Run open-source LLMs locally on Apple Silicon with Apple’s MLX-LM: `pip install mlx-lm`, then `load()` a Hugging Face model and call `generate()` (or `stream_generate()` for live tokens). This post shows 117B on an M4 Max (≈79 tokens/sec, ~63 GB peak) and 3B on a MacBook Air (≈35.5 tokens/sec, ~2.6 GB).
![The image displays a stylized world map with glowing network lines connecting various points, overlaid with numerous small rectangular boxes containing images of people and text labels. Prominently in the center, large blue text reads "AITINKERERS" and "POST-TRAINING", suggesting an informational or promotional graphic.. Text: AITINKERERS
"POST-TRAINING"
PALLADIUM
ELENIOM
BANDICAM
GARDENWARE
MOI AFARLE
ENIGMA
NO FARM IN RAIN CINE PLENIUR
Mianny Hotel
FREELANCE
ALPHONSO
S. Africa
THE FUGA
AL PRUUCE MAGNA COREM ABDUILE BERLLINE ME CEULANTEPIC AN
[numerous other small, unreadable labels and names]](https://sloppy-joe-app.imgix.net/blog_images/post-training-screen-png-7AO1.png?h=475&w=700&fit=crop&auto=format%2Ccompress&q=68)
This roundup highlights three AI directions: clinical co-pilots for healthcare workflows, “pull agents” that proactively retrieve needed information, and life planners that translate goals into actionable plans. Thanks to everyone building these tools—share your real-world wins and what’s working.
In this week’s top AI demos (#29), explore three practical highlights: agent memory for smarter ongoing context, image relighting for dynamic lighting changes, and software testing workflows that help validate results faster. Thanks to everyone sharing these demos—great ideas to try and build on.
Top AI Demos #28 brings practical projects to the community: real-time audio classification for instant listening insights, federated learning privacy that keeps training data protected, and interactive presentations for hands-on exploration. Thanks to everyone building and sharing—there’s plenty here to try, learn from, and extend.
Top AI Demos #27 shares practical builds: self-improving agents that iterate on their own, plus Musebot and Thrum demos to explore what these agent systems can do. Big thanks to everyone in the community driving hands-on experiments and sharing learnings.
Homecrew is an open-source package manager for agent skills: install a skill (a directory with `SKILL.md`) from a git tap and keep it synced across every coding agent on your machine and across your team—copying into each detected agent’s skill directory, resolving dependencies from frontmatter, and safely syncing updates via `crew update`/`crew autoupdate enable`.
In this edition of Top AI Demos: PostHog MCP delivers full product visibility, self-evolving agents, and pooled compute so teams can observe and iterate faster. Parthas brings multi-agent Claude Code for collaborative code execution—great for practitioners who want concrete workflows, not theory.
Explore three practical AI updates: voice agents, MLX trading cards, and cyber threat intelligence. Dive into how voice agents work, what’s new with MLX trading cards, and the latest threat intel insights—then share your take with the community.
In Top AI Demos #24, explore deterministic agent pipelines and how “agent memory” changes behavior, plus a careful look at code leaks. If you build or test agents, these demos are practical prompts to tighten reliability, observe memory effects, and protect code. Thanks for bringing these insights to the community.
⚡ Explore 24/7 Dev Agents paired with MCP Apps—always-on agents that keep working and MCP apps that integrate smoothly—so your workflow stays active around the clock. Thanks for building with us and sharing what you’re testing!
⚡ Autonomous software factories pair well with agentic security to help teams ship faster with safer builds. The key idea: use agents to automate parts of the software pipeline while applying security checks along the way, so reliability and protection stay built-in as work progresses.
Tinkering at Scale focused on agentic orchestration, knowledge graphs, and creative AI, highlighting practical ways to coordinate complex workflows and connect structured knowledge for better outcomes. The session shared concrete wins from creative applications, and the community energy made it easy to translate ideas into experiments.
