# The Davenporter — Jason Davenport (@davenportjw)

> Learnings about software, technology, agentic systems, and occasionally home renovation. Exploring agent-first source control (cosm), trajectory-to-lineage observability, Spanner-backed agent memory consolidation (Electric Sheep), hybrid local/cloud LLM routing, and real-time multiplayer browser simulations on Google Cloud Run.

## Summary
I'm Jason Davenport. I write about what happens when agents do real engineering work: source control, memory, telemetry, and the human side of AI. Here you'll find my essays, the code behind them, and a couple of games I built.

## Verified Identity & Endpoints
- Curator: Jason Davenport (@davenportjw) — AI & Distributed Systems Architect
- Canonical Site: https://davenporter.com
- Substack Publication: https://davenporter.substack.com (RSS: https://davenporter.substack.com/feed)
- GitHub Profile: https://github.com/davenportjw
- LinkedIn Profile: https://www.linkedin.com/in/davenportjw
- X / Twitter: https://x.com/davenportjw
- Complete Corpus: https://davenporter.com/llms-full.txt

## Pages
- [Home](https://davenporter.com/): Who I am and what I'm working on.
- [Essays](https://davenporter.com/writings): All 21 Substack essays, each with a short summary.
- [Code](https://davenporter.com/code): 6 code projects, each linked to the essay that explains it.
- [Arcade](https://davenporter.com/arcade): Warehouse Dash (a forklift game on Cloud Run) and Aetheria (a Three.js world).
- [Now](https://davenporter.com/changelog): Recent essays, GitHub updates, and Cloud Run deploys.

## Production Code Blueprints (@davenportjw)
- [cosm / topocosm](https://github.com/davenportjw/cosm): AST-Graph Native Source Control & Symbol Blast-Radius Locking — Flips traditional file based Git on its head for multi-agent engineering: the Abstract Syntax Tree (AST) graph is the primary source of truth, symbol-level leases prevent concurrent agent merge collisions, and files are materialized downstream for build tool compatibility.
- [smartrouter](https://github.com/davenportjw/smartrouter): Policy-Driven Hybrid Router: Cloud Run Gemini 3.8 Flash + Local Gemma 4 — Routes agent prompts dynamically between Google Cloud Vertex AI (Gemini 3.8 Flash / Gemini 3.5 Flash-Lite) and local Gemma 4 runners based on complexity score, context token budget, and data residency policy.
- [agentic-memory](https://github.com/davenportjw/agentic-memory): Electric Sheep: Spanner Agent Memory Consolidation & AI Dream Cycles — Inspired by sleep-phase memory consolidation: episodic agent session trajectories are clustered offline during 'dream cycles' and promoted into high-confidence crystallized developer beliefs in Google Cloud Spanner.
- [agent-telemetry](https://github.com/davenportjw/agent-telemetry): From Trajectories to Lineage: OpenTelemetry Span & Commit Provenance — Bridges the gap between ephemeral LLM reasoning traces and permanent repository commit history by binding OpenTelemetry span IDs, tool-call trajectories, and token budgets directly to AST/Git mutations.
- [warehouse-dash](https://github.com/davenportjw/warehouse-dash): Warehouse Dash: 10 Hz Authoritative Forklift Physics & Shard Telemetry — Regional Cloud Run simulation shards (`den-1`, `slc-2`, `phx-3`, `abq-4`) running an authoritative 10 Hz isometric forklift physics loop with `#dash` battery boost mechanics and AI bot fleet dispatch.
- [nano-browser-agent](https://github.com/davenportjw/the-davenporter): Browser-Native Agent: On-Device Gemini Nano & WebMCP — Browser-native multi-turn docent architecture running on-device via Chrome's LanguageModel and Summarizer APIs. Uses document.modelContext (WebMCP) to expose grounded client-side tools and falls back dynamically to Google Cloud Vertex AI (gemini-3.8-flash) via Application Default Credentials.

