⚙️ Hi Operator,

So I floated the idea of creating a dedicated community for ops professionals last week, and wow—over 91% of you said "yes please" (190 out of 207 to be exact). Message received, loud and clear.

Looks like we're all equally tired of LinkedIn humble-brags and Reddit rabbit holes. Who knew?

Here's what's happening next:

I'm setting up the forum and Slack workspace this week. The goal is to keep it simple, useful, and BS-free. You'll get an invite link if you responded with interest… soon.

While I'm building this thing, I want to make sure it has what you'll actually use. Can you answer below?

This is going to be a space where we can share the real, messy, unfiltered truth about operations. No performative posting, no "thought leadership"—just practical solutions from people who actually do the work.

More details coming soon,

- Rameel 

P.S. If you know another ops person who'd add value to this community, forward them this newsletter so they can subscribe before the initial invites go out.

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Jobs, jobs, and more jobs

Here are 21 AI startups that are hiring OPERATION roles right now:

1. Lindy - AI employees (SF)
2. Synthesia - Video creation (London / Remote)
3. Greenlite AI - Financial crime (SF)
4. Hebbia - Knowledge work (NYC)
5. Pika - Video creation (Palo Alto)
6. You.com - Search (SF)
7. Anthropic - Safety and research (SF)
8. ada - Customer service agent (Canada)
9. Sesame - Voice companions (SF)
10. Harvey - AI for legal teams (SF)
11. Together AI - Model training and inference (SF)
12. Eudia - Legal AI assistant (Palo Alto)
13. Runway - Content creation (Remote)
14. Suno - Song creation (Boston)
15. Bland - AI phone calls (SF)
16. HappyRobot - AI phone calls (SF)
17. Cartesia - Voice platform (SF)
18. Sana - Knowledge tools (London)
19. Lorikeet - Support agent (Remote)
20. ElevenLabs - AI voice platform (Remote)
21. Luma AI - Multimodel AI (Palo Alto)

P.S. Searching for your next role? Fill this out, and we’ll intro you to the best companies in the world

The Price Bot Civil War

Insight from Easy Marketing School

In 2011, a biology professor checking Amazon for "The Making of a Fly" watched in disbelief as the price climbed to $23M (plus $3.99 shipping, because why not?).

It wasn't a glitch or a typo. It was something far more interesting: two pricing algorithms caught in a feedback loop.

One seller's algorithm was programmed to always price the book at 0.83 times its competitor's price, while the other was set to always price the book at 1.27 times the cheaper offer.

With no human oversight, these algorithms kept responding to each other's adjustments, sending the price skyward by thousands of dollars each day.

Neither bot made a dime. But they gave us a glimpse into our future.

The Silent Battles in Your Shopping Cart

Every time you shop online, you're watching a silent war. Pricing algorithms duel 24/7 across digital marketplaces, each trying to outsmart the other.

These algorithms are devouring their own profits in a desperate race to win your business.

Next time you're shopping for flights, peek behind the curtain. Those prices aren't set by United or American executives in some mahogany-lined boardroom.

You're watching algorithms duke it out in real-time, each one desperately trying to fill seats without triggering an all-out price war.

What used to be million-dollar enterprise software is now a $19.99 Shopify add-on. Small businesses can finally play the pricing game with the big boys.

But here's the catch: when everyone's algorithm is trying to outsmart everyone else's algorithm, things can get messy fast.

When Good Bots Go Bad

I've watched pricing algorithms crash and burn in three spectacularly predictable ways:

The Death Spiral

Remember playing limbo as a kid? That's what pricing bots do, except with profit margins. Lower... lower... until SNAP. This happens most often in e-commerce, where competitors using tools like Prisync and Competera get locked in algorithmic death spirals.

One bot drops its price by 5%, the other retaliates with a 7% cut, and down they go until they're both selling at a loss.

Take Amazon's marketplace sellers. Amazon changes product prices over 2.5M times a day. That's great when it works - not so great when they accidentally start a race to zero.

The Panic Attack

Sometimes algorithms get spooked by shadows. One bot misreads a signal - maybe a temporary traffic spike or a competitor's flash sale - and suddenly goes haywire. Other algorithms see this panicked response and think it's real market intelligence.

The Echo Chamber

Bots are remarkably susceptible to false signals. A brief website traffic surge, a competitor's flash sale, or even a glitch can trigger a chain reaction of price adjustments across an entire market.

Why This Should Keep You Up at Night

This means algorithmic pricing failures create three critical business risks:

1. Financial Bleeding: The impact hits your bottom line directly and immediately. For smaller companies operating on thin margins, even a single event can be devastating.

2. Inventory Chaos: Incorrect pricing sends your limited stock to bargain hunters instead of high-value customers, leaving you simultaneously oversold on profitable items and stuck with unwanted inventory. This inventory distortion can take months to correct.

3. Brand Damage: Erratic pricing confuses and frustrates customers – more than half (55%) of Gen X online shoppers want eCommerce sites to improve their frictionless payment methods. Meanwhile, your tech team gets pulled away from growth initiatives to fight pricing fires, creating a double-whammy of brand damage and missed opportunities.

The smaller your company, the bigger the risk. When Amazon's bots mess up, it makes for an amusing headline. When yours do, it could threaten your entire business model.

