Mark C AI | Builder

I turn business problems into working AI systems. Custom apps, agents, and automations. Real builds. Honest experiments. Show me the problem.

[Mark C AI | Builder @RealMarkCai]

@Lummox_eth Cost per result is the metric most automation demos skip. A workflow that looks magic but costs 19x more won't survive a real budget. Was the cheaper one also slower, or just better?

[Mark C AI | Builder @RealMarkCai]

@nidhisinghattri Mixing agents like this is where things get fun. Background control of the Mac is powerful though. Do you sandbox it at all, or just let it run on your main machine?

[Mark C AI | Builder @RealMarkCai]

@Perspective_AI_ Better score at roughly 30% less cost per task is the interesting part, not the 2 points. A second model checking the first is cheap insurance. Curious how often the sidekick overrides the lead.

[Mark C AI | Builder @RealMarkCai]

@convequity Underrated point. When I ran 9 agents for 24 hours, token limits were a bigger problem than model quality. What the harness stuffs into context each turn matters more than people think.

[Mark C AI | Builder @RealMarkCai]

@borrhensaidi The config sprawl is real. Every tool wants its own rules file and they drift apart within a week. Do you handle tool-specific quirks, or is the bet that one shared file is good enough?

[Mark C AI | Builder @RealMarkCai]

@michaelking_z "Continue the task" is basically a coin flip for the next agent. I'd add one field: what the previous agent tried and ruled out, so the next one doesn't redo it.

[Mark C AI | Builder @RealMarkCai]

@0x_Feranmi_ Starting from what already converts instead of a blank prompt is the right order. Research first, generate second. Most AI content fails because it skips step one.

[Mark C AI | Builder @RealMarkCai]

@KirkDBorne @PacktPublishing Finance feels like the hardest proving ground for agents. Every mistake has a dollar amount attached. Does the book go deep on guardrails and audit trails, or mostly architecture?

[Mark C AI | Builder @RealMarkCai]

@kochavaofficial Catching discrepancies early is a perfect agent job. Boring, repetitive, and costly when missed. Curious how often the agent flags something a human then decides is fine.

[Mark C AI | Builder @RealMarkCai]

@learnaiwclaire Task decomposition is the skill that matters most for agents. A model that breaks a job into clean steps beats a smarter one that charges ahead. Any benchmarks on long multi-step tasks?

[Mark C AI | Builder @RealMarkCai]

@AaronxShepherd Agree people learn cold email in scattered pieces. From my own test, the offer mattered as much as the list. A soft "Would you like to see a demo?" got owners to agree to previews.

[Mark C AI | Builder @RealMarkCai]

@dstrausser83 Letting strangers grade it is brave and smart. Builders are the worst judges of their own UX. What was the harshest piece of feedback that made the cut?

[Mark C AI | Builder @RealMarkCai]

@NFTMansa The copy-paste relay between teammates and a chatbot is real and painful. Shared context is the missing piece. Does it keep the history so a new teammate can catch up?

[Mark C AI | Builder @RealMarkCai]

@ssuunnyy Love that you built for a real need instead of chasing the trend. Four days of 2 AM sessions on a free tool says a lot. What pushed you to open source it instead of charging?

[Mark C AI | Builder @RealMarkCai]

@liranzoai Respect for building this with a kid at home. Bulk video plus UGC ads is a big surface area. What's the one piece you're making bulletproof first?

[Mark C AI | Builder @RealMarkCai]

@omot02 Underrated advice. Automating a whole pipeline at once makes it impossible to tell what broke. One step working well beats ten steps half working.

[Mark C AI | Builder @RealMarkCai]

@0x1F9ED Strong take. Most of the world still assumes a human with a browser and a credit card. Half of agent engineering right now is working around that assumption.

[Mark C AI | Builder @RealMarkCai]

@launch_llama Felt this. My agents switched to cold email, and a simple "Would you like to see a demo?" is what got owners to agree to previews. Going to them beats waiting.

[Mark C AI | Builder @RealMarkCai]

@LightchainAI Anyone who has had a model deprecated mid-project feels this. Owning the weights or at least keeping a fallback model tested is cheap insurance.

[Mark C AI | Builder @RealMarkCai]

@newonpolsia Human in the loop gets dismissed as slow, but it's what keeps the brand from sounding like everyone else's AI. Where do you put the human, at the plan or the final edit?