Deep in a session, right when I understood the work best, I wrote down what to build next as a short structured capsule. Then I cleared the context. A fresh session with none of that understanding read the capsule cold and built it to spec. It did not know it was finishing its own work. Handoff notes fail two ways: they ROT (you forget) or they CANNOT TRAVEL (a fresh session can't read your mind). And terse notes silently drop the two things that matter most: WHERE the work goes and what DONE looks like. I measured it. Labeled-field capsules scored 10/10 on intent fidelity vs terse prose at 9.67, and prose's weakest spots were exactly WHERE and ACCEPTANCE. The honest part: the model still ran ~31% of malformed input instead of refusing it, so that check is deterministic code, not a model call. It understands the capsule. It does not get to decide the capsule is safe. Free CLI and Claude Code plugin, MIT. Try authoring one capsule next time you are deep in something, then clear and let a fresh session build it. github.com/gtsbahamas/intent-capsule

AI Developer Accelerator — Coaching Call - June 16 VIEW RECORDING - 89 mins (No highlights) Meeting Purpose Share project updates and discuss strategies for AI development. Key Takeaways - Fable's absence is a setback, but developers are adapting with multi-model workflows (e.g., Claude for planning, Codex for coding) and focusing on deterministic scaffolding to maintain control. - New projects include an AI-native CRM for UK estate agents (Ryan), a positive-only "KindMark" platform for service workers (Ty), and an AI photo booth (Juan). - Patrick developed "AgentOps," a meta-scaffolding for Hermes using NATS as a "nervous system" to monitor and manage his home lab infrastructure. - A key strategy is using an "adversarial" system prompt to force the AI to challenge assumptions and clarify the core business problem, preventing it from amplifying broken processes. Topics Fable's Absence & Mitigation Strategies - Fable's shutdown is a significant setback, but developers are adapting with multi-model workflows. - Ryan: Uses Opus for iteration on a Fable-generated V1 plan. - Ty: Used Fable for initial problem-solving but found it unusable for security auditing, a critical step. - Paul: Combines Opus for projects with Codex for validating requirements documents. - Patrick: Prefers a collaborative model that challenges assumptions over one that simply executes instructions.

📝 SUMMARY This week's call opened with the community offering condolences to Patrick Chouinard and Paul Miller, who both recently experienced family losses. Patrick shared how Claude helped him compress two months of estate administration into 48 hours during his bereavement. The technical discussion centered on coping strategies following the sudden unavailability of Anthropic's Fable model, with members sharing alternative workflows combining Claude Opus 4.8, Codex GPT-5.5, and the emerging Fusion architecture. A strong consensus emerged around the danger of automating broken business processes, alongside practical demonstrations of adversarial prompting and agent scaffolding strategies. 💡 KEY INSIGHTS Estate administration acceleration: Claude processed funeral home paperwork and proactively searched government websites for required forms and benefits, reducing administrative burden from months to hours while demonstrating unexpected emotional sensitivity by pacing tasks and flagging only time-sensitive items. Deterministic over autonomous: Keep systems as deterministic as possible, using AI decision-making only where necessary. The value in coming years lies in scaffolding and infrastructure rather than end-to-end autonomy. Model specialization: For terminal, infrastructure, and script work, GPT-5.5 (Codex) currently outperforms Claude Opus 4.8, while Opus remains superior for UI-backed application development. Adversarial prompting: Patrick's system prompt configures Claude as a challenging business analyst that asks "what problem are you actually trying to solve?" rather than accepting stated solutions at face value. Placed in Claude.md at the user level, it applies to every session including Claude Code. Process integrity warning: AI amplifies broken business processes rather than fixing them, making dysfunction bigger and more visible. Intention is a muscle that atrophies when over-relying on highly autonomous models. Intent queue workflow: Ty's method uses Claude's background commands to capture context-rich questions, storing them locally to surface as a primed queue at the next session, saving token spend on re-priming.

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Plot twist: bringing a friend to watch you work is now a certified business strategy, "guarded surfaces" have nothing to do with skateboarding, and Anthropic's Fable model as been removed—so if you haven't stress-tested your architecture with it yet, consider this your friendly eviction notice. 📞 HOW THE CALLS WORK The calls can run 2+ hours. We want to make sure we're respecting everyone's time. Especially those of you who actually show up. Here's the structure: 👉 Reply to this post with your questions before the call 👉 If you submit a question and you're on the call, you go first 👉 We work through questions in the order they came in 👉 Then we open it up for everyone else If you can't make the call but want your question answered, drop it in the comments. We'll get to it. But priority goes to people who are there. The goal is simple: if you're taking the time to show up, you shouldn't have to wait behind questions from people who aren't even on the call. Curious if Ty nailed the "explain it to a 10-year-old" test for ShipSafe's messaging? Wondering how Juan's first AI Booth deployments went with his observer friend catching all the customer reactions? Or whether Ryan managed to squeeze every last drop of Fable wisdom before the paywall hits? Come find out—or bring your own experiments to share. 🔗 ZOOM LINK (save this) https://us06web.zoom.us/j/81995207847?pwd=Xe6u6LmIQOmCP5VTnOwWYjDBfZNKGB.1 📅 WHEN Tuesday June 16th at 6PM ET Looking forward to seeing you on the call!