Agent version control plus pipeline-parallel LLMs help teams iterate safely while scaling throughput. By tracking changes across agent versions and running models in parallel stages, you reduce risk and speed up experimentation—so workflows stay consistent as you push new ideas into production.
WebMCP is coming to Chrome, alongside a 3D “Codebase Cities” view to explore code visually. The stack pairs with self-improving coding agents that iterate over your codebase—helping developers move faster with clearer context and tighter feedback loops.
AI Tinkerers #18 spotlights MemoryLane’s screen context and on-device voice models—sharing how to use screen context effectively and keep voice processing on your device. Join the community discussions and learn practical approaches for building and experimenting with on-device voice experiences.
After three months deploying OpenClaw for clients, I learned agents stick when they become background infrastructure: a nightly arXiv research agent (“NO_REPLY” if fewer than 3 strong papers), a two-layer knowledge system (facts in Obsidian + decision reasoning in Honcho queried together), SnapshotClaw versioning for OpenClaw state/config/cron/skills, and a Reachy Mini robot brain wired into Botwick for persistent voice + context.
In AI Tinkerers #17, we build multi-agent Openclaw comics and tackle security considerations while adding an AI fact-checker. Thanks to the community, we’ll share practical notes on prompting and safety—plus how the fact-checker helps keep claims grounded.
AI Tinkerers #16 dives into vector database evolution and persistent agent memory. The session highlights practical shifts in how embeddings are stored and retrieved, plus strategies for keeping agent context across sessions—so builders can design more reliable, stateful AI systems.
Community Spotlights • Issue #15.
Community Spotlights Issue #14 highlights reliability, offline safety, and product-ready AI builds.
Community Spotlights • Issue #13.
Community Spotlights • Issue #12.
Leverage air-gapped OCR with DSPy Vision to build better agents.
⚡ AI Gatekeepers + Legislative Monitoring with Gen AI highlights how Gen AI enables gatekeeping and legislative monitoring.
⚡ RapidFire combines Hyperparallel Tuning with AI Code Tracking.
This post covers Claude Draws, the Second Brain API, and more.
This post highlights On-Device Apple VLM and Windows Speech 🚀.
Image downscaling attacks and an open-source benchmark for app gen offer practical, reproducible research for the community. This update presents hands-on guidance, shared tooling, and benchmarks to help researchers and builders strengthen generation apps together.
⚡ Prompt Hijack + Deterministic Co‑Pilots — See How.
![The image displays a stylized world map with glowing network lines connecting various points, overlaid with numerous small rectangular boxes containing images of people and text labels. Prominently in the center, large blue text reads "AITINKERERS" and "POST-TRAINING", suggesting an informational or promotional graphic.. Text: AITINKERERS
"POST-TRAINING"
PALLADIUM
ELENIOM
BANDICAM
GARDENWARE
MOI AFARLE
ENIGMA
NO FARM IN RAIN CINE PLENIUR
Mianny Hotel
FREELANCE
ALPHONSO
S. Africa
THE FUGA
AL PRUUCE MAGNA COREM ABDUILE BERLLINE ME CEULANTEPIC AN
[numerous other small, unreadable labels and names]](https://sloppy-joe-app.imgix.net/blog_images/swyx-png-6O-h.png?h=475&w=700&fit=crop&auto=format%2Ccompress&q=68)
Voice agents rely on multi-turn chats where speech diverges from text; evals help but aren’t enough. Use hands-on testing, repeatable evals, and context engineering; state-machine workflows. A 30-turn Gemini Live benchmark (~75k tokens) shows limits but improved reliability with RAG and prompts; see Hamel’s FAQ and Dex’s context engineering.
This week’s top demos feature Swift-native agents, micro:bit MPC, and Infinite Brainrot—an inviting snapshot for the community to explore these projects.
Local AI brings browser agents and ultra-low-latency meeting assist, delivering fast, client-side AI support directly in meetings.
