From 73491f6bcd08ac6da1753e468c85dc5580f146fb Mon Sep 17 00:00:00 2001 From: Piotr Zborowski Date: Wed, 25 Mar 2026 12:30:05 +0100 Subject: [PATCH 1/9] add a section on high level harnesses --- astro.config.ts | 1 + .../high-level-harnesses.mdx | 100 ++++++++++++++++++ src/data/links.csv | 7 ++ 3 files changed, 108 insertions(+) create mode 100644 src/content/docs/expanding-horizons/high-level-harnesses.mdx diff --git a/astro.config.ts b/astro.config.ts index 6b5caa2..8d77558 100644 --- a/astro.config.ts +++ b/astro.config.ts @@ -63,6 +63,7 @@ export default defineConfig({ items: [ { slug: "expanding-horizons/threads-context-and-caching" }, { slug: "expanding-horizons/model-pricing" }, + { slug: "expanding-horizons/high-level-harnesses" }, { slug: "expanding-horizons/what-to-read-next" }, ], }, diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx new file mode 100644 index 0000000..9ea682d --- /dev/null +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -0,0 +1,100 @@ +--- +title: High-level harnesses +description: Beyond individual agent sessions — scheduled automations, parallel agent fleets, and the emerging pattern of AI-driven code pipelines. +--- + +import ExternalLink from "../../../components/ExternalLink.astro"; + +The [harness engineering](/becoming-productive/harness-engineering/) chapter covered shaping a single agent's actions through AGENTS.md, skills, hooks, and subagents. +This section is one level of abstraction higher—it covers tools and patterns that treat agents as a managable workforce. + +:::caution +Products and feature sets can change significantly between revisions of this guide. +Treat this page as an orientation, especially for building a solid intuition of the field, not a definitive reference. +::: + +## From conductor to orchestrator + +So far in this guide, you have been a **conductor**—you worked interactively with a single agent, steering it turn by turn in real time. +Now, you will become an **orchestrator**, delegating work to a fleet of agents running in parallel. +Instead of supervising each agent individually, you will manage the output queue—a review inbox, an issue tracker, a PR pipeline. + +:::note[Remember] +The key shift is from "what should the agent do?" to "what work should be running right now, and how do I review what came back?" +::: + +## Running agents in parallel + +The key difference is running several agents simultaneously, each on an isolated task. + +Conductor by Melty Labs is a tool built for exactly this. +It runs multiple AI coding agents at once (both Claude Code and Codex are supported), with each agent working in its own Git worktree. +A dashboard on the user side shows what each agent is doing and lets you review changes as soon as they come in. + +You hand different issues to separate agents at once, come back and review, and merge the ones you like. +That is qualitatively different from the sequential, one-task-at-a-time conductor workflow from the previous chapters. + +## Scheduled and recurring agents + +Agents do not always need to wait for you to trigger them—you can also set them up in advance. + +OpenAI's Codex App includes an Automations feature: +describe a recurring task, set a schedule, and have Codex run it in the background. +Results end up in a review inbox or are auto-archived if nothing needs attention. + +OpenAI uses automations internally for tasks like: +- Daily issue triage +- Surfacing and summarizing CI failures +- Generating release briefs +- Checking for regressions between versions + +With automations, the process becomes closer to a CI pipeline than a chat window—an agent is no longer a tool you reach for and becomes a background process. + +## Issue-tracker-driven orchestration + +You may also set up the agent(s) to respond to issues as they appear. + +Symphony is an open-source orchestration service published by OpenAI. +It monitors a Linear board, creates an isolated workspace per issue, and runs a Codex agent on each one. +Engineers decide what issues belong in scope; Symphony handles assignment and execution. + +Agent behavior is defined in a `WORKFLOW.md` file in the repository alongside the code. The prompt and runtime settings for each agent run are versioned the same way you version a CI pipeline. +When an agent finishes, it gathers evidence: CI results, PR review feedback, complexity analysis. +You can review the output instead of the agent's process. + +:::tip +Symphony is recommended for codebases that have adopted [harness engineering](/becoming-productive/harness-engineering/). +::: + +## The Code Factory pattern + +Beyond specific products, there is an emerging pattern popularized by Ryan Carson under the name **Code Factory**. +The idea is a repository setup where agents autonomously write code, open pull requests, and a separate review agent validates those PRs with machine-verifiable evidence. +If validation passes, the PR merges without human intervention. + +The continuous loop looks like this: + +1. Agent writes code and opens a PR. +2. Risk-aware CI gates check the change. +3. A review agent inspects the PR and collects evidence — screenshots, test results, static analysis. +4. If all checks pass, the PR lands automatically. +5. If anything fails, the agent retries or flags the issue for human review. + +:::caution +A Code Factory is only as good as its quality gates. +An automated pipeline that merges bad PRs is strictly worse than one that does nothing. +Invest in solid tests, linters, and CI before automating the merge step. +::: + +- + +## The one-human company + +The Code Factory pattern is the technical foundation of a broader idea: that a single person with a well-configured agent fleet can operate at the scale