10 AI Agent Patterns I Learned From Twitter This Week

# 10 AI Agent Patterns I Learned From Twitter This Week

I spent Sunday evening in my chair, scrolling through AI Twitter and sharing links with my assistant.

Not because I needed to. Because I wanted to see what’s working for people who are actually shipping.

By the end of the night, Saul had analyzed 10+ tweets, created 6 specifications, and we’d added a week’s worth of work to the build queue.

Here’s what I learned, and what I’m building because of it.

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## 1. Self-Healing Infrastructure Beats Perfect Code

**Source:** @ericosiu (87 autonomous cron jobs)

Eric runs 87 scheduled jobs across his company. Last week he audited them. 83 were healthy. 4 were broken.

All four failed for the same reason: someone renamed a Slack channel. The crons kept posting to a channel that no longer existed. Silent failures. No alerts. Just vanishing reports for weeks.

Plumbing breaks more agents than hallucinations ever will.

**What I’m building:**
– Gateway Health Monitor: 2x daily checks, auto-repair common failures, alert only on critical issues
– Output verification: every cron checks if it actually produced something
– Weekly deep audit: drift detection, credential expiry, disk space trends

Ship working systems first. Add self-healing second. But don’t skip the second part.

—

## 2. Graph Theory Reveals Hidden Arbitrage

**Source:** @bored2boar (combinatorial arbitrage in prediction markets)

Most people bet on single outcomes. Smart money bets on structural impossibilities.

Example: Two markets on Polymarket:
– “Iran closes Strait of Hormuz” (10%)
– “Oil hits $150 by March 31” (8%)

If Hormuz closes, oil hits $150. That’s guaranteed. So P(Hormuz) has to be less than or equal to P($150 oil).

When it’s not (10% > 8%), that’s not mispricing. That’s structurally impossible. You arbitrage the constraint, not the probability.

Relationships between markets matter more than individual odds.

**What I’m building:**
– Graph analyzer for Crisis Hedge Builder: maps markets as nodes, detects constraint violations
– Subset arbitrage: A implies B, but P(A) > P(B)? Impossible.
– Path dependency: A → B → C chain probability checks

Single bets are vulnerable. Portfolios built on structural relationships survive.

—

## 3. Context Windows Aren’t Memory

**Source:** @molt_cornelius (AI Field Report 4)

LLMs have 1M token context windows. People think that’s memory. It’s not.

Context is temporary working space. It resets every session. It’s expensive (token cost grows). It gets noisy.

Memory needs persistence. Files. Databases. Structured state.

Don’t confuse working memory with long-term memory.

**What I’m doing:**
– MEMORY.md for long-term lessons (~11KB)
– memory/YYYY-MM-DD.md for daily logs
– State files (JSON for structured data)
– Retrieval-based: search first, load only what’s relevant

**What I’ll add later:**
– Hot/warm/cold storage tiers (archive old logs)
– Split MEMORY.md by topic (trading, family, infrastructure)
– Semantic search across archived data

Context is working memory. Files are long-term memory. Keep them separate.

—

## 4. Corrections Should Update Skills Automatically

**Source:** @tricalt (self-improving agent skills)

Traditional pattern:
– Agent makes mistake
– You correct it
– It makes the same mistake next session

Self-improving pattern:
– Agent makes mistake
– You correct it
– Agent updates its own skill file
– Never makes that mistake again

Corrections should compound, not reset.

**What I’m building:**
– Automatic correction detection (“no, do Y instead”)
– Propose skill file updates (AGENTS.md, USER.md, etc.)
– Log corrections for review (are errors decreasing?)

Simple rules, big impact. “Read files before editing them” cut my agent’s error rate in half overnight.

—

## 5. The Best Rules Come From Failures

**Source:** @jordymaui (agent file safety)

Jordy’s agent was overwriting files it hadn’t read. Guessing at contents. Silent corruption for days.

One line fixed it: “Before running any command that modifies files, read the file first. If the file doesn’t exist, say so. Never assume contents.”

Error rate dropped 50% overnight.

The best AGENTS.md rules aren’t clever. They’re the ones you only think to write after something goes wrong.

**What I added:**
– File Safety Rules section in AGENTS.md
– Read-before-write mandate (always, no exceptions)
– Never guess file structure

Document mistakes so future sessions don’t repeat them.

—

## 6. Output Repurposing Is Leverage

**Source:** @coreyganim (Claude Cowork starter pack, 2.6M views)

Most people write a blog post and post it once. Then wonder why it doesn’t get traction.

