Sep 21 (edited) • Agents on Autopilot
Orchestrating 24/7 Production
This section is dedicated to creating self-driving systems. We support you in creating assembly lines, producing real pipeline, drive real revenue, and create real opportunity.
How we do this is by incorporating a few frameworks that seem small, but actually take a decent degree of development resources. However, in the stride of keeping this friendly for non-technical, I'll keep this high level. If you want to see how this exists on a more technical level, our resources in the classroom go into this.
This is deeply simplified. I've worked with one of the biggest Medicare providers in Philadelphia, servicing a tax firm sales director with over 4 teams relying on the infrastructure I've set up, and numerous other examples, illustrate one point.
80% of the process is sharpening the axe in advance. That's the majority of what we do, compressing the time to see desirable results into days instead of weeks and months.
1) The Red Team
A red team is your friendly adversary. It tries to break your automations before real customers do, it does by stress-testing edge cases (leaks, broken selectors, CAPTCHAs, error message handling, and hallucination).
It validates the guardrails that we set up in advance, keeps human-in-the-loop feedback gates, run logs and usage.
Without red-teaming, you ship brittle flows (which you'd experience using RPA and no code tools without consideration). If you discover these failures early on, you ship resilient systems that fail safely, stay on budget, and produce clean audit trails for troubleshooting.
This is the baseline for trust.
2) Prompt Chains, Workbenches, and Cards
Manus.im was an early practitioner of this concept, and opened my mind to how to efficiently see success with browser agents in a repeatable fashion.
If you're technical, this is where the path diverges because you can truly just hard code a Python and Puppeteer script, see 90% of the results that I'm about to share.
Prompt Chains: If you prompt a series of LLMs 100x over, you'll end up with the top 10 prompts that get you the result you need. These are crafted by hard working specialists, and they often hold these close to their chest as the bread and butter for what they do.
I'll have the ones we're using available in the Link Hub. Same goes for the rest of the resources mentioned here.
Workbench: A GPT project of any stretch is what this is. It's a central location that all your context goes through that a LLM can reach and reference. Without this, hallucinations go up significantly. Everything should have a reference point to cite, data drives results. This is a prerequisite, not an option. Hallucinations will bite you for not having this. The 1% outliers making money with AI reliably have project spaces and workspaces they can reference, don't skip this.
Cards: These are a newer phenomenon, and only really matter to an educator. In order for someone to get the 80/20 of what works, condensing information into digestibility needs to happen at every step.
That's why we have Agent Cards, which function as agent profiles. Run Cards, which track run logs and budget/usage so we have visibility. Then we have Lab Cards, which are like mini-workshops and tools you can use on your journey as a learning resource.
3) The Production
Detailed roadmaps exist depending on your industry, vertical and use case. To start, I've crafted these in a way I can speak to (available in the Link Hub under orientation and program map).
These will only expand as we iterate and grow on top of them month by month.
AI should not be operating 24/7 in a dark room with nobody watching it, especially with the rampant risk of displacement. My goal with this community and program is to create an evergreen resource that will inspire, inform, and support initiatives that map accessibility around the empowerment that AI is capable of.
Thank you for joining myself and other fellow Citizen Developers as we explore how to integrate this digital workforce into our lives meaningfully.
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Orchestrating 24/7 Production
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