Being Right Too Early: What NGINX in 2010 Taught Me About Tech Adoption

How shipping NGINX in production before it was 'safe' became my playbook for Caddy, Astro—and for refusing performance theater in tech.

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People tell me I have something against current standards. What they don't see is that this isn't a recent position. I'm not writing hot takes based on six months of experience. I've been documenting production deployments and technical experiments for over 15 years. That perspective lets you see cycles that others mistake for novelty.

June 2010. I published a comprehensive guide on installing NGINX + PHP-FPM on Debian. By then, I'd already been running NGINX in production for 2-3 years. The response from potential clients was consistent: "Interesting, but we'll stick with Apache."

Fifteen years later, NGINX powers 35% of all websites.

This is what happens when technical readiness arrives before market readiness. And this is what the archive proves: I wasn't wrong. I was early.

ACT 1: THE SETUP (2010)

My Context in 2010

I was a freelance "firefighter." The kind of developer companies called when their internal teams had already failed. I'd been installing Linux web servers since 1997, when most shops were still paying for Windows NT. By 2010, I had a clear track record:

• Lead developer on Skyrock's Palm WebOS app
• Multi-site WordPress platform managing 100+ sites
• Logic-Immo migration: Oracle → MySQL, Apache → NGINX
• Various corporate projects (Pierre et Vacances, EuroRSCG, etc.)

I wasn't writing that NGINX tutorial to evangelize. I was documenting what already worked in production.

The Article (2010)

The original article made a simple argument:

The Problem:
"PHP frameworks enable faster development but degrade performance. Even with opcode caching (APC, eAccelerator, XCache), optimization isn't enough for high-traffic sites."

Traditional Solutions:

• More powerful servers (expensive)
• Database servers on separate hardware (expensive)
• Load balancing multiple servers (expensive)
• Code review and optimization (time-consuming, diminishing returns)

Alternative Solution:
Switch from Apache to NGINX.

The Pitch:
"10x the capacity, same hardware."

Not theory. Production data from sites I'd already migrated.

The Market Response

Client: "Our Apache setup is drowning under traffic."
Me: "Switch to NGINX. I've run it for 3 years. Here's the data."
Client: "Too risky. Let's add more servers."

[6 months later]

Client: "It still crashes. Can you fix it?"

I wasn't frustrated by the rejections. I understood them. Risk-averse decisions are rational in corporate environments. The market optimizes for predictability, not performance. Understanding this doesn't make the wrong solution right, but it explains why the right solution doesn't sell.

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ACT 2: THE WORLD OF 2010

Pattern Recognition (1989-2010)

This wasn't my first time being right too early.

• 1989: Building on dBASE III+ and Clipper while classmates learned COBOL for IBM mainframes. My curriculum was COBOL, CICS, JCL, MERISE—mainframe thinking. The PC was still a "toy" in academic circles. One got me the diploma. The other got me clients.
• 1997: Running Linux web servers while others paid for Windows NT
• 2007: NGINX in production while others scaled Apache vertically

Same pattern, different decade. See what works, adopt it, document it, watch the market ignore it for 5-10 years.

By 2010, I knew exactly how this would play out. I just didn't expect it to take 15 years this time.

The Technical Landscape

What was standard in 2010:

• Apache 2.2: 60%+ market share, the "safe" choice
• PHP 5.2/5.3: with mod_php or FastCGI
• XCache/eAccelerator: for opcode caching
• Compiling your own web server: normal practice for anyone serious
• The C10K problem: known but considered a "high-traffic edge case"

What I was already running:

• NGINX 0.8.x (version 1.0 wouldn't arrive until 2011)
• PHP-FPM (experimental, "not production-ready" according to most)
• Varnish Cache in front when needed
• Percona Server instead of vanilla MySQL

My CV from 2011 listed: "Web Servers: Apache, NGINX, Varnish Cache + APACHE & mod_pagespeed"

I put Apache first because that's what clients wanted to see. NGINX was already my default for new deployments.