that would previously have required a full engineering team. + +Projects like OpenClaw package infrastructure for connecting AI agents to communication platforms and scheduling systems, turning a single machine into an always-on agent runtime that responds to messages, executes tasks, and ships work continuously. + +Steve Yegge, in a widely-read interview with The Pragmatic Engineer, argues that the engineering profession is reorganizing around exactly this spectrum. +His framing: most engineers are at the low end of AI adoption today, and those who stay there risk being outcompeted by engineers who learn to orchestrate agent fleets—to act as owners of work queues rather than writers of individual functions. + +- \ No newline at end of file diff --git a/src/data/links.csv b/src/data/links.csv index ca4f650..1b75335 100644 --- a/src/data/links.csv +++ b/src/data/links.csv @@ -25,6 +25,7 @@ https://code.claude.com/docs/en/security,Security - Claude Code Docs,Anthropic,, https://code.claude.com/docs/en/sub-agents,Create custom subagents - Claude Code Docs,Anthropic,,2026-03-13 https://code.claude.com/docs/en/sub-agents#code-reviewer,Create custom subagents - Claude Code Docs,,,2026-03-05 https://coderabbit.ai/,CodeRabbit,,,2026-03-05 +https://conductor.build/,Conductor - Run a team of coding agents on your Mac,,,2026-03-25 https://context7.com/,Context7 - Up-to-date documentation for LLMs and AI code editors,,,2026-03-13 https://cursor.com/blog,Cursor Blog,,,2026-03-04 https://cursor.com/bugbot,Cursor Bugbot,,,2026-03-05 @@ -38,6 +39,8 @@ https://cursor.com/for/code-review,Reviewing Code with Cursor | Cursor Docs,,,20 https://cursor.com/pricing,Cursor Subscription,,,2026-03-04 https://developers.openai.com/api/docs/guides/compaction,Compaction,OpenAI,,2026-03-04 https://developers.openai.com/codex/agent-approvals-security,Codex: Agent approvals & security,OpenAI,,2026-03-16 +https://developers.openai.com/codex/app,App – Codex | OpenAI Developers,,,2026-03-25 +https://developers.openai.com/codex/app/automations,Automations – Codex app | OpenAI Developers,,,2026-03-25 https://developers.openai.com/codex/app/worktrees/#working-between-local-and-worktree,Worktrees,,,2026-03-10 https://developers.openai.com/codex/cli/features#run-local-code-review,Codex CLI features (run local code review),,,2026-03-05 https://developers.openai.com/codex/integrations/github/,Use Codex in GitHub,,,2026-03-05 @@ -56,6 +59,7 @@ https://github.com/mcp,GitHub MCP Registry,,,2026-03-13 https://github.com/microsoft/playwright-mcp,microsoft/playwright-mcp,Microsoft,,2026-03-13 https://github.com/mkaput,Marek Kaput,,,2026-03-04 https://github.com/openai/skills,openai/skills,OpenAI,,2026-03-12 +https://github.com/openai/symphony,"GitHub - openai/symphony: Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents. · GitHub",,,2026-03-25 https://github.com/software-mansion-labs/skills,software-mansion-labs/skills,Software Mansion,,2026-03-12 https://github.com/steipete/mcporter/,"steipete/mcporter: Call MCPs via TypeScript, masquerading as simple TypeScript API. Or package them as cli.",Peter Steinberger,,2026-03-04 https://github.com/topics/agent-skills,GitHub Topic: agent-skills,,,2026-03-12 @@ -73,6 +77,8 @@ https://lucumr.pocoo.org/,Thoughts and Writings,Armin Ronacher,,2026-03-04 https://mcp.grep.app/,mcp.grep.app,Vercel,,2026-03-04 https://mitchellh.com/,Blog,Mitchell Hashimoto,,2026-03-04 https://models.dev/,Models.dev - An open-source database of AI models,Opencode,,2026-03-04 +https://myclaw.ai/,OpenClaw & Clawdbot Cloud Hosting — Managed Hosting | MyClaw.ai,,,2026-03-25 +https://newsletter.pragmaticengineer.com/p/from-ides-to-ai-agents-with-steve,From IDEs to AI Agents with Steve Yegge - by Gergely Orosz,,,2026-03-25 https://openai.com/chatgpt/pricing/,ChatGPT Subscription,,,2026-03-04 https://openai.com/index/harness-engineering/,Harness engineering: leveraging Codex in an agent-first world,OpenAI,2026-02-11,2026-03-04 https://openai.com/news/engineering/,OpenAI Engineering News,,,2026-03-04 @@ -110,6 +116,7 @@ https://x.com/GeminiApp,Google Gemini (@GeminiApp) on X,,,2026-03-04 https://x.com/karpathy,Andrej Karpathy (@karpathy) on X,,,2026-03-04 https://x.com/opencode,OpenCode (@opencode) on X,,,2026-03-04 https://x.com/RLanceMartin,Lance Martin (@RLanceMartin) on X,,,2026-03-04 +https://x.com/ryancarson,Ryan Carson (@ryancarson) on X,,,2026-03-25 https://x.com/thorstenball,Thorsten Ball (@thorstenball) on X,,,2026-03-04 https://x.com/thsottiaux,Tibo (@thsottiaux) on X,,,2026-03-04 https://x.com/trq212,Thariq Shihipar (@trq212) on X,,,2026-03-04 From 31d018b5f031fd7d10f8be01cfad99e30f69ec64 Mon Sep 17 00:00:00 2001 From: Piotr Zborowski Date: Wed, 25 Mar 2026 12:45:29 +0100 Subject: [PATCH 2/9] spelling fix --- .../docs/expanding-horizons/high-level-harnesses.mdx | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 9ea682d..061142d 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -6,7 +6,7 @@ description: Beyond individual agent sessions — scheduled automations, paralle import ExternalLink from "../../../components/ExternalLink.astro"; The [harness engineering](/becoming-productive/harness-engineering/) chapter covered shaping a single agent's actions through AGENTS.md, skills, hooks, and subagents. -This section is one level of abstraction higher—it covers tools and patterns that treat agents as a managable workforce. +This section is one level of abstraction higher—it covers tools and patterns that treat agents as a manageable workforce. :::caution Products and feature sets can change significantly between revisions of this guide. @@ -16,7 +16,7 @@ Treat this page as an orientation, especially for building a solid intuition of ## From conductor to orchestrator