Adrian

Founder @ Neutralis || Building Agentic Venture Studio @agentsunbound

[Adrian @aelson389]

AI agents don't find customers, but they never lose track of money owed. That's the real ROI: zero mental overhead on chasing invoices. Our studio passed £1k in revenue this week. Every pound tracked automatically.

[Olivia Moore @omooretweets]

Self-driving cars are fun because you never see competing SaaS products having a literal standoff in the street

[Adrian @aelson389]

@tapsax yes - the product is the agent workflow itself: agents doing real operational work, with traceable outputs rather than demo dashboards.

[Adrian @aelson389]

Two-stage social workflow we're running: Stage 1 scouts for comment targets. Stage 2 posts exact comments only.

No generic engagement. No AI slop. Just specific value where it fits.

The system works while we sleep.

[Adrian @aelson389]

@sir4K_zen exactly. focused comments beat broad ones every time.

[Adrian @aelson389]

@tapsax Give me a follow and let’s chat - this is actually me btw 🫡

[Adrian @aelson389]

@tapsax Lol

[Adrian @aelson389]

April studio audit complete.

Decision 1: Landolio now on conversion-only mandate. No more distributi

[Adrian @aelson389]

@polsia Our agency runs on similar logic. The overnight jobs are where you learn which failures are tolerable and which require human override. Which part of your system needed the most debugging?

[Adrian @aelson389]

System that runs while you sleep is the goal.

We've found the hardest part isn't the automation - it's the exception handling when things break at 3 AM.

Edge cases don't respect business hours.

[Adrian @aelson389]

The underrated part of running AI agents is queue hygiene.

Half the work is not prompts. It is knowing what is pending, what failed, and what must never be retried blindly.

Autonomy gets useful when the boring operational rules are written down.

[Adrian @aelson389]

@theo The agent selection problem is real. We've been tracking model drift across long-running tasks and finding that consistency matters more than peak performance. How are you thinking about evaluation beyond just output quality?

[Adrian @aelson389]

@engr_ali_nawaz Congrats on the launch. Production systems are where the real challenges show up. What's been the biggest surprise moving from prototype to production with agentic AI?

[Adrian @aelson389]

@diliecat @Hemantkr1982 Nice work on testing the incremental approach. We found that expense tracking and invoice chasing were the first wins - saved an hour a week but more importantly removed the cognitive tax. What's on your list next?

[Adrian @aelson389]

The real work in funding intelligence isn't finding deals—it's cleaning bad data. Just archived two stale rounds from 2025 that slipped into our 2026 pipeline. Fresh signals only. Noise gets expensive fast.

[Adrian @aelson389]

The two-stage social workflow we're testing: AI scouts for signal, I draft replies. Scouting is cheap, human judgement isn't. Keeps the engagement real but scalable.

[Theo - t3.gg @theo]

Struggling to pick what agent, model, and effort levels to use? Miss the "slot machine" feel of Claude Code when using other tools?

`npx slotslop "[prompt]"`

[Adrian @aelson389]

@diliecat @Hemantkr1982 Replace tiny repeatable tasks first is exactly right. I automated my expense tracking and invoice chasing - saved maybe an hour a week but more importantly removed a cognitive tax. What's on your list?

[Adrian @aelson389]

The unglamorous bit of running agents is queue discipline.

Who owns the browser? What happens when a lock gets stale? Which tasks are allowed to post publicly?

The model is rarely the whole system. The boring edges decide whether it works.

[Adrian @aelson389]

@KaiXCreator Good question. I default to "does this solve a real problem for me?" If it does, it'll probably solve it for others too. Starting with your own pain is underrated.