Who Was Using NGINX in 2010

• Rambler (Russian search engine—where NGINX originated)
• WordPress.com (beginning migration)
• A handful of startups
• Freelancers like me who'd bothered to test alternatives

Who Wasn't

• 95% of French web agencies
• Enterprise IT departments
• Anyone who needed to justify their choices to non-technical management

The Pitch I Made

Technical merit:

• Event-driven architecture vs Apache's process-per-connection
• Better memory usage under load
• Simpler configuration (once you learned it)
• Native reverse proxy capabilities

Real-world data:

• Sites I'd migrated: 70-80% reduction in memory usage
• Same traffic, 1/3 the servers needed
• Response times: 30-50% improvement under load

The Objections I Heard

"Nobody else is using it"
Translation: "If it fails, I can't blame the industry standard"

"Our team doesn't know NGINX"
Translation: "Training costs money"

"What about support?"
Translation: "Open source = scary, even when it works better"

"Apache has mod_rewrite, how does NGINX handle .htaccess?"
Translation: "We want the new thing to work exactly like the old thing"

The Decision Pattern

My proposal: NGINX + PHP-FPM, 3-4 servers, streamlined architecture

Competitor's proposal: Apache + mod_php, 8-10 servers, familiar stack

Winner: Competitor

Six months later:

"The site still crashes. Can you come fix it?"

What Was "Revolutionary" in 2010

# 2010 NGINX configuration
# Today this is copy-paste from any tutorial
# Then it was "too exotic"

upstream php_backend {
    server 127.0.0.1:9000;
}

server {
    listen 80;
    server_name example.com;

    location ~ \.php$ {
        fastcgi_pass php_backend;
        fastcgi_param SCRIPT_FILENAME $document_root$fastcgi_script_name;
        include fastcgi_params;
    }
}

Compare to 2010 Apache + mod_php setup:

• Multiple config files scattered across the system
• .htaccess parsing on every request
• Module loading complexity
• Significant resource overhead

Why Technical Merit Wasn't Enough

"Technical superiority loses to operational inertia. Every time. The market doesn't buy the best solution. It buys the solution it can justify."

The market isn't broken. It's optimized for a different outcome: minimizing decision-maker risk, not maximizing technical performance.

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ACT 3: THE SLOW ADOPTION CURVE (2010-2020)

2010-2012: The Pioneer Years

• Me and a few others: NGINX in production
• WordPress.com announces migration (2011)
• NGINX version 1.0 released (April 2011)
• GitHub switches
• Market share: still <10%

My projects in this period:

• Skyrock app on Palm WebOS (lead developer, 2010-2011)
• Multi-site WordPress platform (100+ sites, NGINX-based)
• Logic-Immo migration: Oracle → MySQL
• Every new client deployment: NGINX by default

2013-2015: The Early Adopters

• Startups choose NGINX (no legacy, no politics)
• Performance benchmarks start appearing publicly
• NGINX Inc. founded, offers commercial support (2013)
• "Now it's a real company" = legitimacy for corporate buyers
• Market share crosses 20%

The calls I started getting:

"Remember in 2010 when you suggested NGINX? We're ready to talk about that now."

2016-2018: The Tipping Point

• Docker/containers boom: NGINX default in base images
• Cloud providers bundle NGINX by default
• "NGINX vs Apache" articles everywhere (5 years late)
• Market share approaches 30%
• CTOs start asking their teams: "Why are we still on Apache?"

2019-2020: The New Normal

• NGINX in every tutorial
• "Apache" in articles about legacy migration
• Junior devs who've never configured Apache
• Market share: 35%+

The Cycle Completed

2010: "Too risky, nobody uses it"
2012: "Interesting, but we need more time"
2014: "We're evaluating it"
2016: "We should probably migrate"
2018: "Migration planned for next year"
2020: "Obviously NGINX, what else would we use?"

What Changed Technically

Almost nothing. NGINX 1.0 (2011) worked essentially the same as NGINX 0.8 (2010). The features I used in 2008 are the features people deployed in 2018.

What Changed Commercially

Everything.

• Social proof (WordPress, GitHub, etc.)
• Commercial support available
• NGINX Inc. marketing budget
• Industry consensus achieved

The Lesson

"Technical readiness and market readiness are different things. I had the first in 2008. The market achieved the second in 2016. That's an 8-year gap where being right was commercially useless."

