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Psych 101

Writing while the World is on Fire

Episode - 676

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February 18, 2025 Psych 101, Scriptnotes

How do you keep doing creative work when the world is falling apart around you? To sift through the despair and doubt, John welcomes back legendary Scriptnotes guest, writer-turned-psychotherapist Dennis Palumbo. They discuss the many feelings that catastrophic events can bring up in artists, the personal narratives that often inform those feelings, and how to keep moving forward when you feel like the band on the Titanic.

We also follow up on AI, and answer listener questions on competing with brain trusts and how to support a friend embroiled in controversy.

In our bonus segment for premium members, Dennis guides us through the best examples and worst mistakes of portraying therapists on screen.

Links:

  • “Am I Just Fiddling While Rome Burns?” by Dennis Palumbo for Psychiatric Times
  • Scriptnotes 99 – Psychotherapy for Screenwriters
  • ShotDeck
  • River Runner Global
  • At the Existentialist Café by Sarah Bakewell
  • Get a Scriptnotes T-shirt!
  • Check out the Inneresting Newsletter
  • Gift a Scriptnotes Subscription or treat yourself to a premium subscription!
  • Craig Mazin on Threads and Instagram
  • John August on BlueSky, Threads, and Instagram
  • Outro by Spencer Lackey (send us yours!)
  • Scriptnotes is produced by Drew Marquardt and edited by Matthew Chilelli.

Email us at ask@johnaugust.com

You can download the episode here.

UPDATE 2-19-25: The transcript for this episode can be found here.

Something’s Coming

January 6, 2025 Film Industry, Geek Alert, General, Psych 101, Tools

Last week, Dwarkesh Patel put words to an uneasy feeling that resonated with me:

I think we’re at what late February 2020 was for Covid, but for AI.

If you can remember back to February 2020, both the media and the general public were still in normal-times mode, discussing Trump’s impeachment, the Democratic primaries and Harvey Weinstein. Epidemiologists recognized that something big and potentially unprecedented was coming, but the news hadn’t yet broken through.

One of the first front-page articles I can find in the NY Times about Covid is from February 22nd, 2020.

image of NY Times front page, with covid story on left edge

Just three weeks later, markets had crashed and schools were closing. The world was upended. Covid had become the context for everything.

Patel foresees a similar pattern with AI:

Every single world leader, every single CEO, every single institution, members of the general public are going to realize pretty soon that the main thing we as a world are dealing with is Covid, or in this case, AI.

By “pretty soon,” I don’t think Patel believes we’re three weeks away from global upheaval. But the timeframes are much shorter than commonly believed — and getting shorter month by month.

Wait, what? And why?

This post is meant to be an explainer for friends and readers who haven’t been paying close attention to what’s been happening in AI. Which is okay! Technology is full of hype and bullshit, which most people should happily ignore.

We’ve seen countless examples of Next Big Things ultimately revealed to be nothing burgers. Many of the promises and perils of AI could meet a similar fate. Patel himself is putting together a media venture focused on AI, so of course he’s going to frame the issue as existential. Wherever there’s billions of dollars being spent, there’s hype and hyperbole, predictions and polemics.

Still — much like with epidemiologists and Covid in February 2020, the folks who deal with AI for a living are pretty sure something big is coming, and sooner than expected.

Something big doesn’t necessarily mean catastrophic; the Covid analogy only goes so far. Indeed, some researchers see AI ushering in a golden age of scientific enlightenment and economic bounty. Others are more pessimistic — realistic, I’d say — warning that we’re in for a bumpy and unpredictable ride, one that’s going to be playing out in a lot of upcoming headlines.

The sky isn’t falling — but it’s worth directing your gaze upwards.