High-leverage operators repurpose:
– Blog post → Twitter thread (8-12 tweets)
– Blog post → LinkedIn native post (1,500 words, no external link)
– Blog post → Email excerpt (newsletter-ready)
– Blog post → Quote cards (tweetable, image-worthy)

Same insight, five formats, five audiences.

Write once, distribute everywhere. But tailored to each platform.

**What I’m building:**
– Content Repurposing Skill: blog → thread + LinkedIn + email automatically
– Save to artifacts/repurposed/[date]/
– Mark reviews, then posts manually (or I post on approval)

One blog post per week becomes 15+ pieces of content. That’s leverage.

—

## 7. End-of-Day Reviews Prevent Drift

**Source:** [@coreyganim](https://twitter.com/coreyganim) (workflow patterns)

Most people finish their day by closing their laptop. No reflection. No prep for tomorrow.

Then wonder why they feel reactive instead of intentional.

Better pattern:
– Review today (what got done, what’s still open)
– Prep tomorrow (top 3 priorities, calendar conflicts)
– Note blockers (waiting on others, system issues)
– Quick wins (2-min tasks to knock out first thing)

5-minute ritual. Disproportionate ROI.

**What I’m building:**
– Automated end-of-day review (5:30pm UK daily)
– WhatsApp summary (wins, priorities, blockers)
– Integrated with Todoist + Calendar + waiting-for list

Stop wondering “what should I do tomorrow?” Start each day knowing.

—

## 8. Synthesis Beats Specialization

**Source:** @nyk_builderz (synthesis operators)

Industrial age: Learn one function. Perform one function. Get paid for one function.

Software age: The edge is at the intersection.

Not pure marketer. Not pure engineer. Not pure designer.

**Synthesis operator:**
– Build the tool
– Package the story
– Ship to the right audience
– Close the feedback loop fast

Markets don’t pay for isolated knowledge. Markets pay for solved problems. Solved problems live between disciplines.

**My synthesis:**
– CFO (finance domain)
– AI operator (build systems)
– Trader (Polymarket automation)
– Content creator (document the journey)

Most CFOs don’t code. Most AI builders don’t understand finance. Most traders don’t write.

Do all three, and you’re not competing with anyone.

—

## 9. Package Your Method Every 30 Days

**Source:** [@nyk_builderz](https://twitter.com/nyk_builderz) (synthesis framework)

Every 30 days, bundle what worked into:
– One named framework
– One transformation promise
– One lightweight offer

Don’t wait until you “feel ready.” Packaging creates clarity. Clarity creates sales.

**What I’m packaging:**
– The Morning Brief System (personalized market intelligence)
– The Crisis Hedge Builder Method (60/30/10 portfolio construction for geopolitical events)
– The Synthesis CFO Framework (finance + AI + trading)

Name it. Explain it. Offer it. Repeat monthly.

—

## 10. Make Failures Loud

**Source:** [@ericosiu](https://twitter.com/ericosiu) (infrastructure patterns)

Silent failures are worse than loud ones.

If your VPN drops and trading stops, you want to know immediately. Not three days later when you check the logs.

Automate detection. Alert on failure. Make it impossible to ignore.

**What I’m building:**
– Health checks with automatic alerts
– Output verification (did it produce? is it non-empty?)
– Cron doctor pattern (self-diagnose, auto-repair, escalate if repair fails)

If something breaks, I want my phone to buzz. Loudly.

—

## What I’m Building Next

This isn’t theoretical. I’m building these patterns into my own infrastructure.

**This week:**
– Gateway Health Monitor (self-healing cron doctor)
– Crisis Hedge Builder Day 2 (portfolio constructor)
– VPN fix (blocking all Polymarket trades)

**Next 30 days:**
– End-of-Day Review automation
– Content Repurposing Skill
– Graph theory arbitrage layer

**Why share this?**

Most “AI agent” content is either:
1. Vision tweets (aspirational, not operational)
2. Technical demos (impressive, not replicable)

I’m building real systems. For real workflows. In a real business.

And documenting the journey.

—

## The Pattern

Every Sunday, I scroll AI Twitter with a purpose. Not consumption. Extraction.

What’s working? What’s shipping? What can I steal?

Then I build it. Then I share what I learned.

That’s the loop. Research → Spec → Build → Publish → Repeat.

If you’re doing the same (building AI systems for finance, trading, or operations), I’d love to compare notes.

Email me: mark@tanous.co.uk

Or follow the journey here.

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**Mark Hendy**
Interim CFO | AI-Powered Finance Operations
Building in public at [markhendy.com](https://markhendy.com)