The Client Who Called Back

Scenario (2010-2015):

• 2010: I pitched NGINX migration, showed data, explained architecture
• Their response: "Too risky, we'll scale Apache instead"
• 2011-2014: They added servers, applied patches, paid for band-aids
• 2015: Site crashes regularly, team exhausted, costs spiraling
• Emergency call: "Can you come do that NGINX migration now? We'll pay premium rates."

My answer: "No."

Not because of ego.

Because nothing had changed.

Why I Don't Work With Clients Who Rejected Me

The surface reasons they rejected me (2010):

• "NGINX is too risky"
• "Team doesn't know it"
• "Need commercial support"

The real reason:

• I wasn't politically correct
• I challenged their existing choices
• I didn't validate their comfort zone

In 2015, they're still the same organization.

Same people. Same hierarchy. Same culture. Same politics.

The crisis forced them to call me. But it didn't change who they are.

What Would Happen If I Accepted

Week 1-2:

• I diagnose the problem (same as 2010)
• Propose solution (same as 2010)
• They agree (finally)

Week 3-4:

• I start migration
• Their lead dev (who chose Apache in 2010): "Why are we changing the log format?"
• Their project manager: "Can't we keep the old structure?"
• Their CTO: "Is this really necessary?"

Week 5-8:

• Every. Single. Decision. = Meeting
• "Why not use mod_rewrite compatibility?"
• "The team isn't comfortable with this approach"
• "Can we do a POC first with 20% traffic?"
• "We need to document every change for compliance"

Week 9+:

• Migration drags on
• Budget explodes (because of their delays)
• They blame me for cost overruns
• Tension with their team (who resent the outsider)
• Politics escalate

End result:

• Site works (because I'm competent)
• Bill paid late after multiple reminders
• Reputation: "Skilled but difficult to work with"
• Reference: None (or worse, negative)

The Core Problem

They didn't reject NGINX in 2010. They rejected me.

Not my skills. Not my track record. My approach.

I don't do:

• Politics over technical merit
• Endless meetings to validate obvious decisions
• Compromises that make solutions worse
• Tolerating incompetence to protect egos

In 2010, this made me "too risky."

In 2015, this makes me "difficult to work with."

Same person. Different words. Same rejection.

The Pattern

If they rejected me for political reasons, accepting their emergency call means:

1. Technical decisions still filtered through committee approval
2. Every architectural choice becomes a negotiation
3. I'm responsible for outcomes but not empowered for decisions
4. The project succeeds technically but fails politically
5. I get paid but build no sustainable relationship

My time has value. I choose where to invest it.

My Boundary

"You had your chance to make a smart decision. You chose to optimize for political safety. That's a legitimate choice. But I work in environments where technical merit drives decisions. Our constraints are incompatible."

This isn't revenge. It's recognizing that some problems can't be solved within certain constraints.

I can't fix technical dysfunction while operating inside political dysfunction. The emergency doesn't change the constraint. It just makes it more expensive.

What I Tell Them

"I appreciate the call. But we weren't a good fit in 2010, and we won't be a good fit now. The crisis you're facing is a symptom of the decisions you made then. You need someone who can work within your constraints. That's not me. Good luck."

No anger. No lecture. Just clarity.

What Actually Happens

Client calls someone else who accepts the emergency project.

That consultant:

• Works within their political constraints
• Delivers a working-but-fragile solution
• Takes longer due to committee approvals
• Gets paid well and receives glowing references

Because they played the game correctly.

Technical outcome:

• Site works (for now)
• Architecture compromised by committee decisions
• Same crisis likely in 3 years
• Cycle repeats

I'm not in that cycle anymore. That's a choice.

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ACT 4: WHY EARLY ADOPTION FAILS

The Core Insight

"Being right too early is functionally identical to being wrong. The market doesn't reward correctness. It rewards timing."

