Every operator I know has the same pile by now: three or four agents running somewhere, no shared memory, no shared budget, nobody watching the whole board. Paperclip is the first tool I've seen treat that pile as the actual problem. It doesn't give you another agent. It gives the agents you already have a manager.
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The Drops
Repopaperclip
100,970 stars · paperclipai/paperclip
An open-source orchestration layer that manages a team of AI agents the way you'd manage a company, not a pipeline.
Here is the real problem it solves. Once you're running more than one agent, the hard part stops being prompts and starts being coordination. Who's doing what, what it costs, whether it's actually aligned to the goal you set. Paperclip gives every agent a role, a budget, and a reporting line, and gives you one dashboard to watch all of it.
Quick start: clone the repo, define a goal in plain language, then assign agents to it from any harness you already run (OpenClaw, Claude Code, Codex, Cursor, Gemini CLI, and others plug straight in).
Catch: this is infrastructure for a team of agents, not a single assistant. If you're running one agent on one task, you don't need a company, you need a to-do list.
AffiliateHubSpot
HubSpot, a CRM where AI agents work on the customer record your team already keeps. A Customer Agent answers support, a Prospecting Agent researches and drafts outreach, a Data Agent cleans what sits underneath, and you can build your own on one canvas from your prompts and CRM data. The CRM underneath has a free tier.
Use it for: putting support, prospecting and data-cleanup agents on the record your team already keeps.
We may earn a commission.
Repowshobson/agents
40,509 stars · wshobson/agents
A multi-harness plugin marketplace: one set of agents, skills, and commands that runs across Claude Code, Codex, Cursor, OpenCode, Copilot, and more.
Use it for: stop rebuilding the same code-review or testing skill for every harness your team happens to use. 202 agents and 184 skills, installed once, portable everywhere.
Catch: the catalog is big enough that picking the right plugin takes real browsing. Budget ten minutes before you expect to be productive.
ToolOpenHands Agent Canvas
90,750 stars · OpenHands/OpenHands
A self-hosted control center that runs OpenHands, Claude Code, Codex, Gemini, Pi, OpenCode, or any ACP-compatible agent across local, remote, and cloud backends.
Use it for: if Paperclip is the org chart, this is the machine room, one place to start conversations and automate recurring jobs like turning a GitHub issue into a task queue.
Catch: runs locally by default, but the useful stuff (Docker containers, VMs, cloud backends) takes setup before it pays off.
Repowheresryan22/anatomy
6,253 stars · wheresryan22/anatomy
A Claude skill that explains a technical idea by building it as an interactive isometric illustration instead of a paragraph.
Use it for: ask it to explain a rate limiter or a cache key, and it hands back a working animated diagram instead of prose. Runs in OpenCode and Codex too, no API key required.
Catch: it's a presentation layer, not a debugging tool. Great for explaining a system to a teammate, not for finding the bug in it.
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Start Here
Which jobs to hand to a machine, and which to keep.
One prompt today instead of a how-to. It is one of ours, tested on ChatGPT and Claude. Copy it, paste it into the free app you already use, and fill in the three bits in capitals with your own jobs and your own rough times.
The jobs I do over and over, with roughly how long each takes and how often: [THE JOBS YOU DO AGAIN AND AGAIN, ONE PER LINE, WITH ROUGHLY HOW LONG EACH TAKES AND HOW OFTEN]
What already goes wrong when one of them is done badly: [WHAT ALREADY HAPPENS WHEN ONE IS DONE BADLY]
Who would notice a quiet mistake, and how long that would take: [WHO WOULD SPOT A QUIET MISTAKE, AND HOW LONG THAT WOULD TAKE]
Give me, in this order:
1. The payoff, job by job. How long it takes, multiplied by how often, using only the figures I gave you, with the arithmetic shown on the line. Where I gave no time, write time not supplied. Where I gave no frequency, write how often not supplied. Leave the payoff off those lines rather than estimating it.
2. Four questions per job, answered short. Does it come out the same way every time, or does it change. What would it cost me if it went wrong and nobody spotted it for a week. How often does something odd turn up that a person has to stop and think about. Does anybody outside the business see the result.
3. The four piles, with every job I listed in exactly one of them.
Hand it over now: worth the time, the same every time, and a mistake would get spotted.
Hand it over with somebody checking: worth the time, but a quiet mistake is expensive, so a person looks before it leaves.
Fix the job first: the job itself is a mess, and doing a mess faster is worse than doing it slowly.
Keep doing it yourself: not worth the time it saves, or the judgement is the whole job.
4. The one I will want to automate and should not, named out of my own list, with the reason in a sentence I would repeat to somebody else.
5. What of this came from general knowledge. Anything you said about how a job of this kind usually behaves, rather than from what I told you, listed and marked as general knowledge for me to check.
Rules. Work only from the jobs I listed. Do not name a tool, an app or a service; this is about which jobs, not about what to buy. Do not invent a time or a frequency I did not give you, and do not tell me how many hours a week I would save unless every figure in that sum came from me. If I wrote "nothing goes wrong", ask me what a bad one would look like rather than treating the job as safe, and say which piles that answer would move. If I wrote "nobody would notice", no job on my list goes in hand it over now; the best it can do is hand it over with somebody checking, and say why. Before you sort anything, if a job on my list happens fewer than a handful of times a year, say so and put it straight in keep doing it yourself.
The line that makes it work: do not invent a time or a frequency I did not give you. Most "what should I automate" answers promise hours back off numbers nobody supplied. This one only multiplies figures you gave it, so the job that feels worth automating and the job that actually is stop looking like the same job.
TRY THIS: list the five things you did on Monday that you also did last Monday, with a rough time next to each, and see which one lands in keep doing it yourself.
This is one of 100 in the AIgent prompt pack. The other 99, plus guided builds with Mike on video, are inside the AIgent membership, dropping this week.
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Recommended
Sorting which jobs to hand off is half of it. The other half is knowing which tools are worth handing them to, which is the whole case for a second set of eyes that already scans the tool landscape so you don't have to. AI Chief, the newsletter on the AI tools worth your time rounds up the tools and breakthroughs that save you time so you stay sharp without reading everything yourself, free to subscribe. We may earn a commission. |

Frontier Signals
Meta shipped its first frontier model, and kept the strongest version off the API. Muse Wonder lands on Meta's API at $4 per million input tokens, the same rate as Claude Opus 5.5, while the stronger Wonder Full stays inside a paid Muse Code subscription. (VentureBeat)
Anthropic is giving Claude the ability to split itself into a maintainer hierarchy for big projects. "Dynamic workflows," announced Friday and walked through at AI Engineer NYC, let one agent delegate across layers the way Linux moved from Linus Torvalds to trusted maintainers, built for workloads too big for a single context window. (Latent Space)
Asana cut its browser-agent model costs 76x and ran 5x faster, using GPT-6 Astra in Codex to retune the workflow onto GPT-6.1 Sol. Average cost per run landed at 47 cents. If your agent spend is still running on last quarter's model, this is the number that says go check. (OpenAI Blog)
Python 3.15 shipped with explicit lazy imports, letting you write lazy import json so a module only loads the moment you actually use it. Useful immediately if you ship a CLI or plugin system with heavy, rarely-used dependencies. (Simon Willison)
PC shipments fell 20.1% year over year, the sharpest drop since early 2023, with desktops down 23.5% and laptops down 20.6%. Vendors stocked up earlier in the year ahead of memory price hikes, and high prices are now holding demand down. (Ars Technica)
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Before You Go
What's managing your agents right now, a spreadsheet, a Slack channel, or nothing at all? Reply and tell me, I read every one.
See you Wednesday.
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