The world of tomorrow, today

Science fiction is becoming science fact much faster than almost anyone anticipated. One way to track this is to ask interested parties how many years it will be before we have artificial general intelligence (AGI) capable of doing most human tasks. In 2020, the average estimate was around 50 years. By the end of 2023, it was seven.

chart showing decline from 30 years to 8 years, with dashed lines indicating further declines

Over the past few months, a common prediction has become three years. That’s the end of 2027. Exactly how much AI progress we’ll see by then has become the subject of a recent bet. Of the ten evaluation criteria for the bet, one hits particularly close to home for me:

8) With little or no human involvement, [AI will be able to] write Oscar-caliber screenplays.

As a professional screenwriter and Academy voter, I can’t give you precise delimiters for “Oscar-caliber” versus “pretty good” screenplays. But the larger point is that AI should be able to generate text that feels original, compelling and emotionally honest, both beat-by-beat and over the course of 120 satisfying pages. Very few humans can do that, so will an AI be able to?

A lot of researchers say yes, and by the end of 2027.

I’m skeptical — but that may be a combination of ego preservation and goalpost-moving. It’s not art without struggle, et cetera.

The fact that we’ve moved from the theoretical (“Could AI generate a plausible screenplay?”) to practical (“Should an AI-generated screenplay be eligible for an Oscar?”) in two years is indicative of just how fast things are moving.

So what happened? Basically, AI got smarter much faster than expected.

Warp speed

Some of the acceleration is easy to notice. When large language models (LLMs) like ChatGPT debuted at the end of 2022, they felt like a novelty. They generated text and images, but nothing particularly useful, and they frequently “hallucinated,” a polite way of saying made shit up.

If you shrugged and moved on, I get it.

The quality of LLM’s output has improved a lot over the past two years, to the point that real professionals are using them daily. Even in their current state — even if they never get any better — LLMs can disrupt a lot of work, for better and for worse.

An example: Over the holidays, I built two little iOS apps using Cursor, which generates code from plain text using an LLM.

Here’s what I told it as I was starting one app:

I’ll be attaching screen shots to show you what I’m describing.

  1. Main screen is the starting screen upon launching the app. There will be a background image, but you can ignore that for now. There are three buttons. New Game, How to Play, and Credits.

  2. How to Play is reached through the How to Play button on the main screen. The text for that scrolling view is the file in the project how-to-play.txt.

  3. New Game screen is reached through the new game button. It has two pop-up lists. the first chooses from 3 to 20. the second from 1 to 10. Clicking Start takes you into the game. (In the game view, the top-right field should show the players times round, so if you had 3 players and five rounds, it would start with 1/15, then 2/15.

  4. the Setup screen is linked to from the game screen, if they need to make adjustments or restart/quit the game.

Within seconds, it had generated an app I could build and run in Xcode. It’s now installed on my phone. It’s not a commercial app anyone will ever buy, but if it were, this would be a decent prototype.

Using Cursor feels like magic. I’m barely a programmer, but in the hands of someone who knew what they were doing, it’s easy to imagine technology like this tripling their productivity.1 That’s great for the software engineer — unless the company paying them decides they don’t need triple the productivity and will instead just hire one-third the engineers.

The same calculation can be applied to nearly any industry involving knowledge work. If your job can be made more productive by AI, your position is potentially in jeopardy.

That LLMs are getting better at doing actually useful things is notable, but that’s not the main reason timelines are shortening.

Let’s see how clever you really are

To measure how powerful a given AI system is, you need to establish some benchmarks. Existing LLMs easily pass the SAT, the GRE, and most professional certification exams. So researchers must come up with harder and harder questions, ones that won’t be in the model’s training set.

No matter how high you set the bar, the newest systems keep jumping over it. Month after month, each new model does a little better. Then, right before the holidays, OpenAI announced that its o3 system made a huge and unexpected leap:

chart showing o3 performance and cost, both vastly higher

With LLMs like ChatGPT or Claude, we’re used to getting fast and cheap answers. They spit out a text or image in seconds. In contrast, o3 spends considerably more time (and computing power) planning and assessing. It’s a significant change in the paradigm. The o3 approach is slower and more expensive — potentially thousands of dollars per query versus mere pennies — but the results for certain types of questions are dramatically better. For billion-dollar companies, it’s worth it.