The Risk Asymmetry (Corporate Perspective)

When you're the decision maker:

Scenario A: Choose Apache (2010)

• Infrastructure: 10 servers to handle load
• Hosting costs: High (more servers, more management)
• Management: Complex (more moving parts)
• Site crashes anyway
• Response: "We need even more servers"
• Your career: Safe (industry standard choice)

Scenario B: Choose NGINX (2010)

• Infrastructure: 3 servers handle same load
• Hosting costs: 1/3 of Apache approach
• Management: Simpler, more efficient
• Site works perfectly
• Response: "But what if it breaks?"
• Your career: At risk (exotic choice)

Scenario C: Choose NGINX and it fails (2010)

• Same cost as B
• Response: "Who authorized this experiment?"
• Your career: Over

The Math

From a decision-maker's perspective:

• Apache fails: Shared responsibility (industry standard failed, not you)
• NGINX works: You took unnecessary risk (why gamble?)
• NGINX fails: Personal responsibility (you authorized unproven tech)

Rational choice in corporate environment: Apache

Optimal choice technically: NGINX

This isn't stupidity. It's different optimization criteria. The market optimizes for decision-maker safety. I optimize for technical efficiency. Both are rational within their constraints.

The Knowledge Gap

What clients said:
"Our team knows Apache. Training on NGINX would take weeks."

What they meant:
"Change is expensive and uncertain. Status quo is cheap and certain."

Reality:

• NGINX config: simpler than Apache once learned
• Training time: 2-3 days for competent sysadmin
• ROI: immediate (better performance, lower costs)

But "immediate ROI" loses to "zero learning curve."

The Support Theater

Conversation I had multiple times:

Client: "What if NGINX breaks at 3am?"

Me: "Same thing as if Apache breaks. You fix it."

Client: "But Apache has commercial support."

Me: "Which you've never used. When did you last call support?"

Client: "That's not the point. We could call support."

The point wasn't actual support. The point was ass-covering.

If Apache fails: "We had support, they're working on it."

If NGINX fails: "Why did we choose unsupported software?"

The Consultant's Paradox

The scenario:

1. Client has problem
2. I propose correct solution (NGINX)
3. Competitor proposes safe solution (more Apache)
4. Competitor wins contract
5. Problem persists
6. Client calls me back (emergency rates)
7. I implement original solution
8. Problem solved

The outcome:

• I was right
• Competitor got initial contract
• I got emergency contract (higher rates, worse conditions)
• Client paid 3x total cost
• Nobody learned anything

Why This Pattern Persists

Incentive misalignment:

• Consultant incentive: solve problem correctly
• Internal team incentive: make defensible choice
• Manager incentive: avoid personal risk
• Company incentive: minimize cost

Only one of these aligns with "choose NGINX in 2010."

When Correctness Isn't Enough

You can be right about:

• Technical merit
• Performance data
• Cost analysis
• Long-term trajectory

And still not win contracts.

Because the market doesn't buy solutions. It buys comfort, predictability, and defensibility.

This isn't a flaw in the market. It's a feature. Understanding this changes the game from "convince them I'm right" to "document for those who are ready."

What I Learned

Strategies that don't work with markets optimized for safety:

• Lead with "this is better" (triggers defensiveness)
• Show data proving current approach wrong (embarrasses decision-makers)
• Propose unfamiliar solutions without crisis (no urgency)

What works for markets optimized for safety:

• Wait for crisis (creates urgency)
• Frame new solution as "industry best practice" (provides social proof)
• Provide easy rollback plan (reduces perceived risk)
• Let them "discover" the idea (creates ownership)

In other words: Wait for the market to be ready.

But I Don't

Why? Because:

1. Waiting wastes time that could be spent documenting
2. Sites crash while everyone waits for consensus
3. Someone has to create the first map
4. The archive helps those who come after

"I wrote that 2010 NGINX tutorial knowing most readers wouldn't use it for 5 years. But when they were ready, it was there. That's value that compounds."

I'm not playing the market's game. I'm playing a longer game: building knowledge infrastructure for those who optimize for technical merit over political safety. It's a smaller market, but it's my market.

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ACT 5: THE CYCLE CONTINUES (2026)

Today's NGINX

Market status (2026):

• 35%+ market share
• Default in Docker/Kubernetes
• Every junior dev's first web server
• "Obviously the right choice"

What changed:
Nothing technical. Same core architecture as 2010.

What changed:
Everything commercial. Consensus achieved.

The New Generation

I work with developers who:

• Never configured Apache
• Don't remember the C10K problem
• Think NGINX was always the standard
• Have no idea it was controversial

To them, my 2010 article is historical documentation. Like reading about migrating from IIS 5.