So far in this guide, you have been a **conductor**—you worked interactively with a single agent, steering it turn by turn in real time. -Now, you will become an **orchestrator**, delegating work to a fleet of agents running in parallel. +Now, you will become an **orchestrator**, delegating work to a fleet of agents running in parallel. Instead of supervising each agent individually, you will manage the output queue—a review inbox, an issue tracker, a PR pipeline. :::note[Remember] @@ -52,13 +52,14 @@ With automations, the process becomes closer to a CI pipeline than a chat window ## Issue-tracker-driven orchestration -You may also set up the agent(s) to respond to issues as they appear. +You may also set up agents to respond to issues as they appear. Symphony is an open-source orchestration service published by OpenAI. It monitors a Linear board, creates an isolated workspace per issue, and runs a Codex agent on each one. Engineers decide what issues belong in scope; Symphony handles assignment and execution. -Agent behavior is defined in a `WORKFLOW.md` file in the repository alongside the code. The prompt and runtime settings for each agent run are versioned the same way you version a CI pipeline. +Agent behavior is defined in a `WORKFLOW.md` file in the repository alongside the code. +The prompt and runtime settings for each agent run are versioned the same way you version a CI pipeline. When an agent finishes, it gathers evidence: CI results, PR review feedback, complexity analysis. You can review the output instead of the agent's process. From 4e2e6f41ec04f58b881e7bceee0dbadecf4228bc Mon Sep 17 00:00:00 2001 From: Piotr Zborowski Date: Thu, 26 Mar 2026 12:42:15 +0100 Subject: [PATCH 3/9] implement part of suggestions --- .../high-level-harnesses.mdx | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 061142d..061be77 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -6,18 +6,19 @@ description: Beyond individual agent sessions — scheduled automations, paralle import ExternalLink from "../../../components/ExternalLink.astro"; The [harness engineering](/becoming-productive/harness-engineering/) chapter covered shaping a single agent's actions through AGENTS.md, skills, hooks, and subagents. -This section is one level of abstraction higher—it covers tools and patterns that treat agents as a manageable workforce. +This page is one level of abstraction up — it covers tools and patterns that treat agents as a manageable workforce. :::caution Products and feature sets can change significantly between revisions of this guide. Treat this page as an orientation, especially for building a solid intuition of the field, not a definitive reference. ::: -## From conductor to orchestrator +## From engineering to managing -So far in this guide, you have been a **conductor**—you worked interactively with a single agent, steering it turn by turn in real time. -Now, you will become an **orchestrator**, delegating work to a fleet of agents running in parallel. -Instead of supervising each agent individually, you will manage the output queue—a review inbox, an issue tracker, a PR pipeline. +So far in this guide, you have been an **engineer** — you worked interactively with a single agent, steering it turn by turn in real time. +Now, you will become a **manager**, delegating work to a fleet of agents running in parallel. +Instead of supervising each agent individually, you will manage the output queue — a review inbox, an issue tracker, a PR pipeline. +Your coding assistant no longer serves as a conductor, but as an orchestrator. :::note[Remember] The key shift is from "what should the agent do?" to "what work should be running right now, and how do I review what came back?" @@ -36,7 +37,7 @@ That is qualitatively different from the sequential, one-task-at-a-time conducto ## Scheduled and recurring agents -Agents do not always need to wait for you to trigger them—you can also set them up in advance. +Agents do not always need to wait for you to trigger them — you can also set them up in advance. OpenAI's Codex App includes an Automations feature: describe a recurring task, set a schedule, and have Codex run it in the background. @@ -48,7 +49,7 @@ OpenAI uses automations internally for tasks like: - Generating release briefs - Checking for regressions between versions -With automations, the process becomes closer to a CI pipeline than a chat window—an agent is no longer a tool you reach for and becomes a background process. +With automations, the process becomes closer to a CI pipeline than a chat window — an agent is no longer a tool you reach for and becomes a background process. ## Issue-tracker-driven orchestration @@ -94,8 +95,8 @@ Invest in solid tests, linters, and CI before automating the merge step. The Code Factory pattern is the technical foundation of a broader idea: that a single person with a well-configured agent fleet can operate at the scale that would previously have required a full engineering team. Projects like OpenClaw package infrastructure for connecting AI agents to communication platforms and scheduling systems, turning a single machine into an always-on agent runtime that responds to messages, executes tasks, and ships work continuously. - +x Steve Yegge, in a widely-read interview with The Pragmatic Engineer, argues that the engineering profession is reorganizing around exactly this spectrum. -His framing: most engineers are at the low end of AI adoption today, and those who stay there risk being outcompeted by engineers who learn to orchestrate agent fleets—to act as owners of work queues rather than writers of individual functions. +His framing: most engineers are at the low end of AI adoption today, and those who