with Intent: Human-Guided Sessions in AI Development ¶

February 1, 2026 — The YOLO mode shipped 14 commands in a week. But technical debt doesn't send invoices. This is the story of what happened when we started guiding the AI with intent.

Topics: refactoring, code quality, documentation standards, module decomposition, YOLO versus intentional development

How Deep Is Too Deep?¶

February 12, 2026 — I kept feeling like I should go deeper into ML theory. Then I spent a week debugging an agent failure that had nothing to do with model architecture. When depth compounds and when it doesn't.

Topics: AI foundations, abstraction boundaries, agentic systems, context engineering, failure modes

Agent Workflows¶

Parallel Agents, Merge Debt, and the Myth of Overnight Progress ¶

February 17, 2026 — You discover agents can run in parallel. So you open ten terminals. It is not progress: it is merge debt being manufactured in real time. The five-agent ceiling and why role separation beats file locking.

Topics: agent workflows, parallelism, verification, context engineering, engineering practice

Parallel Agents with Git Worktrees ¶

February 14, 2026 — I had 30 open tasks that didn't touch the same files. Using git worktrees to partition a backlog by file overlap, run 3-4 agents simultaneously, and merge the results.

Topics: agent teams, parallelism, git worktrees, context engineering, task management

Field Notes and Signals¶

When a System Starts Explaining Itself ¶

February 17, 2026 — Every new substrate begins as a private advantage. Reality begins when other people start describing it in their own language. "Better than Adderall" is not praise; it is a diagnostic.

Topics: field notes, adoption signals, infrastructure vs tools, context engineering, substrates

Why Zensical ¶

February 15, 2026 — I needed a static site generator for the journal system. The instinct was Hugo. But instinct is not analysis. Why zensical was the right choice: thin dependencies, MkDocs-compatible config, and zero lock-in.

Topics: tooling, static site generators, journal system, infrastructure decisions, context engineering