Systems like these are particularly good at solving difficult math and computer science problems. And since AI systems themselves are based on math and computer science, today’s model will help build the next generation. This virtuous cycle is a significant reason the timelines keep getting shorter. AI is getting more powerful because AI is getting more powerful.

When and why this will become the major story

In 2020, Covid wasn’t on the front page of the NY Times until its economic and societal impacts were unmistakable. The stock market tanked; hospitals were filling up. Covid became impossible to ignore. Patel’s prediction is the same thing will happen with AI. I agree.

I can imagine many scenarios bringing AI to the front page, none of which involve a robot uprising.

Here are a few topics I expect we’ll see in the headlines over the next three years.

  • Global tensions. As with nuclear technology during the Cold War, big nations worry about falling behind. China has caps on the number of high-performance AI chips it’s allowed to import. Those chips it needs? They’re made in Taiwan. Gulp.

  • Espionage. Corporations spend billions training their models.2 Those model weights are incredibly valuable, both to competitors and bad actors.

  • Alignment. This is a term of art for “making sure the AI doesn’t kill us,” and is a major source of concern for professionals working in the field. How do you teach AI to act responsibly, and how do you know it’s not just faking it? AI safety is currently the responsibility of corporations racing to be the first to market. Not ideal!

  • Nationalizing AI. For all three of the reasons above, a nation (say, the U.S.) might decide that it’s a security risk to allow such powerful technology to be controlled by anyone but the government.

  • Spectacular bankruptcy. Several of these companies have massive valuations and questionable governance. It seems likely one or more will fail, which will lead to questions about the worth of the whole AI industry.

  • The economy. The stock market could skyrocket — or tank. Many economists believe AI will lead to productivity gains that will increase GDP, but also, people work jobs to earn money and buy things? That seems important.

  • Labor unrest. Unemployment is one thing, but what happens when entire professions are no longer viable? What’s the point in retraining for a different job if AI could do that one too?

  • Breakthroughs in science and medicine. Once you have one AI as smart as a Nobel prize winner, you can spin up one million of them to work in parallel. New drugs? Miracle cures? Revolutionary technology, like fusion power and quantum computing? Everything seems possible.

  • Environmental impact (bad). When you see articles about the carbon footprint of LLMs, they’re talking about initial training stage. That’s the energy intensive step, but also way smaller than you may be expecting? After that, the carbon impact of each individual query is negligible, on the order of watching a YouTube video. That said, the techniques powering systems like o3 involve using more power to deliver answers, which is why you see Microsoft and others talking about recommissioning nuclear plants. Also, e-waste! All those outdated chips need to be recycled.

  • Environmental impact (good). AI systems excel at science, engineering, and anything involving patterns. Last month, Google’s DeepMind pushed weather forecasting from 10 days to 15 days. Work like this could help us deal with effects of climate change, by improving crop yields and the energy grid, for example.

So how freaked out should you be?

What is an ordinary person supposed to do with the knowledge that the world could suddenly change?

My best advice is to hold onto your assumptions about the future loosely. Make plans. Live your life. Pay attention to what’s happening, but don’t let it dominate your decision-making. Don’t let uncertainty paralyze you.

A healthy dose of skepticism is warranted. But denial isn’t. I still hear smart colleagues dismissing AI as fancy autocomplete. Sure, fine — but if it can autocomplete a diagnosis more accurately than a trained doctor, we should pay attention.

It’s reasonable to assume that 2027 will look a lot like 2024. We’ll still have politics and memes and misbehaving celebrities. It’ll be different from today in ways we can’t fully predict. The future, as always, will remain confusing, confounding and unevenly distributed.