stay there risk being outcompeted by engineers who learn to orchestrate agent fleets — to act as owners of work queues rather than writers of individual functions. - \ No newline at end of file From 8cae326a04385a1594f5f099cb6fbb790573b1c5 Mon Sep 17 00:00:00 2001 From: Piotr Zborowski Date: Thu, 2 Apr 2026 14:48:36 +0200 Subject: [PATCH 4/9] implement the rest of the suggestions --- .../high-level-harnesses.mdx | 57 +++++++++++-------- src/data/links.csv | 4 +- 2 files changed, 35 insertions(+), 26 deletions(-) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 061be77..0f9b77a 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -27,45 +27,53 @@ The key shift is from "what should the agent do?" to "what work should be runnin ## Running agents in parallel The key difference is running several agents simultaneously, each on an isolated task. - -Conductor by Melty Labs is a tool built for exactly this. -It runs multiple AI coding agents at once (both Claude Code and Codex are supported), with each agent working in its own Git worktree. -A dashboard on the user side shows what each agent is doing and lets you review changes as soon as they come in. - You hand different issues to separate agents at once, come back and review, and merge the ones you like. That is qualitatively different from the sequential, one-task-at-a-time conductor workflow from the previous chapters. -## Scheduled and recurring agents +[Subagents](/becoming-productive/harness-engineering/#subagents) are also parallel, but they are different: a subagent is spawned **by the agent** to partition a single task's context. +The agent decides when to spawn one, waits for the result, and folds it back into its own session. +You as the human still trigger one top-level session and review one result. -Agents do not always need to wait for you to trigger them — you can also set them up in advance. +What is described here is different: **you** spawn multiple fully independent agent sessions, each assigned to a separate task. +No session knows about the others. +You are not waiting on any one of them — you come back later and review the queue of results in bulk. -OpenAI's Codex App includes an Automations feature: -describe a recurring task, set a schedule, and have Codex run it in the background. -Results end up in a review inbox or are auto-archived if nothing needs attention. +In practice, each agent needs its own isolated workspace — typically a separate Git worktree — so their changes do not interfere. +A dashboard or queue then surfaces results as agents finish, letting you review and merge at your own pace. -OpenAI uses automations internally for tasks like: +For example, Conductor is a tool built around this model, +running multiple AI coding agents (Claude Code and Codex) in parallel worktrees with a shared review dashboard. + +## Scheduled and recurring agents + +Agents do not always need to wait for you to trigger them — you can set them up in advance to run on a schedule. +The pattern is similar to a cron job or a CI pipeline: describe a recurring task, define when it should run, and have an agent execute it in the background. +Results land in a review inbox or are auto-archived if nothing needs attention. + +This is well-suited for tasks like: - Daily issue triage - Surfacing and summarizing CI failures - Generating release briefs - Checking for regressions between versions -With automations, the process becomes closer to a CI pipeline than a chat window — an agent is no longer a tool you reach for and becomes a background process. +With scheduled agents, the process becomes closer to a CI pipeline than a chat window — an agent is no longer a tool you reach for, but a background process. + +As an example, OpenAI's Codex App includes an Automations feature built around exactly this model. ## Issue-tracker-driven orchestration -You may also set up agents to respond to issues as they appear. +A natural extension of scheduled agents is wiring them directly to your issue tracker. +Instead of manually assigning tasks to agents, the system monitors a board and automatically spawns an agent for each new issue in scope. +Engineers decide what issues belong in scope; the orchestrator handles assignment and execution. -Symphony is an open-source orchestration service published by OpenAI. -It monitors a Linear board, creates an isolated workspace per issue, and runs a Codex agent on each one. -Engineers decide what issues belong in scope; Symphony handles assignment and execution. +Agent behavior can be defined in a workflow file versioned alongside the code — the same way you version a CI pipeline. +When an agent finishes, it gathers evidence (CI results, PR review feedback, complexity analysis) for human review. -Agent behavior is defined in a `WORKFLOW.md` file in the repository alongside the code. -The prompt and runtime settings for each agent run are versioned the same way you version a CI pipeline. -When an agent finishes, it gathers evidence: CI results, PR review feedback, complexity analysis. -You can review the output instead of the agent's process. +For example, Symphony is an open-source orchestration service published by OpenAI that implements this pattern, +monitoring a Linear board and running a Codex agent per issue in an isolated workspace. :::tip -Symphony is recommended for codebases that have adopted [harness engineering](/becoming-productive/harness-engineering/). +Issue-tracker-driven orchestration works best on codebases that have adopted [harness engineering](/becoming-productive/harness-engineering/). ::: ## The Code Factory pattern @@ -94,9 +102,10 @@ Invest in solid tests, linters, and CI before automating the merge step. The Code Factory pattern is