![The image displays a stylized world map with glowing network lines connecting various points, overlaid with numerous small rectangular boxes containing images of people and text labels. Prominently in the center, large blue text reads "AITINKERERS" and "POST-TRAINING", suggesting an informational or promotional graphic.. Text: AITINKERERS
"POST-TRAINING"
PALLADIUM
ELENIOM
BANDICAM
GARDENWARE
MOI AFARLE
ENIGMA
NO FARM IN RAIN CINE PLENIUR
Mianny Hotel
FREELANCE
ALPHONSO
S. Africa
THE FUGA
AL PRUUCE MAGNA COREM ABDUILE BERLLINE ME CEULANTEPIC AN
[numerous other small, unreadable labels and names]](https://sloppy-joe-app.imgix.net/blog_images/me-bridge-png-a8NW.png?usm=20&usmrad=15&w=700&h=475&fit=crop&auto=format%2Ccompress&q=68)
We built Vibe Kanban (70K+ lines) to show vibe coding at scale: start every task with a planning step, cap PRs (<400 LOC, <10 files) and ship incrementally; enforce cross-stack type safety with ts-rs shared types.ts; use per-session DBs for clean dev; split backend into crates for compile-time guardrails.
![The image displays a stylized world map with glowing network lines connecting various points, overlaid with numerous small rectangular boxes containing images of people and text labels. Prominently in the center, large blue text reads "AITINKERERS" and "POST-TRAINING", suggesting an informational or promotional graphic.. Text: AITINKERERS
"POST-TRAINING"
PALLADIUM
ELENIOM
BANDICAM
GARDENWARE
MOI AFARLE
ENIGMA
NO FARM IN RAIN CINE PLENIUR
Mianny Hotel
FREELANCE
ALPHONSO
S. Africa
THE FUGA
AL PRUUCE MAGNA COREM ABDUILE BERLLINE ME CEULANTEPIC AN
[numerous other small, unreadable labels and names]](https://sloppy-joe-app.imgix.net/blog_images/screenshot-2025-08-11-at-12-25-38-pm-png-Sxr1.png?h=475&w=700&fit=crop&auto=format%2Ccompress&q=68)
Claude Code tips emphasize an Explore/Plan/Execute/Commit loop, grounding tasks with CLAUDE.md in root and subfolders, using /resume and Esc+Esc to reuse context, and Plan Mode for safe planning. Leverage MCP servers and Github integration (/install-github-app), plus hooks and subagents to parallelize work; keep a compact context with updates to CLAUDE.md.
Practical AI Builds returns on August 11 with hands-on formats covering Scheduling Agents, MoE Assembly, Virtual Try-On, and more—delivering actionable techniques, real-world demos, and community-driven insights for builders and researchers.
![The image displays a stylized world map with glowing network lines connecting various points, overlaid with numerous small rectangular boxes containing images of people and text labels. Prominently in the center, large blue text reads "AITINKERERS" and "POST-TRAINING", suggesting an informational or promotional graphic.. Text: AITINKERERS
"POST-TRAINING"
PALLADIUM
ELENIOM
BANDICAM
GARDENWARE
MOI AFARLE
ENIGMA
NO FARM IN RAIN CINE PLENIUR
Mianny Hotel
FREELANCE
ALPHONSO
S. Africa
THE FUGA
AL PRUUCE MAGNA COREM ABDUILE BERLLINE ME CEULANTEPIC AN
[numerous other small, unreadable labels and names]](https://sloppy-joe-app.imgix.net/blog_images/diagram-webp-ZQJm.jpg?h=475&w=700&fit=crop&auto=format%2Ccompress&q=68)
We built Lovable for AI Agents to skip days of OAuth and tooling decisions; powered by Composio's managed tools with 500+ apps, letting you generate a live, specialized agent in under ten minutes via /api/generate-agent. Authentication flows use /api/create-connection—choose Composio-managed or custom credentials—and tool discovery via COMPOSIO_SEARCH_TOOLS.
Cut latency, ditch the cloud—our hottest AI tinkerer demos on July 28.
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