Most people talk about Agentic AI.
Very few can actually design it.
Here’s a simple cheat sheet to design + explain Agentic AI architecture 👇
🎯 Start here ➡️ Define the goal
What exactly should the agent achieve?
1️⃣ Orchestration Layer ➡️ The control panel
Decides flow, logic, and coordination
2️⃣ Agents Layer ➡️ The workforce
Single or multi-agents handling specialized tasks
3️⃣ Tools Layer ➡️ Execution power
APIs, web search, databases, external systems
4️⃣ Memory ➡️ The brain
Short-term + long-term context storage
5️⃣ Monitoring ➡️ The eyes
Track every step, detect issues in real time
6️⃣ Reliability & Failure ➡️ The safety net
Retries, fallbacks, human-in-the-loop
7️⃣ Governance & Security ➡️ The guardrails
Auth, compliance, audit, data protection
💡 Real insight:
Agents alone don’t make systems powerful.
Architecture does.
If you can explain this simply,
you’re already ahead of 90% in AI.
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Quant at Jane Street kills 97 out of every 100 strategies it builds. That body count is the edge.
Not the 3 survivors. The 97 corpses.
The faster you falsify garbage, the faster you reach the one idea that isn't.
Retail runs this backwards - finds one setup, gets emotionally married to it, and rides it down 40% over six months defending it like a religion.
Run the kill-loop yourself with Horizon -> https://t.co/pDDYFGfVga
Type an idea in plain English. Horizon parses it into entry/exit logic, position sizing, risk rules.
Backtests 5 years of tick data in ~12 seconds. Runs Monte Carlo across thousands of simulated paths.
Deflates Sharpe ratio for the number of trials so luck can't sneak through. Spits out a cold verdict: dead or alive.
Kill it. Type the next. 50 ideas before dinner.
That loop cost $25K/year and a quant desk. Now it's a sentence and 12 seconds.
The edge was never having ideas. It was murdering them at scale.
Save this. Test 50. Keep 2. Kill the rest without mercy
I just found a Polymarket trader, who made over 4,200 trades with a 93% win rate…
He started with just $13 and turned it into more than $6,900 in only 3 months.
Here’s how he trades:
> He focuses only on weather markets.
> He often enters positions at 30–40% probability and still wins.
> Most likely, he uses airport weather data or aviation observations like METAR + SPECI to get the most accurate temperature data in real time.
> He keeps the same bet size for each his trade, no gambling.
Some of his recent trades:
> Hong Kong: entered with only $14 and turned it into $710
> Lagos: from $14 to $188
> Seoul: from $12 to $150
> Taipei: from $164 to $1700
Right now, he has open positions worth more than $4,900: https://t.co/GO0NkrgcTU
I found him by this custom Live Trades filter:
> Weather markets only
> Bots excluded
> Traders with a >$5k Pnl only
> Win rate >90%
He is one of the most successful and consistent weather traders I have ever seen on Polymarket.
A Wall Street quant who ran a trading desk for 12 years just released the exact framework behind building algorithmic trading systems from scratch publicly for free.
Bookmark & give it 1 hour today, no matter what. It'll be the most productive thing you could do this weekend.
Hermes agent masterclass.
In this video, I cover everything you need to understand and customize Hermes Agent. Self-evolving skills, three-tier memory, GEPA optimization, and going from 1 to 10 agents that work for you 24/7.
Enjoy!
Chapters:
00:00 - Intro
02:03 - How to get the most out of this video
02:32 - What we're building (and why it's wild)
07:11 - How the whole thing works under the hood
09:27 - The SOUL.md: your agent's personality file
11:15 - The 3-tier memory system that keeps it all together
14:16 - Skills: what your agent can actually do
16:49 - The self-evolving loop (agents that improve themselves)
19:58 - The curator: Hermes' built-in garbage collector
22:56 - GEPA optimization: making your agent sharper
25:08 - Installation and setup
27:38 - Connecting your agent to Telegram
30:36 - Configuring programmer with Claude Code
31:53 - Adding new skills (from a hub of ready-made skills)
34:59 - Going from 1 to 10 agent profiles
36:49 - Building a custom designer from scratch
40:42 - Anatomy of the .hermes folder (where everything lives)
45:05 - Skill taps: sharing skills via a GitHub repo
45:59 - Skill bundles: stacking skills for workflows
47:19 - Hermes Kanban (coming soon)
48:05 Outro
Cheers! :)