Just like the actual pandemic wasn’t quite Contagion or Outbreak, the arrival of stronger AI won’t closely resemble Her or The Terminator or Leave the World Behind. Rather, it’ll be its own movie of some unspecified genre.

Which hopefully won’t be written by an AI. We’ll see.

Thanks to Drew, Nima and other friends for reading an early draft of this post.

  1. Google’s CEO says that more than 25% of their code is already being generated by AI. ↩
  2. DeepSeek, a Chinese firm, apparently trained their latest LLM for just $6 million, an impressive feat if true. ↩

What I Learned Writing a Trilogy

February 3, 2021 Arlo Finch, Author, Books, Projects, Psych 101

In October 2016, I began writing Arlo Finch in the Valley of Fire. It’s about a kid who moves to the mountains of Colorado, where he joins the Rangers. Modeled on the scouts of my youth, Rangers can do some kinda magic things because the forest outside their town is kinda magic.

arlo 1Arlo Finch sold to Roaring Brook/Macmillan as a trilogy, with Valley of Fire debuting in February 2018 and Lake of the Moon the following year. It has spawned thirteen translations published around the world. I’ve toured extensively across the U.S. and Europe. It’s been a wild trip.

Now the trilogy is finished. The paperback of Arlo Finch in the Kingdom of Shadows arrives in bookstores across the U.S. and Canada today.

As this part of the journey ends, I wanted to look back on what I learned in writing a trilogy. Here’s what I wish someone had told me before I started.

1. Have a plan, but be ready to change it.

When I sold the trilogy, my proposal included descriptions of books two and three. Here’s a paragraph I wrote in my summary of Kingdom of Shadows:

The Duchess, who has always operated through proxies and emissaries, is finally forced into the open. Charming, clever and ruthless, she’s willing to make a bargain with the boy she can’t seem to kill. Arlo must decide whether to forsake his friends and family in order to keep them safe.

No spoiler warning needed, because this doesn’t happen. The Duchess — a character I’d intended to become the series villain — never appears in the trilogy at all. There’s nothing even remotely like her. Early in writing book two, a better villain appeared, one who was a much stronger foil for Arlo.

arlo coverAnd it’s not just the Duchess. Here are seven crucial elements in the trilogy that I didn’t know when I sold it:

  1. Hadryn, and his connection to Arlo
  2. Fallpath
  3. The Broken Bridge
  4. Big Breezy
  5. The Summerland Incident
  6. Mirnos and Ekafos
  7. Why the Eldritch actually need Arlo

Shouldn’t I have planned better? Was it pure hubris to start writing without locking down these details?

Maybe. But I didn’t know about Hadryn until he showed up in a scene. He was a bit player who caught my interest and ended up becoming a costar. I didn’t know — and perhaps couldn’t have known — that I needed him back when I was writing the first book. Many things you only discover while writing.

In the end, a series outline is like a map. It can help keep you from getting lost, but if you follow it too closely you may drive right past some amazing discoveries.

2. Set rules. Break them when necessary.

Every book has rules. Some are conventions (such as spelling and punctuation), while others are specific to the genre or audience (no swearing in a kid’s book).

These rules help both authors and readers. For example, consider how we handle dialogue in prose. The author doesn’t have to add he said or she said to every line because readers have come to expect that characters alternate speaking unless otherwise indicated.

The same principle applies to point of view. Like many fantasy novels, Arlo Finch is told from a close third-person perspective. As the reader, we are hovering right behind Arlo’s shoulder. We only see what he sees, and we can only peer inside his head. Arlo Finch is at the center of every scene.

Fifty feet away, by the edge of the gravel driveway, a dog was watching him. Arlo assumed it was a dog, not a coyote or a wolf, though he had never seen one of the latter in person. The creature had a collar, which at least meant it belonged to somebody.

Arlo knew to be careful around strange dogs, but this one didn’t seem threatening. It was simply watching him.

Although the book never explicitly states it, the reader quickly understands the rule: Everything is from Arlo’s point of view.

