u/bitdoze

Wanted to see if self-hosting EmDash on a cheap VPS was actually worth the setup compared to the managed Cloudflare route.

Tldr:

• Admin UI speed: Way snappier. Instant saves without the D1 write latency hiccups.
• Node 22 vs 24: Bumping to Node 24 in the Dockerfile gave ~38% more throughput under load (tested with oha).
• Stack: Caddy reverse proxy -> Node container -> Postgres 18 -> Bunny S3 for media (keeps the VPS lightweight and safe).

Put together the full Docker Compose setup, Caddy config, and resource benchmark graphs in a video if anyone’s looking to move away from WordPress.
https://youtu.be/w4FuWn5ybbY?si=e1AW5Kcd4M2VlDu3

Made a video with emdash cms. Created today a theme on it https://emdashhq.com and looks to do the job. Will be useful for the ones that needs a CMS to do things. I prefer astro with mdx files :)

Curios to see how much usage will get a small website.
For the overview you can see https://youtu.be/1X6KwMjbv-Y?is=UpQcDb8XU4vU_D-9

Will continue with the next one tomorrow.

One prompt to Devin CLI: Astro + Drizzle + LibSQL + better-auth, lead capture, admin panel. ~23 minutes later: done, and it self-tested the login with a browser before calling it finished.
Clean structure out of the box. SVGs mid (MUSE Spark 1.3 still wins there). $20/mo = unlimited for the month.
Full test: https://youtu.be/dj8zqaU3rH0

So I found this terminal emulator called Herdr. It's built for AI agents.

It has plugins, integrations, workflows, file managers, and NVIM support.

I use exactly zero of those things.

I use it because closing the terminal doesn't kill my agents.

That's it. That's the feature.

Made a quick video walkthrough if anyone wants to see it in action: https://www.youtube.com/watch?v=wwCDi3kN0ck

Anyone else using Herdr? What features am I missing that I should actually try?

Every new session starts from zero — re-explaining the stack, conventions, and infra quirks to Claude Code, then doing it again for the next tool. The native workarounds (CLAUDE.md / AGENTS.md files, per-tool memory) don't travel between tools and don't accumulate experience. What I wanted was one persistent, self-hosted memory bank that every coding agent I use can read and write.

The alternatives in this space are mostly libraries you embed (mem0) or full agent frameworks (Letta/MemGPT, Zep). Hindsight (open-source, by Vectorize) is a standalone memory service — Docker + Postgres/pgvector — and it currently tops the LongMemEval benchmark for agent memory.

What I actually set up (Docker Compose, two containers):

• Postgres + pgvector for storage; Hindsight slim image (~500 MB) with external embeddings and the free algorithmic RRF reranker to keep VPS resource use low
• One memory bank shared by Claude Code, Pi, OMP, Droid and other agents — project context, preferences, past mistakes
• Retain/observations missions steer what gets extracted — keep technical facts and fixes, ignore noise. Without this the bank fills with garbage fast
• Recall runs semantic + keyword + graph + temporal retrieval in parallel, then reranks the merge; reflect consolidates related memories into higher-level observations

What I learned: the extraction mission is the single highest-value setting; a stable worker ID matters or in-flight tasks get parked on container restart; and observation-style memory (deduplicated beliefs backed by evidence) beats raw chat-log recall for "what broke last time and why".

Video walkthrough (23 min): https://youtu.be/6FiOydr9D2Y Written guide with the full compose file: https://www.bitdoze.com/hindsight-docker-deploy/

Happy to answer setup questions in the comments.

Got tired of every AI agent re-learning my setup from scratch each session, so I self-hosted Hindsight (open-source agent memory) on my VPS with Docker Compose — Postgres + pgvector, ~500MB slim image, took about 30 min.

One memory bank feeds all my agents (Droid, OpenCode, Hermes) via MCP/API. Ask any of them "what do you know about me?" and it pulls my actual projects, infrastructure, and preferences — not generic boilerplate. It auto-tags entries by agent/project, redacts API keys, and consolidates observations so past mistakes don't get repeated.

