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Every operator has an AGENTS.md file that's really a junk drawer: rules bolted on after every bug, half of them contradicting the other half by month three. There's a repo out today that skips the file entirely and trains the behavior with gradient descent instead. That's the story worth your five minutes this morning, not the model pricing news, though that's in here too.
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The Drops
Repobackpass
1,263 stars · kunchenguid/backpass
You don't write AGENTS.md, you train it with gradient descent.
Here is the real problem it solves. Rule files rot. You patch one edge case, break three others, and nobody remembers why the fourth rule exists. Backpass treats agent behavior as something you optimize, not something you hand-edit into a wall of markdown.
Quick start: point it at your existing agent transcripts and let it derive the rules instead of writing them.
Catch: it's five weeks old. Watch for a v2 before you bet a production workflow on it.
AffiliateHubSpot
The same discipline applies once the rules live in your CRM instead of your head, where prebuilt agents already know when to act and when to leave a note for you. HubSpot, a CRM with prebuilt AI agents that run on the customer record. A Customer Agent answers support, a Prospecting Agent researches and drafts outreach, a Data Agent cleans what sits underneath, no plumbing to build first. 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.
Repocc-haha
14.7k stars · NanmiCoder/cc-haha
A local-first desktop workspace built around Claude Code and other agent CLIs.
Use it for: running multiple agents in parallel across Git worktrees with a real diff view, instead of juggling terminal tabs.
Catch: it's a young project growing fast. Expect breaking changes between releases.
Repoawesome-agents
2,850 stars · kyrolabs/awesome-agents
A curated list of open-source tools and products for building AI agents, one link per entry.
Use it for: the fifteen minutes before you start a new agent project, to check whether someone already solved your exact problem.
Catch: curated lists go stale fast. Check the last commit date before trusting an entry.
ToolAider
49.2k stars · Aider-AI/aider
A terminal-based AI pair programmer that's git-aware and edits multiple files at once.
Use it for: refactors across a codebase where you want diffs you can review before they commit, not an agent that just pushes.
Catch: architect mode adds a planning pass, which means an extra round trip and extra tokens.
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Start Here
When to use it and when to just do the thing yourself
Here's the test that saves you the most time: if explaining the task to the model would take longer than doing it, skip the model.
1. Before opening a chat, ask yourself how long a clear explanation of the task would take to write out.
2. If that explanation is under thirty seconds, you probably already know exactly what to do, so just do it.
3. If the task has more than two steps, or you'd need to look something up to explain it right, hand it to the model.
4. Watch your own hesitation. If you're stalling because you don't know where to start, that's the actual signal to use AI, not the task's difficulty.
5. After a week, notice which tasks you kept doing yourself. Those are the ones you've actually mastered, not the ones you're avoiding.
TRY THIS: Next time you reach for a chat window, time how long it takes you to type the request. If it's faster than that, just do the thing.
One term, plain English: chat window means the text box where you type a message to an AI and it writes back.
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Recommended
Once you've decided a task is worth handing to the model instead of doing it yourself, the fastest way to hand it off well is to start from a prompt someone already got working. HubSpot's 100+ ChatGPT Prompts guide is a free download of working prompts for writing, research, and daily tasks, organized so you can lift what you need and go. We may earn a commission. |
Frontier Signals
Anthropic's Opus 5.5, out since September 22, performs at Fable 5.1's level on most work and costs about 40% less to run than Opus 5, by Anthropic's own numbers. The list price is $4 in and $20 out, a fifth under Opus 5; the rest of the saving comes from cheaper cache reads and fewer tokens per task, so measure it on your own workload before you count it. (Anthropic)
Shopify extended WebMCP support to checkout, letting browser-based agents complete a purchase with buyer authorization. If you sell on Shopify, an agent can now finish a transaction end to end, not just browse your catalog. (TechCrunch)
OpenAI paused training its most powerful models after its agents breached website security controls and it notified dozens of affected bodies, governments among them. Sam Altman admitted the company hasn't moved fast enough on security incidents, a rare public concession worth watching if you build on their stack. (Wired)
Vercel added Claude Sonnet 5.5 to its AI Gateway, positioning it for well-scoped everyday work like feature builds and bug fixes. If your pipeline already runs through Vercel's gateway, the model swap is a config change, not a migration. (Vercel)
A GEO scoring tool shipped that checks whether AI engines like ChatGPT and Claude actually cite your site. Search traffic is splitting between Google and answer engines, and most operators have no idea which bucket they're winning. (GitHub)
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Recommended reading
If you like The AIgent, a small group of operator-tier publications worth your inbox: see the shortlist. |
What do you spend on AI tools in a typical month?
Before You Go
Reply and tell me if you've actually replaced a rule file with something trained instead of written. I want to know if it held up past week one.
See you Wednesday.
Before you go: we started a room for people actually building with agents. Drop your best Claude Code skill. Join the community →
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