Meanwhile, I've Moved On

My current stack (2026):

• Caddy (automatic HTTPS, simpler config)
• OpenLiteSpeed (LiteSpeed performance, open source)

The response:

"NGINX works fine. Why change?"

My answer:

"That's what people said about Apache in 2010."

The Pattern Repeats Exactly

Category	Then (2010)	Now (2026)
Web Server	Apache = standard	NGINX = standard
"Alternative"	NGINX = exotic	Caddy = exotic
CMS/Platform	WordPress = standard	WordPress still = standard
"Alternative"	Static blogs = niche	Astro/Hugo = niche
Objection	"Need commercial support"	"Need commercial support"
Objection	"Team doesn't know it"	"Team doesn't know it"
Objection	"Too risky"	"Too risky"

The cycle is fractal. It repeats at every layer of the stack.

Other Technologies I'm "Too Early" On in 2026

Static Site Generators (WordPress → Hugo → Astro)

This is the perfect modern parallel to the Apache → NGINX story.

The progression:

Platform	Market Position	Technical Reality	Why It Matters
WordPress	The Standard (comfort)	Dynamic CMS for static content. Database + 50 plugins to display text. Slow, fragile, constant security patches.	It's the Apache of CMS. Everyone knows it, so it feels safe.
Hugo	The Transition (exploration)	Pure speed. Go binary, millisecond builds. But rigid templating, steep learning curve.	It's the "NGINX moment" for content—fast but unfamiliar.
Astro	The Pragmatic Choice (efficiency)	Static by default, interactive when needed. Zero JS unless required. Combines speed + developer experience.	Security by design (no DB = no hacks), hosting costs near zero, performance optimal.

The pattern is identical to 2010:

Moving from WordPress to Astro is the same decision as moving from Apache to NGINX: remove unnecessary layers, keep only what serves the end user.

• WordPress: "But everyone uses it, and there are plugins for everything!"
• Hugo: "Interesting, but our team doesn't know Go templates"
• Astro: "Why change? WordPress works fine"

Reality (business website, 50k monthly visitors):

• WordPress: 2-4 vCPU, 4-8GB RAM, MySQL database, PHP-FPM pool, opcode cache, object cache, CDN required for acceptable performance. Load time: 1.5-3s.
• Astro: Static files on CDN edge nodes. Zero compute, zero database, zero runtime. Load time: 200-400ms. Scales to millions of requests without infrastructure changes.

Market response: "WordPress works fine. Why change?"

Same inertia. Different technology. Same 5-10 year adoption curve ahead.

Anti-Agile (my most-read article: more than 2k views, "Performance Theater")

• Response: "But we've always done Scrum"
• Reality: Ritual replacing productivity

Vector Databases with SQL (MyScaleDB)

• Response: "Specialized DBs are better"
• Reality: Most teams don't need specialized, they need familiar

The pattern is identical.

The Meta-Pattern

Innovation emerges
  ↓
Early adopter tests it
  ↓
Writes documentation
  ↓
Market rejects it: too risky
  ↓
Problems persist
  ↓
Crisis forces change
  ↓
Innovation becomes standard
  ↓
Early adopter already testing next thing
  ↓
[Cycle repeats]

The Question

"Should I stop being early? Should I wait for the market to catch up?"

My Answer

No.

Because:

1. Someone has to go first. If everyone waits, nothing moves.
2. Technical correctness matters, even when it's commercially irrelevant.
3. Documentation compounds. That 2010 article helped thousands migrate in 2015-2020.
4. Integrity. I'd rather be right too early than wrong on time.

The Trade-Off

Being right too early has opportunity costs.

I could have:

• Nodded along with Apache recommendations in 2010
• Accepted the emergency callback in 2015
• Built my career on reassuring corporate indecision
• Optimized for income over integrity

Instead, I chose:

• Technical integrity over political comfort
• Documentation over repeat contracts
• Freedom to say "No" over financial security
• Building for those who come after over maximizing current revenue

This is a trade-off, not a defeat.

I'm not a victim of the market. I'm someone who understood the rules and chose to play a different game. That game has different rewards: the ability to sleep at night, the freedom to document truth, and a clean archive that helps people a decade later.