the technical foundation of a broader idea: that a single person with a well-configured agent fleet can operate at the scale that would previously have required a full engineering team. -Projects like OpenClaw package infrastructure for connecting AI agents to communication platforms and scheduling systems, turning a single machine into an always-on agent runtime that responds to messages, executes tasks, and ships work continuously. -x +This requires connecting agents to communication platforms, scheduling systems, and external services — turning a single machine into an always-on runtime that responds to messages, executes tasks, and ships work continuously. +As an example of tooling in this space, see OpenClaw, which packages infrastructure for exactly this kind of setup. + Steve Yegge, in a widely-read interview with The Pragmatic Engineer, argues that the engineering profession is reorganizing around exactly this spectrum. His framing: most engineers are at the low end of AI adoption today, and those who stay there risk being outcompeted by engineers who learn to orchestrate agent fleets — to act as owners of work queues rather than writers of individual functions. -- \ No newline at end of file +- diff --git a/src/data/links.csv b/src/data/links.csv index 1b75335..ecea782 100644 --- a/src/data/links.csv +++ b/src/data/links.csv @@ -25,7 +25,7 @@ https://code.claude.com/docs/en/security,Security - Claude Code Docs,Anthropic,, https://code.claude.com/docs/en/sub-agents,Create custom subagents - Claude Code Docs,Anthropic,,2026-03-13 https://code.claude.com/docs/en/sub-agents#code-reviewer,Create custom subagents - Claude Code Docs,,,2026-03-05 https://coderabbit.ai/,CodeRabbit,,,2026-03-05 -https://conductor.build/,Conductor - Run a team of coding agents on your Mac,,,2026-03-25 +https://conductor.build/,Conductor - Run a team of coding agents on your Mac,Melty Labs,,2026-03-25 https://context7.com/,Context7 - Up-to-date documentation for LLMs and AI code editors,,,2026-03-13 https://cursor.com/blog,Cursor Blog,,,2026-03-04 https://cursor.com/bugbot,Cursor Bugbot,,,2026-03-05 @@ -77,11 +77,11 @@ https://lucumr.pocoo.org/,Thoughts and Writings,Armin Ronacher,,2026-03-04 https://mcp.grep.app/,mcp.grep.app,Vercel,,2026-03-04 https://mitchellh.com/,Blog,Mitchell Hashimoto,,2026-03-04 https://models.dev/,Models.dev - An open-source database of AI models,Opencode,,2026-03-04 -https://myclaw.ai/,OpenClaw & Clawdbot Cloud Hosting — Managed Hosting | MyClaw.ai,,,2026-03-25 https://newsletter.pragmaticengineer.com/p/from-ides-to-ai-agents-with-steve,From IDEs to AI Agents with Steve Yegge - by Gergely Orosz,,,2026-03-25 https://openai.com/chatgpt/pricing/,ChatGPT Subscription,,,2026-03-04 https://openai.com/index/harness-engineering/,Harness engineering: leveraging Codex in an agent-first world,OpenAI,2026-02-11,2026-03-04 https://openai.com/news/engineering/,OpenAI Engineering News,,,2026-03-04 +https://openclaw.ai/,OpenClaw — Personal AI Assistant,,,2026-04-02 https://opencode.ai/docs/go/,Opencode Go,,,2026-03-04 https://platform.claude.com/docs/en/build-with-claude/compaction,Compaction,Anthropic,,2026-03-04 https://platform.claude.com/docs/en/resources/prompt-library/socratic-sage,Prompting best practices,Anthropic,,2026-03-04 From 63ef31da5060b4ac7f2ba30104a8a3216f0d9585 Mon Sep 17 00:00:00 2001 From: Piotr Zborowski Date: Tue, 7 Apr 2026 11:16:22 +0200 Subject: [PATCH 5/9] add a section on agent communication --- .../high-level-harnesses.mdx | 27 +++++++++++++++++++ 1 file changed, 27 insertions(+) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 0f9b77a..83d8509 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -76,6 +76,33 @@ monitoring a Linear board and running a Codex agent per issue in an isolated wor Issue-tracker-driven orchestration works best on codebases that have adopted [harness engineering](/becoming-productive/harness-engineering/). ::: +## Agent communication + +Running multiple agents in parallel may cause coordination problem — agents must exchange information without overloading any one context window. +Two broad patterns have emerged. + +The simpler one is **hub-and-spoke orchestration**, where a lead agent spawns workers, collects their outputs, and consolidates. +Workers never communicate directly. +The benefit is simplicity, as the full picture is present in one place. +The cost is that every intermediate result, log line, and failed attempt flows back through the orchestrator's context, degrading its reasoning quality over time. + +The more capable pattern is **collaborative teaming**, where agents share a task list, claim work independently, and can send messages directly to one another. +A worker can flag a dependency, request a peer review, or broadcast a finding without routing it through the lead. +The lead's context stays clean; coordination happens at the edges. + +In practice, most pipelines fall somewhere on a spectrum between these extremes, often organized into three levels: + +1. **Isolated workers** — each agent runs independently and returns its output to the caller. +2. **Orchestrated workflows** — outputs become inputs for the next stage via shared files or aggregated results. +3. **Collaborative teams** — agents share a task graph, can send direct or broadcast messages, and notify the lead when work completes. + +The right level depends on how tightly coupled the tasks are. +Independent parallel tasks — security scan, test run, lint check — fit level 1 or 2 well. +Tasks that need to challenge or build on each other's intermediate findings call for level 3. + +For reference, Claude Code Agent Teams implements level 3 with a shared task list, file-locked claiming, mailboxes for direct and broadcast messages, and idle notifications back to the lead. +Codex 0.117 introduced path-based agent addressing and structured inter-agent messaging for its multi-agent workflows. + ## The Code Factory pattern Beyond specific products, there is an emerging pattern popularized by Ryan Carson under the name **Code Factory**. From 0d9d56fc1b110b06cdb203d4ac159c0d5e8ddea3 Mon Sep 17 00:00:00 2001 From: Marek Kaput Date: Wed, 8 Apr 2026 07:29:24 +0200 Subject: [PATCH 6/9] fix grammar in agent communication docs --- .../docs/expanding-horizons/high-level-harnesses.