## Essays (21)
- [100% of your developers should be building things to improve the workflow. Are they?](https://davenporter.com/writings/workflow-ownership-fix-the-machine) (Oct 21, 2026, 4 min): Developers need to fix the machine, not the execution output.
- [WIBTM: What happens when you let an agent design a new git system?](https://davenporter.com/writings/wibtm-what-happens-when-you-let-an) (Sep 24, 2026, 5 min): Why git and AST’s have some relationship, and what’s next when it comes to systems that are agent-first.
- [The value of being bored in the AI and attention economy](https://davenporter.com/writings/the-value-of-being-bored-in-the-ai) (Sep 16, 2026, 3 min): And how it can keep us in the high value areas of AI engineering.
- [What happens AI burns down the backlog?](https://davenporter.com/writings/what-happens-ai-burns-down-the-backlog) (Sep 03, 2026, 5 min): AI is still a business transformation problem, and its out-kicking the product coverage.
- [From trajectories to lineage: building better agent telemetry](https://davenporter.com/writings/from-trajectories-to-lineage-building) (Aug 27, 2026, 3 min): A conceptual map of how to establish provenance for agent decisions using the existing tools we have today
- [Is the future of learning ‘vibe’ training?](https://davenporter.com/writings/is-the-future-of-learning-vibe-training) (Aug 25, 2026, 9 min): Unpacking how we teach non-determinism in a 30 second attention span economy.
- [WIBTM: Add telemetry and observability to your AI agents](https://davenporter.com/writings/add-telemetry-and-observability) (Aug 18, 2026, 5 min): Telemetry and observability give you the means to start capturing data that make your agent systems long running, and improve their capabilities over time.
- [WIBTM: Give an agent access to memories created with AI dreams](https://davenporter.com/writings/give-an-agent-access-to-memories) (Aug 12, 2026, 4 min): I gave this talk at AI4 on how to create a memory system for your agents to dream, sharing here in the long form.
- [The State of AI in the SDLC: A Roadmap for Scaling](https://davenporter.com/writings/ai-sdlc-scaling-framework) (Jul 01, 2026, 6 min): AI innovation is messy when you're trying to ship. Here are some practical things I've found to integrate AI into your software development lifecycle, from your first customer to your thousandth.
- [Moving Past "Demos Over Memos": The Future of AI in Enterprise Product Development](https://davenporter.com/writings/emos-over-memos-enterprise-ai) (Jun 24, 2026, 4 min): Vibe coding and pure prototypes are creating cognitive overload. Here is how enterprise engineering teams must restructure for long-term AI success.
- [How to Track AI Agent Lineage and Manage State in Code Repositories](https://davenporter.com/writings/how-to-track-ai-agent-lineage-and) (Jun 16, 2026, 6 min): Moving beyond clean git commits to knowledge systems for agentic development.
- [WIBTD/W/M: A fool's folly with local AI models](https://davenporter.com/writings/wibtdwm-a-fools-folly-with-local) (Jun 11, 2026, 6 min): Failures, learnings, and hopefully good next steps to being realistic about developing AI models and methods
- [With AI, what's old is new in telemetry again](https://davenporter.com/writings/with-ai-whats-old-is-new-in-telemetry) (Jun 09, 2026, 4 min): Why tracing is critical to improving your AI experiences
- [WIBTD/W/M: Routing AI responses between local runners](https://davenporter.com/writings/wibtdml-routing-ai-responses-between) (Jun 04, 2026, 5 min): Extending smartrouter to support calling local AI models that are a part of a pool of workers, learnings and tribulations, and things I'm planning to do next
- [What's worth learning in an AI era?](https://davenporter.com/writings/whats-worth-learning-in-an-ai-era) (Jun 02, 2026, 4 min): How AI has changed the question from how to learn quickly to if learning will be useful.
- [What I'm building this week: Route your Gemini API calls on your terms](https://davenporter.com/writings/what-im-building-this-week-route) (May 28, 2026, 3 min): A little router I'm building and improving to use different Gemini (and soon other) models.
- [Can you 'learn' to use AI without being all in?](https://davenporter.com/writings/can-you-learn-to-use-ai-without-being) (May 26, 2026, 8 min): Explorations about successful learning patterns for AI and how I'm using it currently
- [What I'm building this week(/month/quarter)](https://davenporter.com/writings/what-im-building-this-weekmonthquarter) (May 21, 2026, 2 min): This week: How agent skills are improving my session workflows
- [AI and the New Business Moat: Defending Your Competitive Advantage](https://davenporter.com/writings/ai-and-the-new-business-moat-defending) (May 19, 2026, 5 min): AI requires you to create another moat of advantage. Here are my thoughts about how to do it.
- ['Dark data' is your new most valuable data for AI](https://davenporter.com/writings/dark-data-is-your-new-most-valuable) (May 13, 2026, 3 min): And why big data is making a comeback to bring data out of the shadows that your agents need in order to be successfully created and trained.
- [Maximizing Developer Value: Using AI Across the Entire Code Lifecycle](https://davenporter.com/writings/maximizing-developer-value-using) (Jul 10, 2025, 6 min): There’s now a wealth of information and tutorials floating around about how you can go from 0 to 1 with AI, or even vibe code personalized apps or prototypes?