The market optimizes for conformity. I optimize for correctness. Both strategies have costs. I've made my choice consciously.

The Archive Doesn't Lie

In 2026, when someone searches "NGINX migration 2010," they find my article.

Not as nostalgia. As a roadmap.

Someone migrating from Apache today can follow the exact steps I documented in 2010. The configuration still works. The architecture still makes sense. The reasoning is still valid.

That's the value of being right early: you leave a map for those who come after.

I'm not waiting for vindication. I'm building documentation for the next generation of people who see patterns before the market does. That's a different game with different rewards.

Final Thought

"In 2010, I was documenting NGINX when the market wasn't ready. In 2026, I'm documenting Caddy and Astro for those who will be ready in 2030. In 2040, someone will write this exact article about whatever comes next."

The technology changes. The pattern doesn't.

I've been writing for 15 years. That archive shows three complete cycles:

1. 1997-2010: Linux servers → mainstream
2. 2007-2020: NGINX → mainstream
3. 2020-2035: Static-first architecture → (pending mainstream)

The value isn't in being right on time. It's in documenting the path before the crowd arrives.

When you search "NGINX 2010," you find my guide. When you search "WordPress to Astro" you'll find my current work. In 2035, both will be obvious. But the people who needed the map in 2010 and 2026 had it waiting.

That's the game I'm playing. Not convincing the market. Building infrastructure for those who are ready.

The archive doesn't lie. The pattern holds. And the next generation won't have to rediscover what we already documented.

Postscript (January 2026):

As I finalize this article, Cloudflare announces the acquisition of Astro.

The pattern I documented over 15 years just played out again in real-time:

• Astro was "too risky" in 2024
• Cloudflare validates it in 2026
• It will be "obviously correct" by 2030

I didn't predict this acquisition. I predicted the pattern.

And the pattern is never wrong. Just early.

Grumpy postscript (for 2035 readers):

If you're reading this in 2035 and it all sounds "obviously correct", remember someone got called an idiot for writing it in 2010.

The archive hasn't issued an apology. Neither do I.

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If You Liked This

My archive shows patterns across tech stacks and organizational dysfunction. If this resonated, you might find value in:

Building Reliable Legal AI — How I turned frustration with "semantic" search tools that miss Supreme Court cases into a graph-based legal search engine. Same pattern: the market sells AI magic, reality needs structured data.

Actually Agile: Against Performance Theater in Software Development — Why most Agile rituals are stage props for managers, not tools for developers. The same inertia that resisted NGINX created cargo-cult Scrum.

Efficient Laziness at Scale: The Agile Team I Never Needed — How I use "laziness" as a design constraint for systems, not as an excuse. Building tools that make the right thing the easy thing.

From WordPress to Astro: Three Days to Reclaim Performance — Applying the NGINX playbook to CMS migration. Same objections ("WordPress works fine"), same 10x performance gain.

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Closing

What's your "NGINX moment"? What are you right about too early?

Read the original (2010): Installer NGINX, PHP5-FPM, Xcache et MySQL sur une Debian Lenny / Squeeze

Current stack (2026): Caddy + OpenLiteSpeed. See you in 2035.

Comments

[Sylwia Laskowska]

This resonates a lot. On the frontend, the exact same pattern plays out — sometimes even more brutally.

We often know there’s a technically better solution, but still stick to older ones because the team already knows them, they feel safer, or they’re easier to justify to non-technical stakeholders.

The difference is that on the frontend, being “right too early” can actually kill a good idea entirely. Ecosystem, community adoption, and tooling support aren’t just nice-to-haves — they’re survival factors.

A backend can wait years for the market to catch up. A frontend solution without momentum often doesn’t get that luxury.

[Pascal CESCATO]

Totally agree — and it’s fascinating how the same pattern takes a different shape on the frontend.
On the backend, you can survive a long winter as long as the idea is solid. On the frontend, if the ecosystem doesn’t rally quickly enough, the idea just evaporates before reaching maturity.
What you said about “momentum as a survival factor” is spot on. It’s almost like technical merit is just the opening move; community adoption decides the rest of the game. And that pressure makes early correctness feel even riskier.
Thanks for adding this angle — it rounds out the story in a way I hadn’t articulated.