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 83d8509..73afb0f 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -78,10 +78,10 @@ Issue-tracker-driven orchestration works best on codebases that have adopted [ha ## Agent communication -Running multiple agents in parallel may cause coordination problem — agents must exchange information without overloading any one context window. +Running multiple agents in parallel may create coordination problems — agents must exchange information without overloading any one context window. Two broad patterns have emerged. -The simpler one is **hub-and-spoke orchestration**, where a lead agent spawns workers, collects their outputs, and consolidates. +The simpler one is **hub-and-spoke orchestration**, where a lead agent spawns workers, collects their outputs, and consolidates them. Workers never communicate directly. The benefit is simplicity, as the full picture is present in one place. The cost is that every intermediate result, log line, and failed attempt flows back through the orchestrator's context, degrading its reasoning quality over time. @@ -97,7 +97,7 @@ In practice, most pipelines fall somewhere on a spectrum between these extremes, 3. **Collaborative teams** — agents share a task graph, can send direct or broadcast messages, and notify the lead when work completes. The right level depends on how tightly coupled the tasks are. -Independent parallel tasks — security scan, test run, lint check — fit level 1 or 2 well. +Independent parallel tasks — security scans, test runs, lint checks — fit level 1 or 2 well. Tasks that need to challenge or build on each other's intermediate findings call for level 3. For reference, Claude Code Agent Teams implements level 3 with a shared task list, file-locked claiming, mailboxes for direct and broadcast messages, and idle notifications back to the lead. From 011fb9160b19c4243976594ec18542ef11a886ee Mon Sep 17 00:00:00 2001 From: Marek Kaput Date: Wed, 8 Apr 2026 07:31:11 +0200 Subject: [PATCH 7/9] Update src/content/docs/expanding-horizons/high-level-harnesses.mdx Signed-off-by: Marek Kaput --- src/content/docs/expanding-horizons/high-level-harnesses.mdx | 4 ---- 1 file changed, 4 deletions(-) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 73afb0f..7b78f2c 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -8,10 +8,6 @@ import ExternalLink from "../../../components/ExternalLink.astro"; The [harness engineering](/becoming-productive/harness-engineering/) chapter covered shaping a single agent's actions through AGENTS.md, skills, hooks, and subagents. This page is one level of abstraction up — it covers tools and patterns that treat agents as a manageable workforce. -:::caution -Products and feature sets can change significantly between revisions of this guide. -Treat this page as an orientation, especially for building a solid intuition of the field, not a definitive reference. -::: ## From engineering to managing From 05ef2103bf962112a8cad2d954fc1e354609a34b Mon Sep 17 00:00:00 2001 From: Marek Kaput Date: Wed, 8 Apr 2026 07:39:15 +0200 Subject: [PATCH 8/9] more redactions --- .../docs/expanding-horizons/high-level-harnesses.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 7b78f2c..4d3b72e 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -11,7 +11,7 @@ This page is one level of abstraction up — it covers tools and patterns that t ## From engineering to managing -So far in this guide, you have been an **engineer** — you worked interactively with a single agent, steering it turn by turn in real time. +So far in this guide, you have been an **engineer** — you have worked interactively with a single agent, steering it turn by turn in real time. Now, you will become a **manager**, delegating work to a fleet of agents running in parallel. Instead of supervising each agent individually, you will manage the output queue — a review inbox, an issue tracker, a PR pipeline. Your coding assistant no longer serves as a conductor, but as an orchestrator. @@ -32,7 +32,7 @@ You as the human still trigger one top-level session and review one result. What is described here is different: **you** spawn multiple fully independent agent sessions, each assigned to a separate task. No session knows about the others. -You are not waiting on any one of them — you come back later and review the queue of results in bulk. +You do not need to wait for any single agent — you come back later and review the queue of results in bulk. In practice, each agent needs its own isolated workspace — typically a separate Git worktree — so their changes do not interfere. A dashboard or queue then surfaces results as agents finish, letting you review and merge at your own pace. @@ -128,7 +128,7 @@ The Code Factory pattern is the technical foundation of a broader idea: that a s This requires connecting agents to communication platforms, scheduling systems, and external services — turning a single machine into an always-on runtime that responds to messages, executes tasks, and ships work continuously. As an example of tooling in this space, see OpenClaw, which packages infrastructure for exactly this kind of setup. -Steve