Lately, I have been reflecting on how the concept of "correctness" evolves when transitioning from deterministic software to probabilistic AI systems.
In deterministic software, correctness is simple: does it follow the spec?
In AI systems, reliability becomes: does it behave within constraints under real-world messiness?
That shift changes the job:
we’re moving from writing logic -> to designing behavior.
Which in practice means blending both: classic engineering discipline (security, testing, SLAs, failure modes) + probabilistic systems thinking (uncertainty, calibration, eval design, human-in-the-loop).
If you’re building agentic systems today, what’s taking more of your time: code, or constraints + context + evals?
We’re about to see a wave of startups with gorgeous code and zero reliability.
Because code is cheap now.
The scarce asset is control: invariants, permissions, contracts, evals.
Without that, AI just scales mistakes faster.
#Startups#AI#SaaS#DevOps
Everyone’s asking: “We need AI agents for business automation.”
Cool I’m all about agents.
But first: what are we actually trying to improve? Which workflow?
Because agents don’t magically solve operational chaos… they can scale it.
Half the time the real blocker is legacy debt: messy handoffs, fragmented tools, unclear ownership, brittle integrations, no clean source of truth.
Once we map the workflow, the use cases basically reveal themselves:
•60% deterministic (rules/automation)
•20% agentifiable (judgment + context)
•10% human-in-the-loop (risk, money, policy)
That’s when agents help without becoming another layer of chaos.
Built and shipped an app last weekend.
Deployed Sunday night. Woke up Monday ready to “watch it take off.”
Reality:
27 visits (half from me refreshing).
0 signups.
1 friend: “looks cool” (never opened it again).
1 prospect: “can you share pricing + security info?”
The app worked.
The confidence didn’t.
Shipping is fast now.
Scaling still comes down to attention, distribution, and trust.
What’s the part you’re dealing with right now, getting noticed or getting believed?
#Tech #ai #Growth #build #Startups
@SeifBassam Juggling multiple products might feel productive, but skimming the surface can cost you depth.
Sometimes focusing deeply on one thing at a time leads to better results.
Curious about the latest AI tools and frameworks—especially AI agents. If anyone has insights or cool use cases to share, I'd love to learn more! What's everyone exploring these days?
@TheAbdulmuiz_ No-code tools can be a great start, but at some point, you'll need the flexibility and scalability that no-code tools can't offer. A technical co-founder can bridge that gap and supercharge your project for the future!
What if we judged startup 'success' not by funding rounds, but by the positive ripple effect we create for real people life?
Are we building for a fleeting valuation, or for lasting value in the world? Hoping we choose the latter. Let's build with purpose, not just profit.