--- title: "Burned Through a Month of Claude in 4 Days And Accidentally Reenacted Star Wars" canonical: https://www.hatch.org/2026/05/05/may-4-be-with-you/ author: "Steve Hatch" date: 2026-05-04 categories: ["Artifical Intelligence, Coding, Star Wars, Agents, Claude, Development, Prompt Engineering, AI-development"] tags: ["AI","Scheduling","Agents"] --- # Burned Through a Month of Claude in 4 Days And Accidentally Reenacted Star Wars **May the 4th be with you** ![Burned Through a Month of Claude in 4 Days And Accidentally Reenacted Star Wars](https://www.hatch.org/images/may-4-be-with-you.jpg) There are productivity stories. There are AI stories. And then there’s whatever this was—a four-day arc that started as a helpful experiment and ended as a fully committed, cinematic tragedy… capped off by the most on-the-nose message imaginable on **May the 4th**: > _“You’ve hit your org’s monthly usage limit.”_ Naturally. But here’s the twist: those four days didn’t feel random. They mapped almost perfectly to the original trilogy. Not metaphorically. Structurally. --- ## Day 1: _A New Hope_ — The Friendly Ping That Starts a Rebellion Like all good origin stories, this one began with a message. A long-time friend reached out—not with small talk, but with a problem: > “Scheduling spa appointments is a nightmare.” Not “slightly annoying.” Not “could be optimized.” A full-blown, multi-actor, constraint-heavy, edge-case-riddled **empire of scheduling chaos**: - Multiple providers - Limited time slots - Human preferences (the most dangerous variable of all) - Constant rescheduling entropy In other words: the Death Star, but with facials. Enter Claude. We weren’t just solving a problem—we were going to build an **agentic system**. Something that could: - Reason about constraints - Coordinate across actors - Adapt dynamically This wasn’t a script. It was a **rebellion**. And like any good rebellion, it started scrappy: - Rough prompts - Iterative thinking - “What if we tried it this way?” energy Hope was high. Tokens were plentiful. The galaxy felt… manageable. --- ## Day 2: _The Empire Strikes Back_ — Reality Pushes Back By Day 2, the system started to take shape. And immediately, the problem pushed back. Hard. Because it turns out: - People cancel last minute - Preferences conflict in non-linear ways - “Just optimize it” is the software equivalent of “just win the war” Every time we thought we had it: - A new constraint emerged - A corner case broke the model - A seemingly elegant solution collapsed under real-world messiness We escalated: - More detailed prompts - More nuanced reasoning - More “let’s simulate this scenario” Claude delivered. Repeatedly. Impressively. But the deeper we went, the clearer it became: We weren’t building a solution. We were **engaged in an ongoing battle with complexity itself**. And complexity… strikes back. --- ## Day 3: _Return of the Jedi_ — The Illusion of Victory Day 3 is where things got dangerously optimistic. We had: - A working conceptual model - A believable agent loop - A narrative that _felt_ like it could scale We weren’t just solving scheduling anymore—we were designing the **future of coordination**. This is where the prompts got… cinematic: - Multi-agent simulations - Decision frameworks - Narrative explanations of system behavior - “Explain how this evolves over time” We started telling ourselves a story: > This works. This could actually work. And to be fair, it _did_—in the same way the Rebels blowing up the second Death Star “worked.” But here’s the part nobody talks about in the highlight reel: Victory is not the same as stability. --- ## Day 4: _May the 4th_ — The System Strikes Back I woke up ready to push it further. Refine the model. Harden the system. Turn something promising into something real. Instead, I got this: > _“You’ve hit your org’s monthly usage limit.”_ On May the 4th. At that moment, the entire arc snapped into focus. Because what we had built over those three days suddenly looked… familiar. --- ## The Real Ending: Rebuilding the Jedi Is Hard Here’s the uncomfortable parallel. What we were trying to do with this “agentic scheduling system” wasn’t just solve a problem. We were trying to **rebuild an institution**—from scratch. And like Luke after _Return of the Jedi_, we had: - **No mature foundation** Just prompts, patterns, and partial abstractions - **One “teacher” (Claude) and one orchestrator (me)** No distributed system of validated intelligence—just a powerful but centralized collaborator - **Incomplete knowledge** We were discovering edge cases _as we went_, not operating from a complete model - **A hostile, chaotic environment** Real-world human behavior is the dark side of system design - **A deceptively convincing early success** Enough to believe it works… not enough to ensure it holds What “made it work”—briefly—was exactly what you’d expect: - Aggressively iterating on prompts - Pulling in more context - Building layer upon layer of reasoning - Treating the model like a hybrid of engineer, analyst, and philosopher In other words: **obsessively reconstructing capability from fragments** And just like Luke’s early Jedi Order, it was: > **inherently brittle** Because the foundation wasn’t deep—it was _assembled_. Which is why it didn’t take a catastrophic system failure to stop us. It took something much simpler. A quota. --- ## The Ben Solo of This Story: Token Limits We like to imagine systems fail because of dramatic, internal collapse. But sometimes? They fail because: - Resources run out - Constraints assert themselves - The environment reminds you who’s actually in control My “Ben Solo moment” wasn’t a rogue agent or a broken model. It was: > _“Monthly usage limit reached.”_ A single constraint, revealing how fragile the whole construct really was. --- ## What Actually “Worked” (For a While) And yet—this is the part that matters—it _did_ work. For a moment, we had: - A system that could reason about a messy real-world problem - A loop that could adapt and refine - A glimpse of what agentic coordination actually feels like That’s not nothing. That’s the early Jedi temple phase: - Small - Experimental - Held together by belief and iteration Powerful enough to be exciting. Fragile enough to collapse under pressure. --- ## Final Thought: The Future Is Real—Just Not Stable Yet Burning through a month of tokens in four days isn’t just a funny story. It’s a signal. We’re entering a phase where: - These systems are genuinely useful - They can model complex domains - They can _almost_ hold together under real-world conditions But “almost” is doing a lot of work. Right now, building with AI feels like: > Reconstructing a powerful, half-forgotten system from incomplete knowledge, in a chaotic environment, with just enough success to keep going. Sound familiar? --- ## And So… On May the 4th, I didn’t just hit a limit. I got a perfectly timed reminder: > You’re not operating a stable empire yet. > You’re still rebuilding the Jedi. And that work? It’s slow. It’s fragile. And occasionally… it ends because you ran out of tokens. May the force—and your quota—be with you.