This point of view splits the difference between a first-person narrator (e.g. The Hunger Games) and an omniscient narrator (Game of Thrones). It keeps the reader dialed in with the hero, which makes it a perfect choice for Arlo Finch…until chapter 37 of Lake of the Moon.

Arlo and his friend Indra had gotten separated. Now I needed to show what Indra was up to. But how? There was no elegant way to do it without breaking the rule on POV.

So I did it. I broke the rule. After 100,000+ words from Arlo’s perspective, we shift to Indra’s POV for that chapter.

And it was fine.

My editor noticed — but no one else did. (Or at least, they didn’t complain.) In context, it felt natural to be seeing these events from the point of view of a well-established supporting character. Later, when Indra meets up with the Blue Patrol, they’re focused on finding Arlo but the reader hardly notices that our POV character isn’t there.

Ultimately, I wasn’t breaking the rule as much as amending it: Everything is from Arlo’s point of view — unless he’s not present. Then it’s from the POV of the best-known character.

For book three, I stuck with this modified rule. One of my favorite chapters in Kingdom of Shadows is told from Uncle Wade’s perspective.

POV wasn’t the only rule I ended up breaking in Arlo Finch. I initially set out to show that Arlo’s real strength was not as a leader, but rather a follower. If there was a decision to be made, he’d help find consensus but would never take the reins.

This “hero as wallflower” approach lasted until the midpoint of book two, when he found himself facing many more challenges alone. By the third book, he’s standing up against governments and supernatural forces of unfathomable power. He’s a reluctant leader, but he’ll do what it takes.

Doing what it takes is part of writing a trilogy. You need to break rules carefully but unapologetically.

3. Build roads, not worlds.

The town of Pine Mountain brushes up against the Long Woods, a vast extra-dimensional wilderness that can only be navigated by mastering a special Ranger’s compass. Unlike a lot of fantasy literature, there’s no map at the front of the novels because the Long Woods cannot be mapped.

But there are books in Arlo Finch: Arlo and his friends occasionally consult Culman’s Bestiary to learn about the dangerous creatures they’re facing, yet I never seriously considered putting together the actual catalogue. Nor did I write out the oft-cited Rangers’ Field Book. I knew the names of the ranks and a few of the requirements, nothing more.

When it came to world building, I tried to create only what Arlo could himself encounter. I put a sticky note on my monitor to remind myself: Don’t build more than you need.

In the case of Arlo Finch, the decision was partly practical; I simply had too many chapters to write. But I also recognized a pattern I’d seen in a lot of fantasy literature:

  • Elaborately constructed universes that have little to do with the hero’s story.
  • Supporting characters who talk about events that happened long ago.
  • Visitors hailing from faraway lands the hero (and reader) will never visit.
  • Creatures described but never encountered.

Even over the course of a trilogy, your characters will only see a small corner of their universe. So focus on that. Make it rich, rewarding and most of all relevant.

4. Slow and steady wins the race.

I started Arlo Finch as part of NaNoWriMo, the annual challenge to write 50,000 words of a novel in thirty days. That’s a pace of 1,667 words per day.

While I’d had a lot of experience as a screenwriter, I was a complete newbie to the world of publishing. I knew I had a lot to learn, so I used the excuse of making a documentary podcast (called Launch) to ask hundreds of naive questions to editors, booksellers and other authors. They taught me about the joys, challenges and frustrations of getting a book published.

When told I was writing a trilogy, authors invariably offered a sympathetic smile along with a gentle shake of the head. Oh, child, they seemed to be saying. You don’t know what you’ve gotten yourself into.

Writing any book is a marathon. Writing three books back-to-back is like a race that never ends.

I wasn’t prepared for the sheer number of words I’d be typing — 202,595 in all — and having to do copy edits on one book while finishing the next. In the morning, Arlo might be investigating a mysterious campsite in Lake of the Moon. In the afternoon, he was back six months earlier in Pine Mountain, meeting his friends for the first time in Valley of Fire.