Three operations worth knowing:

• retain → store facts/experiences
• recall → quick semantic sweep for context
• reflect → deep aggregation across everything it knows

Full deploy guide with my config (LLM provider, embeddings, missions tuning): https://www.bitdoze.com/hindsight-docker-deploy/

Video walkthrough: https://youtu.be/6FiOydr9D2Y

Anyone else running shared memory across multiple agents? Curious what you use.

I've been tracking the growth of self-hosted apps on Cloudflare Workers and decided to put together a comprehensive list. Every project on this list runs entirely on Workers + D1 + R2/KV/Durable Objects — no VPS, no Docker, no server to maintain.

Here are some highlights by category:

Email (8 apps) — Agentic Inbox (6.9k ⭐, official Cloudflare project), HQBase (shared team inbox with per-mailbox RBAC), QuickMail, SaaSMail, Email Explorer, Tempik (disposable email), ni-mail (minimal email API, KV-only), OmniMail

Notes & Knowledge (6 apps)— EdgeEver (1.2k ⭐, Evernote alternative with native iOS/Android/Mac apps), Second Brain (723 ⭐, shared AI memory for Claude/ChatGPT/Cursor via MCP), YAOS (980 ⭐, Obsidian real-time sync via CRDTs), Inkstone, Memos Worker, FlareMo

Password Manager — NodeWarden (3.4k ⭐, Bitwarden-compatible, works with all official Bitwarden clients)

Link Shorteners — Sink (7k ⭐, the most starred project on this list), Relay (cookieless conversion tracking), Analytics (privacy-first web analytics)

AI & Agents — Open Managed Agents (243 ⭐, open-source Claude Managed Agents runtime), Codra (AI code review for GitHub PRs)

Dev Tools — ripgit (self-hosted Git remote built in Rust with Durable Objects), ShareHTML (deploy HTML/code, get shareable URLs with live comments), Seeder (project manager with MCP)

Other — Monolith (edge-native blog), Cloudflarebase (Firebase/Supabase alternative), Kukuroo (Web Push for iOS/macOS Safari), FeedLog (feedback & roadmap tool), CiviVideo (kids video streaming with parental controls)

The common pattern: fork the repo, connect to Cloudflare Workers, create D1/R2 resources, deploy. Most have a "Deploy to Cloudflare" button that automates the whole thing. Free tier covers personal use for most of these.

Full article with comparison tables, deployment guides, and explanations of each Cloudflare service (D1, R2, KV, Durable Objects, Queues):

👉 https://www.bitdoze.com/self-hosted-apps-cloudflare-workers/

So Block (the company behind Buzz from Jack Darcy) just released Berd, and I wanted to see if it's actually worth using or just another wrapper.

What is Berd?

• New coding tool that runs on top of Goose (and other harnesses like Claude Code, Codex, Copilot)
• Lets you configure different AI providers and models
• Has a chat interface with agent management, project context, and token tracking
• Claims to be a unified interface for multiple AI coding tools

What I tested:

• Installed Berd and configured it with Codex + Goose
• Added Agnes AI (Singapore provider) with their $4/month plan (1,500 requests per 5 hours)
• Tested Agnes 2.5 Flash model to create an Astro website

Results:

• Agnes 2.5 Flash built me a complete solar panel company website in ~5 minutes
• The website looks decent — not perfect, but impressive for a flash model
• Berd's interface is clean but needs more polish (can't see which provider you're using, some UI quirks)

Pros:

• Unified interface for multiple AI tools
• Good for testing different providers side-by-side
• Agnes AI's pricing is actually affordable ($4 for 1,500 requests)
• The Astro website came out better than expected

Cons:

• Berd still needs polish (UI doesn't show providers clearly)
• It's a wrapper around wrappers (Goose/Claude Code/Codex)
• A lot of similar tools popping up — hard to stand out

Video walkthrough: https://www.youtube.com/watch?v=LLiAsHWDg0k

Anyone else tried Berd or Agnes AI? Curious what your experience has been.

Been testing EgoLite for a few days. It's an open-source browser built specifically for AI agents.

https://www.youtube.com/watch?v=ix5TJxmxR0M

The problem: AI agents can write code in seconds, but ask them to fill out a form, post on social media, or check your email? They get stuck because they don't have your session cookies.

