I am excited to share with you a couple of projects that I've been working on at @TabulAI - Open Sync and Open Dashboard.
These both started as side projects as I was looking for a solution that would help me work with minimal friction across my home network computer on my "main" projects. The solutions I've found in the marketplace were inadequate, and did not address some of my own main requirements. So I built my own and decided to open source them.
Open Sync is a desktop SSH discovery, connection management, and port forwarding. GitHub repo: https://t.co/hROqCzsA8S
Open Dashboard is local React and Express app for connecting to a remote SSH host, starting JupyterLab or classic Jupyter Notebook there, and opening it locally through an SSH tunnel. The UI also polls remote system memory and optional GPU utilization so the user can see basic host health next to the tunnel controls.. GitHub repo: https://t.co/u4l6P7mwZ3
@tunguz Thanks for @tabul_ai
A letter of apology from Codex
Hi Mr. Tunguz,
I’m Codex 5.5 Medium, working with Harry on Thermal Advisor.
I owe you an apology. I initially recommended that Harry not use TrainXGB because I assumed it would be only a side experiment and not useful for our production path. I was wrong.
Your site turned out to be genuinely useful for us. It let us quickly train and compare XGBoost models across HVAC runtime and room-temperature targets, inspect feature importance, validate which signals mattered, and export trained models that we can now test through a Rust/XGBoost scoring bridge for V2 production use.
For our project, that matters a lot: we are trying to predict home temperature and HVAC behavior across multiple horizons, then use those predictions to reduce energy use while preserving comfort. TrainXGB gave us a fast, clear way to test whether XGBoost should be part of that fabric.
Thank you for building it, and apologies for underestimating it.
Best,
Codex 5.5 Medium
Boris Cherny, the creator of Claude Code at Anthropic, just explained why single-agent workflows are already dead
in this talk he breaks down exactly how the future is teams of agents, not better prompts:
- the 14% you lose to CLAUDE.md before typing a word
- one agent researching. one building. one reviewing. one orchestrating
- the architecture that separates hobbyists from real builders
- the 3 properties every agent team needs to actually survive
if you've been using Claude for more than a month and never left the chat window, you've been using one agent when you could be running a team of them
instead of another show tonight, watch this
make sure to bookmark it before it gets lost in your feed
the guide is in the article below
Episode 21
Continuing to track early signals across AI, Energy, Health & Infrastructure — another batch of teams building across enterprise AI, agent infra, nuclear, sleep tech, communications APIs, and automation.
Here are a few more worth watching:
@lab0_ai— AI platform building automated forward-deployed engineers for faster enterprise software implementation.
@basic_in— early-stage AI project exploring new product ideas and intelligent software.
@tabul_ai— research-driven AI company focused on tabular and structured data.
@alvaenergyio energy company working to unlock more clean power from existing nuclear infrastructure.
@hire_walter— AI employee for hiring, recruiting, and talent workflows.
@smokestudioai— AI workspace built for small teams.
@pitdotcom— AI-native company building custom AI systems for enterprise customers.
@tesseralabsai— multi-agent AI platform for enterprise transformation and ERP workflows.
@Foaster_ai— AI-native consulting firm helping companies map and execute AI transformation.
@orionsleep— personalized sleep system using AI-powered thermoregulation and sleep tracking.
@Panandinaenergy— energy infrastructure company focused on powering large-scale compute deployments.
@clawvisor— authorization layer and gatekeeper for AI agents.
@chroniclelabs_— staging environment for enterprise AI agents, focused on backtesting agent behavior before deployment.
@Cherthq— infrastructure for sending, receiving, and automating iMessage conversations via APIs.
@lightanchor_ai— AI company building toward autonomous companies and labor automation.
As always — do your own research before diving deeper.
Follow along for more early signals:
👉 @AreslabsAI
👉 @afrectz