As a screenwriter, I’m used to working on one movie at a time. When writing Toto, I don’t need to worry about the sequel; it’ll only happen in wild success.

Instead, my experience writing a trilogy had much more in common with the life of TV showrunnner. My friends who write TV have to map out a season, then write the episodes, then oversee all the tweaks and changes — often all at the same time.

While it’s amazing to have this amount of control over one’s work, it requires a steady pace. There’s simply no way to sprint it.

5. The middle book is the hardest, but also the most exciting.

The middle book of a trilogy serves as a bridge between the start of the series and the end. It’s the second act, where stakes and complications are raised. As the writer, you’re spinning a bunch of plates, and then you add more.

You can find many articles about middle book syndrome, because if there’s one thing writers love, it’s lamenting about how hard writing is.

For me, the second book felt like the second season of a TV series. And I love second seasons. That’s when shows hit their stride.

Having established the characters and the rules of the world, I could introduce new obstacles and conflicts. For example, Arlo has friends — but what if his friends aren’t getting along? Arlo has a routine with family and school, but what happens when he’s away from all of that?

I wrote the second novel while I was living in Paris. My friend Damon Lindelof was in town and stopped by to record an episode of Scriptnotes. In our conversation, we discussed the list of ideas you have as a writer than you never actually get around to writing:

Damon: I always wanted to do a show about time travel. And then I suddenly realized, hey, Lost is that show. There is not time travel embedded in the pilot of Lost, but J.J. and I tried to do everything that we could to open up all possibilities in the pilot so that if we wanted to get to time travel, we could.

And I always wanted to set a show in the ’70s, and I was like, well, we’ve got time travel now. So Lost is that show, too. And I’ve always wanted to do like a pirate show. Well, Lost could be that show, too.

I always wanted to write some time travel as well. So I decided that was a thing that was possible in Arlo Finch.

Having established the mystery of the lost Yellow Patrol in book one, I wanted Arlo to not only learn what had happened, but to be the cause of it. Figuring out how to do that was brain-melting, but the resulting novel is my favorite of the series.

6. Most reviewers only read the first book.

Librarians and professional reviewers have to look at dozens or hundreds of books each year, so even if they love book one, they’re unlikely to review book two unless it’s a publishing phenomenon. That’s a real frustration when you’re writing a trilogy, because you’re deliberately portioning out your story over three books.

In the case of Arlo Finch, I wanted to push back against the tropes of the genre (cf. Harry Potter and Percy Jackson), in particular the notion that the titular hero is the chosen one. So in book one, Arlo is confused why he’s special. Then in book two, he gets the answer: he wasn’t “chosen” at all. He’s an ordinary kid who made a choice — and in the process, created the villain of the story.

But reviewers won’t see that, because they’re only reading the first book.

Now that all three books are out in the world, it’s been gratifying to see some bloggers and librarians looking at the series as a whole when making their recommendations.

I am so sad that is over but it ended in such a satisfying way! If you haven’t read this series yet, do so. It will be one of the best stories you read in your lifetime.

Returning to the TV analogy, readers who start reading Arlo Finch now will have a different experience than those who encountered it one book/season at a time. Without a year between installments, Arlo’s arc becomes a lot more clear. The setups and payoffs aren’t separated by time.

7. Clear some shelf space.

In addition to the original English version, Arlo Finch is available in 12 translations. For each of these, I receive five copies, for a total of 195 books, which have to go somewhere.

This is luxury problem, to be sure. It’s great and gratifying that so many international publishers took a chance on Arlo. And it’s exciting to cut open a box to see the new Polish or Romanian translation. But then what? I can’t read them. I don’t need them. Yet I can’t bring myself to get rid of them, either.

I hadn’t anticipated how much space it would all take.

shelf with arlo finch books lined up

In my library, I cleared room for one copy of each translation. The rest are packed away in boxes in a closet.

