Authority topics
AI software delivery
Faster generation only becomes delivery when coordination, review, ownership, and correction loops absorb the increased output.
Writing about agent-assisted delivery systems, multi-agent coordination, code review, software factories, project execution, and the operating models that turn generated work into accepted outcomes.
Core writing
The Correction Loop Is Becoming the Product
As generation gets cheaper, the correction loop becomes the valuable system around AI: verifiers, traces, domain feedback, outcome judges and regression-tested knowledge determine whether execution actually improves. This Weekly Read shows how to design correction paths that are observable, bounded, auditable and durable enough to compound.
Weekly ReadThe engineering job is moving from writing software to building the system that writes it.
Agentic code-review numbers show why a software factory is becoming urgent — and why the missing piece is the operator layer between stages, not the model.
Engineering LeadershipFurther writing
Recent analysis
AI Is Turning Hidden Assumptions Into System Contracts
Agent execution is getting cheap enough that requirements, acceptance criteria, autonomy boundaries, state and architecture economics can no longer remain implicit. This Weekly Read shows how to turn those hidden assumptions into inspectable system contracts using requirement recovery, executable acceptance, evidence-based handoffs, durable state and lifecycle cost models.
Weekly ReadThe Model Stopped Being the System
Week of June 15, 2026. One shift ran under every story: the model became a swappable component, and control moved to the layer around it — review, boundaries, context, and the people who own the result. A scan-layer TL;DR, five themes each with an operator move, one taken deep, three counter-signals, and what to track.
Weekly ReadShort pieces
One task in my workflow can be researched in ChatGPT, implemented by Codex, challenged by Claude, and updated through MCP.
Most project tools still assume every participant is human, which leaves someone acting as the relay between chats, repositories, decisions and the board.
BuildingEvery engineer knows Amdahl's law. Almost nobody applies it to AI forecasts.
A 10x improvement in one operation produces almost nothing at the system level if that operation was not the constraint — which explains both failed pilots and outsized wins.
AI transformationA generated patch is a hypothesis until someone re-runs the exploit.
Across 6,080 AI-generated patches only 26% were clean — and a plausible-but-wrong fix direction in the prompt cut success from two-thirds to one in six, with agents overriding their own contrary evidence.
AI engineeringFour agents cleared the backlog because none was allowed to be the hero.
Astro's issue factory separated reproduction, diagnosis, verification and implementation — the improvement came from forbidding self-verification, not from adding agents.
AI engineeringAI shortened how long it takes to build a feature — not how long it takes to learn from one.
37signals cut its cool-down along with its build time. Delivery compresses; customer absorption and operational recovery mostly do not, and the ratio between them shifts.
Engineering leadershipEvery AI strategy has a shadow roadmap — the work the organization quietly stopped funding.
Mid-market app counts jumped 41% in a year while a third of AI tools moved to token-based billing, which makes the negative roadmap the honest part of any AI plan.
AI transformationAI is getting good at reviewing code. That is exactly why the human's job in review has to move up.
An AI reviewer is good at the mechanical pass — but it misses the change that fits the diff and breaks the architecture. The reviewer's value moves up the abstraction stack, to the judgment and accountability the model structurally cannot supply. The mechanical reviewer can be automated; the one who owns the consequence cannot.
AI EngineeringThe model can be available and the deployment can still fail. The last mile is an engineering problem.
Enterprise AI depends on last-mile engineering: wiring AI into real tools, permissions, data, processes, and review gates. Buying capability is easier than absorbing it. The model is a purchase; the working system is a build.
AI TransformationIf an AI output is hard to evaluate, the problem may not be the eval. It may be the product boundary.
Good AI products make verification cheaper — decompose work into reviewable units, attach evidence, make the boundary between decided and inferred visible. Output that cannot be verified cheaply gets trusted blindly or ignored, and both are failures.
AI EngineeringThe important part of Claude Tag is not that Claude joined Slack. It is that execution is moving into the collaboration layer.
When agents enter the place where teams discuss work, the operating risk shifts from prompting to delegation, context, permission, and ownership. AI adoption becomes workflow design, not chat integration.
AI TransformationPrompt engineering was the visible phase. Loop engineering is where AI starts becoming operating infrastructure.
A loop has a goal, context, a way to act, a way to evaluate, and a rule for what happens next. The hard part is not making it run — it is deciding what the loop is allowed to optimize and where it must stop.
AI EngineeringFor years an app was a screen you tapped through. It is quietly becoming a set of functions an agent can call without ever opening it.
With Android 17 AppFunctions, an app exposes its actions as callable tools and the screen becomes optional. When a machine can call your product directly, your permission model stops being plumbing — it becomes the product.
Product EngineeringBuilt from this thinking
Codencer
A persistent daemon that manages, executes, validates, and audits tasks performed by external coding agents.
Orchestration bridge for coding agentsThe Tam
The Tam is the delivery system behind @tam, an AI Delivery Partner that plans work, coordinates engineers and coding agents, follows blockers and keeps delivery moving toward human review.
AI Delivery Partner