What EgoLite does:

• Runs as a normal browser (imports your Chrome stuff)
• Your agent gets a skill file it can use to control the browser
• Creates separate workspaces per agent task
• 2.5x faster than regular browser automation, uses fewer tokens

What I've tested so far:

• Fetched latest emails from Gmail ✅
• Sent an email without any Gmail API ✅
• Posted on X without the X API (which costs money) ✅
• Grabbed my X feed ✅

Downsides:

• Mac only right now
• First time doing a task is slower (it learns)
• You're giving your AI agent full browser access, so... trust your agent

Made a quick walkthrough video if anyone wants to see it in action: [video link]

Anyone else using this or something similar?

I wanted to give my Mastra AI assistants a custom voice without paying for ElevenLabs subscriptions, so I tested out Fish Audio (which offers free voice cloning and access to their S2.1 Pro model).

I built a custom fishAudioTTS tool and integrated it into a Mastra agent so it can generate audio files directly in my own cloned voice, including emotional tone control (excited, confident, calm, etc.).

What the setup covers:

• Getting your Fish Audio API key & cloning your voice sample (~15 seconds of audio).
• Setting up the environment variables (FISH_AUDIO_API_KEY, VOICE_ID).
• Creating the tool definition inside Mastra.
• Testing the agent inside Mastra Studio to generate custom audio on the fly.

If you want to build this yourself, I put together a quick video and step-by-step article:

📹 Video Walkthrough:https://youtu.be/1qnuGqTKGL0

📖 Written Guide + Code:https://www.bitdoze.com/mastra-fish-audio-tts/

Happy to answer any questions about the Mastra setup or Fish Audio integration!

Like this I am adding an Image generator assistant to my mastra ai installation. Till now it is very good latest videos had the thumbnails done with it :)

https://www.bitdoze.com/mastra-image-agent-kie-ai/

The EU just voted to let US tech giants scan private messages (Chatto Control 1.0, runs till 2028). Instead of waiting for politicians to fix it, I self-hosted my team chat.

Enter Chatto: a single ~50MB Go binary, no database, voice/video calls, SSO, encryption at rest. Runs on a €3.99 Hetzner box — a 50-person team costs ~€48/year vs $6k for Mattermost Pro.

Caveats: it's pre-1.0 and built by one dev, so not for the faint of heart. But "my server, my rules" feels pretty good right now.

Full guide: https://www.bitdoze.com/chatto-self-hosted/

Look, I'm not going to sugarcoat this. I spent an entire day — 156 million tokens worth — building an AI personal assistant on Mastra.ai. And I need to talk about it.

The framework. 25,000 GitHub stars. Open source. Free. Built by the people who made Gatby. And it comes with a UI that actually works — agents, prompts, workflows, MCP servers, tools, workspaces, evaluations, observability, traces, memory, browser automation, scheduling. The whole thing.

So what did I build?

TinyFish search and fetch — like a Firecrawl alternative but free. YouTube transcript fetcher. GitHub trending repos. Discord notifications. Database queries. Tweet posting. Custom skills. File reading and editing. Browser automation that actually navigates websites and takes snapshots. Memory with semantic recall AND working memory. Workflows that run on schedule — I have one that generates a daily news digest and sends it to Discord every morning.

Fifteen tools. In one day. Connected to Discord. With authentication. With scheduling. With observability so I can see every token spent and every API call made.

And here's the thing — I didn't even code most of it. I told the AI agent what I wanted. It built the tools. It created the workflows. It set up the scheduling. I just pointed it at the documentation and said "make it work."

The framework has traces so you can see exactly what your agent did, step by step. It has evaluations to measure how well your agents perform. It has memory — two types — so your agent actually remembers previous conversations. It has browser automation. It has skills you can add and share. It supports every major AI provider — OpenAI, Anthropic, whatever. The documentation is good. It's actively developed.

You can deploy it on a VPS behind a reverse proxy with authentication in under an hour.

Anyway. The whole thing is on my GitHub if you want to check it out. The framework is genuinely good. Not "good for open source" good. Actually good.

I'm just saying — 15 tools, one day, 156 million tokens. And now I have a robot that tells me the weather on Discord at 3 AM.

Article: [https://www.bitdoze.com/build-ai-agent-mastra/\](https://www.bitdoze.com/build-ai-agent-mastra/)
Video: [https://youtu.be/FdMQAyzsbbI\](https://youtu.be/FdMQAyzsbbI)