8. You won’t get everything right. (See #1.)

If I could go back to book one, I would make a few changes.

Capitalize Eldritch. I didn’t realize these supernatural beings would become so important. (I also didn’t know they were giants.) We started capitalizing Eldritch in book two, but it bugs me that we’re not consistent.

Set up Arlo’s origin earlier. In book one, we learn Arlo is a “tooble,” but not what it means. We get an answer in book two, but as noted earlier, most reviewers only read the first book. Fox, who appears at the end of book one, could have been less oblique.

Name the Warden. In book three, we learn that the adult Ranger Arlo talks to after the campfire in book one is the middle school band teacher (Mr. O’Brien). I wish I’d given him his name from the start.

Put Hadryn in book one. Hadryn appears early in book two, but by the rules of trilogies, he should have shown up in the first book — if not as a character, then at least as a named threat.

Call out how it’s different from other fantasy trilogies. Unlike Harry Potter or Percy Jackson, Arlo Finch sleeps in his own bed every night. It’s a much more grounded adventure. I think that’s obvious, but none of the reviewers seemed to notice. I should have underlined that.

9. Don’t wait to thank people.

Early on, I decided that I wanted to save all of the thank yous and acknowledgements until the end of the third book. My reasoning was that as a reader I generally skip these sections, so why waste the pages and the ink? Plus, wouldn’t it feel presumptuous to thank a bunch of people for a book that might not be well-received?

In retrospect, this decision was dumb.

I should have included thank yous in the first two books as well. As the past year has demonstrated, anything can happen. There was no guarantee the final book would ever come out, or that everyone would be alive to see it. So thank people often and publicly.

10. It’s hard to say goodbye.

It’s been almost 18 months since I turned in the final revisions for Kingdom of Shadows. I’m finished, yet I don’t entirely feel finished.

The series was conceived as a trilogy and definitely resolves the major open questions. Like any finale, I took advantage of the opportunity to burn down the sets and let characters move on.

Could there be another book? Sure.

Does there need to be another book? Not really.

Had Arlo Finch become a runaway best-selling phenomenon, I’d certainly be writing more books in the series. But as a writer, my most precious resource is time, and the best use of it going forward is on other projects.

Still, Arlo is special. I’ve lived with it longer than anything except Big Fish. I know every inch of the Finch house. I know Indra’s secrets. I know what happens at the Ranger equivalent of the Philmont Scout Ranch in New Mexico and the circumstances of Arlo’s first kiss.

There are Arlo Finch books that won’t be written and stories that won’t be told. But I’m grateful for the three I have, and the years it took to write them. I’m happy they’ll outlive me.


You can find Arlo Finch in bookstores everywhere. The series is appropriate for anyone age 8 and up, including quite a few adults.

General meetings don’t have to be general

August 21, 2020 Film Industry, Pitch Session, Producers, Psych 101

I like this advice from Jeff Nathanson:

It took me well over a decade to realize that general meetings are only general if I allowed them to be. And so, I changed my approach. I figured as long as I’m putting on a clean shirt and meeting with people who have the ability to hire me, I might as well try like hell to get a job.

I started to prepare for every general as if it would be my last. I would tailor a short pitch for specific executives (even when I was told not to pitch an idea). I would do my research, find out what movies they had in production, what scripts they were struggling with.

I asked questions, tried to cut through the general conversation and discuss passion projects. I asked studio executives about obscure titles they had in their library. And suddenly I started walking out with scripts under my arms, books to read, magazine articles they had optioned.

This approach makes even more sense in the age of Zoom. You need to be able to move pretty quickly from chit-chat to what you’d like to write, be it a property they control or something of your own.

This isn’t the time for a full pitch, but rather to frame an idea. “I really love heist movies. I’m working on one set on a super tanker. I’ve gone deep down the rabbit hole of research on it.”

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