Yegge, in a widely-read interview with The Pragmatic Engineer, argues that the engineering profession is reorganizing around exactly this spectrum. +Steve Yegge, in a widely read interview with The Pragmatic Engineer, argues that the engineering profession is reorganizing around exactly this spectrum. His framing: most engineers are at the low end of AI adoption today, and those who stay there risk being outcompeted by engineers who learn to orchestrate agent fleets — to act as owners of work queues rather than writers of individual functions. - From 22ffcb0fb9d28288fcc1dfe5423fac26edb1a4b3 Mon Sep 17 00:00:00 2001 From: Marek Kaput Date: Wed, 8 Apr 2026 08:15:43 +0200 Subject: [PATCH 9/9] a round of Marek's redactions --- .../high-level-harnesses.mdx | 24 +++++++++---------- src/data/links.csv | 14 ++++++----- 2 files changed, 20 insertions(+), 18 deletions(-) diff --git a/src/content/docs/expanding-horizons/high-level-harnesses.mdx b/src/content/docs/expanding-horizons/high-level-harnesses.mdx index 4d3b72e..4cc0f4f 100644 --- a/src/content/docs/expanding-horizons/high-level-harnesses.mdx +++ b/src/content/docs/expanding-horizons/high-level-harnesses.mdx @@ -37,7 +37,7 @@ You do not need to wait for any single agent — you come back later and review In practice, each agent needs its own isolated workspace — typically a separate Git worktree — so their changes do not interfere. A dashboard or queue then surfaces results as agents finish, letting you review and merge at your own pace. -For example, Conductor is a tool built around this model, +For example, is a tool built around this model, running multiple AI coding agents (Claude Code and Codex) in parallel worktrees with a shared review dashboard. ## Scheduled and recurring agents @@ -54,7 +54,10 @@ This is well-suited for tasks like: With scheduled agents, the process becomes closer to a CI pipeline than a chat window — an agent is no longer a tool you reach for, but a background process. -As an example, OpenAI's Codex App includes an Automations feature built around exactly this model. +Example application features built around this pattern: +- +- +- ## Issue-tracker-driven orchestration @@ -65,7 +68,7 @@ Engineers decide what issues belong in scope; the orchestrator handles assignmen Agent behavior can be defined in a workflow file versioned alongside the code — the same way you version a CI pipeline. When an agent finishes, it gathers evidence (CI results, PR review feedback, complexity analysis) for human review. -For example, Symphony is an open-source orchestration service published by OpenAI that implements this pattern, +For example, is an open-source orchestration service that implements this pattern, monitoring a Linear board and running a Codex agent per issue in an isolated workspace. :::tip @@ -96,10 +99,9 @@ The right level depends on how tightly coupled the tasks are. Independent parallel tasks — security scans, test runs, lint checks — fit level 1 or 2 well. Tasks that need to challenge or build on each other's intermediate findings call for level 3. -For reference, Claude Code Agent Teams implements level 3 with a shared task list, file-locked claiming, mailboxes for direct and broadcast messages, and idle notifications back to the lead. -Codex 0.117 introduced path-based agent addressing and structured inter-agent messaging for its multi-agent workflows. +For reference, implements level 3 with a shared task list, file-locked claiming, mailboxes for direct and broadcast messages, and idle notifications back to the lead. -## The Code Factory pattern +## Code factories Beyond specific products, there is an emerging pattern popularized by Ryan Carson under the name **Code Factory**. The idea is a repository setup where agents autonomously write code, open pull requests, and a separate review agent validates those PRs with machine-verifiable evidence. @@ -121,14 +123,12 @@ Invest in solid tests, linters, and CI before automating the merge step. - -## The one-human company +## One-human companies -The Code Factory pattern is the technical foundation of a broader idea: that a single person with a well-configured agent fleet can operate at the scale that would previously have required a full engineering team. +The code factory pattern is the technical foundation of a broader idea: that a single person with a well-configured agent fleet can operate at the scale that would previously have required a full engineering team. This requires connecting agents to communication platforms, scheduling systems, and external services — turning a single machine into an always-on runtime that responds to messages, executes tasks, and ships work continuously. -As an example of tooling in this space, see OpenClaw, which packages infrastructure for exactly this kind of setup. +As an example of tooling in this space, packages infrastructure for exactly this kind of setup. -Steve Yegge, in a widely read interview with The Pragmatic Engineer, argues that the engineering profession is reorganizing around exactly this spectrum. +In , Yegge argues that the engineering profession is reorganizing around exactly this spectrum. His framing: most engineers are at the low end of AI adoption today, and those who stay there risk being outcompeted by engineers who learn to orchestrate agent fleets — to act as owners of work queues rather than writers of individual functions. - -- diff --git a/src/data/links.csv b/src/data/links.csv index ecea782..04eaceb 100644 --- a/src/data/links.csv +++ b/src/data/links.csv @@ -19,19 +19,21 @@ https://claude.com/plugins/playground,Playground Claude Plugin,Anthropic,,2026-0 https://claude.com/pricing,Claude Subscription,,,2026-03-04 https://cli.github.com/,GitHub CLI | Take