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The Harness Is the Thing

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Why This Matters

This article highlights how the evolution of AI-powered development tools, particularly the use of harnesses and agents, is transforming software creation. It emphasizes that individual developers can now achieve large-scale, high-quality results with less reliance on large teams, thanks to these advancements. The focus on cost-effective, unified AI models underscores the democratization of powerful development resources, making high-level productivity accessible to more developers and consumers.

Key Takeaways

When I started out as a developer, I had a graybeard observe for me that Moore's law also applies to software. I didn't understand that this constant conversation about how we were solving problems was the arc of progress; that complaining about J2EE and how slow Netbeans was, and wheezing about table-based layouts and constant full-page reloads, was the day-to-day optimizing that is also an engine of progress.

The last eighteen months have been a particular window of relentless improvement. Tab completions have given way to agentic coding which has given way to managing your agents with a harness. I've gone from being awed at the productivity gains to settling into the game and squeezing the lemon to see what I can get.

There are new truths

Single developer projects can build to the caliber and consistency of large development teams. You can and should build bespoke applications and you don't have to sweat onboarding experienced engineers; if they know their stack backwards and forwards they'll quickly know how to contribute to yours. But most of all, I have learned that the harness is the thing; the fulcrum from which my expectations meet the LLM's capabilities.

At the moment my rig is supported by two subscriptions (Cursor, Claude) that I can augment with Pi as needed. All three share my skills and AGENTS.md . Though I am using three TUIs, I have a unified experience. This has commodified the models for me; there is no magic sauce or special experience in Claude or Cursor that I need in order to be productive. I have zero anxiety about the transition from Cursor to Codex at the end of this month.

The cost advantage

In the commodity1 era I can get great results from a host of available models, but I've been leaning on deepseek-v4-flash-0731 since it came out. It's a rare case that I dip into my Anthropic API budget to utilize Fable.

I can run Deepseek on most maintenance and simple tasks. It's when I am exploring a serious feature or large refactor with lots of moving parts that I reach for the frontier. Recently I learned about prewalk2, Can Bölük's technique that uses frontier for the planning phase and first task, then hands off once the pattern is set. I paired it with the planner/worker/critic split from Building an Advanced Agentic Harness3 - a single prompt that plans, executes, and critiques itself confuses its own objectives, so each role gets isolated instead. I built both into a skill, with a supporting Pi extension that can take over at any stage of work.

Exploration leads to a plan formalized into an explicit DAG (directed acyclic graph) task list. Then a worker takes over, focusing on implementing the DAG one node at a time. Once complete, I bring in the critic to simplify and question what was implemented. Often this phase will push back enough that the worker phase is revisited. But once satisfied, the critic gives way to a promoter, which is my reminder that a job is not complete until you've properly communicated it to others.

I added the promoter step to shore up a weak spot I have for wanting to ship and move on. It's my reminder to let people know about work I'm completing. I need a little help from Fable in this phase, as promotion is subtle and easily borked, and nobody likes a critic so running it through the frontier gives it more weight.

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