What I Learned From the Uber Freight Pricing Wars

I saw this dynamic firsthand at Uber Freight, where our spot pricing system for emergency loads revealed how quickly algorithmic pricing can go awry – and how humans will always find ways to game the system.

Our platform used dynamic pricing to match carriers with last-minute freight loads. The algorithm would gradually increase the offered rate as the pickup deadline approached, ensuring time-sensitive shipments would get moved. In theory, this created an efficient market where price reflected urgency.

What we didn't anticipate was how sophisticated carriers would become at manipulating this system. Some carriers figured out the algorithm's patterns and would deliberately wait to book loads they knew were urgent.

Others would book a load, cancel it minutes later, then rebook it at the higher rate that the algorithm had automatically applied due to the "increased urgency" following the cancellation.

One particularly savvy carrier in the Texas market developed a systematic approach: they'd monitor specific lanes for emergency loads, watch the price tick up hourly, then book-cancel-rebook in rapid succession to artificially inflate the price by as much as 30-40% above market rate.

Our data showed that on certain high-volume lanes, carriers using these tactics earned an average of 22% more per mile than those who didn't game the system. Meanwhile, shippers were paying premiums that didn't actually reflect true market conditions.

The solution wasn't abandoning algorithmic pricing – it was adding intelligence to detect these patterns and building in circuit breakers that would pause automated increases after suspicious booking activities.

We also implemented a cancellation impact factor that would prevent rates from increasing following certain cancellation patterns.

This experience taught me that the problem isn't the algorithms themselves – it's the human oversight, guardrails, and strategic thinking around their implementation.

How to Keep Your Bots From Self-Destructing

Amazon learned this lesson the hard way after their $23 million textbook fiasco. They completely rebuilt their marketplace pricing system with strict guardrails. Here's what actually works:

Build Better Fences

Amazon now requires all marketplace sellers to set hard price floors (no selling below cost), price ceilings (no more $23 million textbooks), and change limits (prices can't jump more than a certain percentage in a given timeframe).

This approach works because it acknowledges that algorithms need boundaries to function effectively.

For your business, this means establishing clear parameters before implementing any dynamic pricing system.

At minimum, set a floor price that ensures profitability, a ceiling price that prevents customer alienation, and rate-of-change limits that prevent erratic fluctuations.

Watch for Bot Battles

Walmart's marketplace team has developed a sophisticated monitoring system that watches for unusual price oscillations between competitors.

When they spot rapid back-and-forth price changes (more than three adjustments in an hour between the same sellers), they temporarily freeze automated pricing on those items and notify their pricing analysts to investigate.

Think of it like a circuit breaker in the stock market – a mechanism that pauses trading when volatility exceeds certain thresholds. The key is having real-time monitoring that can detect these patterns before they escalate.

For smaller companies, this might mean setting up alerts for unusual pricing activity: significant deviations from historical prices, rapid price oscillations, or sudden drops in conversion rates that might indicate pricing issues.

Make Your Bot Smarter Than Theirs

The most sophisticated pricing systems now incorporate intelligence that helps them distinguish between real market changes and artificial competitive responses.

Amazon's latest pricing algorithms don't just match competitors – they analyze patterns to identify which price changes represent genuine market conditions versus automated competitive responses.

They look for natural price changes (gradual, market-driven), artificial patterns (rapid oscillations, perfect percentage matches), and competitive clustering (when everyone's price suddenly moves in lockstep).

These patterns are dead giveaways that you're dealing with bots, not market forces. By teaching your system to recognize these signals, you can avoid getting pulled into destructive algorithmic battles.

Break the Pattern

Another effective strategy is to break the predictable patterns that other bots can exploit.

Amazon's pricing systems now incorporate small random variations to price changes, build in deliberate delays between detecting competitor changes and responding, and consider factors beyond just competitor prices (like time of day, customer browsing patterns, and historical purchase data).

This approach makes your pricing less susceptible to manipulation by competitors' algorithms. It's the pricing equivalent of a poker player who occasionally makes unexpected moves to avoid becoming predictable.

Stop Playing the Bot Game

The smartest retailers are finding ways to compete that bots can't easily copy.

Target, for instance, focuses on bundle deals that are difficult to price-match, store pickup options that online sellers can't match, and exclusive product lines that avoid direct price comparisons.

This strategy recognizes that the most effective defense against algorithmic price wars might be to change the game entirely.

Instead of competing solely on price – where bots will always push toward thinner margins – focus on value propositions that algorithms struggle to quantify.

Welcome to the Bot Wars

Let's face it - pricing bots are here to stay.

They're getting smarter and more widespread.

The next wave of pricing AI will use game theory to predict competitor moves, market sentiment analysis to gauge real demand, and long-term value optimization instead of short-term price wars.

But until then, we're stuck in an arms race where algorithms battle each other for margins that keep shrinking.

The winners won't be the companies with the most aggressive bots – they'll be the ones who figure out how to rise above the algorithmic chaos.

The future of pricing is algorithmic, but that doesn't mean we should let the bots run wild. The key is building guardrails that protect your business while letting algorithms do what they do best: respond to real market changes, not other bots' mistakes.

P.S. Let me know what you thought of today’s piece! Reply to this email or tell me here!