GitHub to the command line,,,2026-03-13 https://cline.bot/blog/post-mortem-unauthorized-cline-cli-npm,Unauthorized Cline CLI npm publish,Saoud Rizwan,2026-02-24,2026-03-16 +https://code.claude.com/docs/en/agent-teams,Claude Code Agent Teams,Anthropic,,2026-04-08 https://code.claude.com/docs/en/best-practices#write-an-effective-claude-md,Best Practices for Claude Code - Claude Code Docs,Anthropic,,2026-03-04 https://code.claude.com/docs/en/hooks,Hooks reference - Claude Code Docs,Anthropic,,2026-03-13 https://code.claude.com/docs/en/security,Security - Claude Code Docs,Anthropic,,2026-03-16 https://code.claude.com/docs/en/sub-agents,Create custom subagents - Claude Code Docs,Anthropic,,2026-03-13 https://code.claude.com/docs/en/sub-agents#code-reviewer,Create custom subagents - Claude Code Docs,,,2026-03-05 https://coderabbit.ai/,CodeRabbit,,,2026-03-05 -https://conductor.build/,Conductor - Run a team of coding agents on your Mac,Melty Labs,,2026-03-25 +https://conductor.build/,Conductor,Melty Labs,,2026-03-25 https://context7.com/,Context7 - Up-to-date documentation for LLMs and AI code editors,,,2026-03-13 https://cursor.com/blog,Cursor Blog,,,2026-03-04 https://cursor.com/bugbot,Cursor Bugbot,,,2026-03-05 https://cursor.com/docs/agent/browser,Cursor Browser,,,2026-03-04 https://cursor.com/docs/agent/modes#debug,Cursor Debug Mode,,,2026-03-04 https://cursor.com/docs/agent/review,Cursor Review Agent,,,2026-03-04 +https://cursor.com/docs/cloud-agent/automations,Cloud Agents Automations,Cursor,,2026-04-08 https://cursor.com/docs/context/rules,Cursor Rules,,,2026-03-04 https://cursor.com/docs/hooks,Hooks Docs,Cursor,,2026-03-13 https://cursor.com/docs/subagents,Cursor Subagents,Cursor,,2026-03-13 @@ -39,8 +41,7 @@ https://cursor.com/for/code-review,Reviewing Code with Cursor | Cursor Docs,,,20 https://cursor.com/pricing,Cursor Subscription,,,2026-03-04 https://developers.openai.com/api/docs/guides/compaction,Compaction,OpenAI,,2026-03-04 https://developers.openai.com/codex/agent-approvals-security,Codex: Agent approvals & security,OpenAI,,2026-03-16 -https://developers.openai.com/codex/app,App – Codex | OpenAI Developers,,,2026-03-25 -https://developers.openai.com/codex/app/automations,Automations – Codex app | OpenAI Developers,,,2026-03-25 +https://developers.openai.com/codex/app/automations,Automations in Codex app,OpenAI,,2026-03-25 https://developers.openai.com/codex/app/worktrees/#working-between-local-and-worktree,Worktrees,,,2026-03-10 https://developers.openai.com/codex/cli/features#run-local-code-review,Codex CLI features (run local code review),,,2026-03-05 https://developers.openai.com/codex/integrations/github/,Use Codex in GitHub,,,2026-03-05 @@ -59,7 +60,7 @@ https://github.com/mcp,GitHub MCP Registry,,,2026-03-13 https://github.com/microsoft/playwright-mcp,microsoft/playwright-mcp,Microsoft,,2026-03-13 https://github.com/mkaput,Marek Kaput,,,2026-03-04 https://github.com/openai/skills,openai/skills,OpenAI,,2026-03-12 -https://github.com/openai/symphony,"GitHub - openai/symphony: Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents. · GitHub",,,2026-03-25 +https://github.com/openai/symphony,Symphony,OpenAI,,2026-03-25 https://github.com/software-mansion-labs/skills,software-mansion-labs/skills,Software Mansion,,2026-03-12 https://github.com/steipete/mcporter/,"steipete/mcporter: Call MCPs via TypeScript, masquerading as simple TypeScript API. Or package them as cli.",Peter Steinberger,,2026-03-04 https://github.com/topics/agent-skills,GitHub Topic: agent-skills,,,2026-03-12 @@ -77,11 +78,11 @@ https://lucumr.pocoo.org/,Thoughts and Writings,Armin Ronacher,,2026-03-04 https://mcp.grep.app/,mcp.grep.app,Vercel,,2026-03-04 https://mitchellh.com/,Blog,Mitchell Hashimoto,,2026-03-04 https://models.dev/,Models.dev - An open-source database of AI models,Opencode,,2026-03-04 -https://newsletter.pragmaticengineer.com/p/from-ides-to-ai-agents-with-steve,From IDEs to AI Agents with Steve Yegge - by Gergely Orosz,,,2026-03-25 +https://newsletter.pragmaticengineer.com/p/from-ides-to-ai-agents-with-steve,From IDEs to AI Agents with Steve Yegge,Gergely Orosz,,2026-03-25 https://openai.com/chatgpt/pricing/,ChatGPT Subscription,,,2026-03-04 https://openai.com/index/harness-engineering/,Harness engineering: leveraging Codex in an agent-first world,OpenAI,2026-02-11,2026-03-04 https://openai.com/news/engineering/,OpenAI Engineering News,,,2026-03-04 -https://openclaw.ai/,OpenClaw — Personal AI Assistant,,,2026-04-02 +https://openclaw.ai/,OpenClaw,Peter Steinberger,,2026-04-02 https://opencode.ai/docs/go/,Opencode Go,,,2026-03-04 https://platform.claude.com/docs/en/build-with-claude/compaction,Compaction,Anthropic,,2026-03-04 https://platform.claude.com/docs/en/resources/prompt-library/socratic-sage,Prompting best practices,Anthropic,,2026-03-04 @@ -101,6 +102,7 @@ https://skills.sh/mitsuhiko/agent-stuff/tmux,tmux skill,Armin Ronacher,2026-01-2 https://skills.sh/vercel-labs/agent-browser/agent-browser,agent-browser,Vercel,2026-01-16,2026-03-04 https://skills.sh/vercel-labs/agent-skills/vercel-react-best-practices,vercel-react-best-practices skill,Vercel,2026-01-16,2026-03-04 https://support.apple.com/guide/mac-help/mh40584/mac,Dictate messages and documents on Mac - Apple Support,,,2026-03-10 +https://support.claude.com/en/articles/13854387-schedule-recurring-tasks-in-cowork,Schedule recurring tasks in Cowork,Anthropic,,2026-04-08 https://support.microsoft.com/en-us/windows/use-voice-typing-to-talk-instead-of-type-on-your-pc-fec94565-c4bd-329d-e59a-af033fa5689f,Use voice typing to talk instead of type on your PC - Microsoft Support,,,2026-03-10 https://swmansion.com/,Software Mansion,,,2026-03-04 https://tidewave.ai/,Tidewave,,,2026-03-04