Notes
Thoughts on software, AI, and systems.
AI-Native SDLC: A Verification-First Lifecycle for Agent-Generated Code
A blueprint for an AI-native SDLC built on intent-first specs, multi-agent competitive generation, deterministic guardrails, adversarial verification, and continuous validation.
Designing Agent-Oriented CLIs That Teach Themselves
A guide to agent-oriented CLIs: versioned command contracts, safe validate/plan/apply, deterministic JSON outputs, stable error codes, and replayable provenance.
Harness Engineering Is the Primary Lever for Agent Reliability in 2025–2026
Why agent reliability in 2025–2026 is often driven more by harness engineering—tool gating, verification, retries, termination rules, and tracing—than by marginal base model upgrades.
rx: Why Lean Agent Kernels Beat General Coding Frameworks
Why agent infrastructure benefits from a lean microkernel: an explicit control loop, narrow tool contracts, append-only event state, and replaceable transport for predictable cost and behavior.
Tests Aren’t the Primary Safety System in High-Velocity, AI-Assisted Codebases
In AI-assisted, high-velocity codebases, tests stay necessary but cannot be the primary safety system; survivability comes from observability, constraints, and recovery.
Decoupling Agency and Privilege for High-Agency AI Agents on Real Infrastructure
An operator-focused case for separating an agent’s autonomy from its permissions and secrets to limit blast radius under prompt injection and model variability.
Trust, Patience, and the Craft of Working With Modern Agentic AI
An operator-focused guide to earning trust in agentic AI through constraints, instrumentation, and iterative verification loops.
The Human Loop: Orientation in the Age of Autonomous Agents
Software engineering is shifting from 'Human-in-the-loop' execution to 'Human-on-the-loop' orientation, where humans manage system dynamics and context in a Joint Cognitive System with autonomous agents.
Personal Software Factories: Individual-Scale Production Lines for Software
An operator model for turning intent into deployed software via repeatable pipelines and agentized execution.
Designing Agent Workflows as Environments, Not Prompts
Prompting treats agents as step-by-step trainees; cultivation treats them as actors embedded in environments where tools, constraints, and feedback loops drive reliability.
Personal Operating Systems and Micro-Apps
Multi-agent coding assistants have reduced software creation costs enough that individuals can now build personal operating systems—control layers that encode decision rules and execution mechanisms into custom micro-apps, shifting knowledge work from passive memory toward active execution.
Open Source After Coding Agents: From Labor to Judgment
Why open source must shift from maximizing contribution volume to enforcing strict curation as coding agents drive the cost of code to zero.
The Evolution of AI Coding Agents: From Autocomplete to Autonomous SDLC
A milestone timeline (2013–2026) showing how AI coding tools evolved from autocomplete into terminal-native agents with tool use, planning, and verification loops.
Code as a Compilation Target: The New Assembly
An exploration of how AI agents shift source code from a human artifact to a compilation target, requiring a move from syntax-based review to intent-based validation.
The Software Replacement Age: Architecting for a Low-Cost Generation World
In an era where regeneration is cheaper than comprehension, replaceability becomes the primary architectural virtue.
GitHub Copilot Model Selection Guidelines
A systems design approach to selecting the optimal LLM tier within GitHub Copilot to maximize research throughput and minimize cognitive waste.
AI-Native Engineering: From Autocomplete to Agent Orchestration
Exploring the shift from AI-augmented to AI-native engineering, the context stack, and the systemic verification crisis.
Authority-First Agent Architecture
Decoupling permission logic from reasoning loops to build safer, more predictable agentic systems.
Failure-Oriented Agent Orchestration
A governance-first approach to agent orchestration prioritizing predictability, containment, and recoverability over raw productivity.
Earned Agent Autonomy: A Governance Model for AI Systems
A risk-mitigated governance framework for integrating AI agents into production software engineering workflows through a staged autonomy ladder.
Agent Execution Contracts: Unifying Specification, Testing, and Labor
How specifications, tests, and agents collapse into a single machine-readable contract that governs autonomous labor.
Agent-First Software Engineering
A practical description of an agent-first workflow where software engineering shifts from typing code to designing boundaries, governance, and verification for AI agents.
Typing Code Is Solved
Why the bottleneck in software engineering is no longer typing code, but context, constraints, and judgment in agent-assisted systems.