most people want an AI that can operate autonomously
they want it to make every decision, handle entire workflows, and figure everything out without guidance
the result is different outputs every time with little consistency
when an AI makes all decisions, you get random results
ask Cursor to "build a customer service chatbot" 10 times and you'll get 10 completely different solutions
but with automating business tasks you need predictability
the right way: map out how YOU do the task manually first
write it like training instructions for a dipshit intern
every decision point, every step in order
here's an example with cold email reply management:
step 1: reply comes in you read it
step 2: categorize response type (interested / not interested / wrong person / bad timing)
step 3: if interested - ask for their availability
step 4: check if their suggested time matches your calendar
if available - send calendar invite
if not available - follow up with open times
notice there are multiple decision points here:
first categorization: what type of response?
second categorization: does timing work?
each decision has clear options and next steps
now here's where AI fits in:
don't ask an AI to design this entire process as everyone has their own unique processes
but you can ask it to make specific choices at each decision point
for cold email reply management that’s going to be:
"what type of response is this:
> interested
> not interested
> wrong person
> bad timing?
"
then route to your predetermined next action based on the category
for the second decision point:
"does their suggested Tuesday 2pm conflict with my calendar? yes or no?"
if yes - send alternative times template
if no - send calendar invite
to recap this framework for building reliable AI systems:
> map out your manual process step by step
> identify each decision point in the workflow
> turn decisions into clear categories for AI to choose from
> let AI categorize and route, not create
all you’re doing is designing the process and the AI helps route everything
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how to give an AI agent memory to make it smarter over time:
most AI system treats every conversation like it's meeting you for the first time
for example a customer first complains about a broken chair, then the AI responds like it's a new issue
but the same customer complains about another broken chair 2 months later
but in most cases an AI system still treats it like a new convo and acts like it's never happened before
what an AI with memory would do:
"Hello David, following up on your previous case from August where you experienced issues with an ergonomic chair, I sincerely apologize this is happening again. We appreciate your continued trust since 2023..."
it references past interactions and treats customers like actual humans
here's everything you need to make money with AI (the only 2 paths that actually work):
there are only two ways to make money with AI
most people get confused because they see all the time on twitter about how people are making six figures with this automation or using this tool and shit like that
but when you strip away all the noise, it comes down to just these two paths
path 1: use AI to amplify what you're already good at
this is for 90% of you reading this
if you're decent at copywriting, sales, paid ads, whatever - don't abandon that to become an "AI expert"
instead, use AI to make you 10x better at what you already do
here's everything you need to build and deploy AI apps in hours (complete beginner's guide):
most people think you need years of coding experience to build apps
but with AI tools doing the heavy lifting, you can go from idea to deployed app in a single day
the key is using the right stack and approach
here's the vibe coding stack I usually recommend for beginners:
> planning with ChatGPT/Claude
> coding with Cursor and Sonnet 4
> storing data with Supabase
> handling user logins with Clerk
> deploying with Vercel or Railway